METHOD AND SYSTEM FOR ENHANCING OPTICAL MODELING OF PRECIOUS STONES.

专利摘要:
A method of constructing a virtual gemstone model comprising the steps of for each identified inclusion, performing the following steps: determining a location and a 3D shape of the inclusion in the interior volume of the gemstone; capture at least one image of inclusion; use the image at least to determine relevant optical characteristics of the inclusion; and constructing a virtual 3D model of the inclusion, said model comprising the 3D shape of the inclusion and optical properties of the inclusion based on said optical characteristics.
公开号:BE1018615A4
申请号:E2008/0553
申请日:2008-10-06
公开日:2011-05-03
发明作者:Sergey Borisovich Sivovolenko
申请人:Ideal Scope Pty Ltd；
IPC主号:

专利说明:

METHOD AND SYSTEM FOR IMPROVING OPTICAL MODELING
PRECIOUS STONES
FIELD OF THE INVENTION
The present invention relates to the evaluation of precious stones, and more particularly to the improvement of the computer modeling of precious stones, and more specifically the modeling of internal defects (inclusions). Potential applications of the invention include, but are not limited to: modeling and viewing raw (uncut) gemstones; the blooming of precious stones; the modeling and observation of cut / polished precious stones, proposed to be carved in an uncut stone; or an existing stone cut and polished; the computerized determination of the purity of proposed stones or existing cut / polished stones; and evaluating the value of a gemstone. Embodiments of the invention are described herein with particular reference to the evaluation and computerized modeling of diamonds, but it will be appreciated that the invention is equally applicable to the modeling and evaluation of other types of precious and semi-precious stones.
BACKGROUND OF THE INVENTION
The value of a cut diamond is substantially determined by the "4 Cs": carat, color, clarity (purity) and cut (size). Of these, the number of carats and the color are substantially objective characteristics that can be assigned specific values very precisely. The number of carats is simply the weight of the diamond, one carat being equal to 200 milligrams. The color, in terms of hue and transparency, can also be easily measured objectively, although the results of this measurement depend relatively on the lighting conditions. Most diamonds used as gemstones are substantially transparent with little hue ("white diamonds"). However, the most common impurity, nitrogen, causes a yellow / brown hue that is present, to some degree, in almost all white diamonds. The most commonly used color grading system is the Gemological Institute of America (GIA), which assigns a grade of D (no color) to Z (light yellow color) to nominally white diamonds. Generally, low color is more desirable, although diamonds with hues other than yellow / brown, such as pink or blue diamonds, may be more valuable than white diamonds because of their scarcity and / or level of interest in the market. In all cases, the evaluation of the hue of a diamond with respect to the color standards, and of the transparency in terms of absorption of the light, presents few practical difficulties.
Purity and size, on the other hand, influence the visual appearance of gemstones in a relatively complex way. In fact, these features have complex interactions with each other, as well as with lighting, the viewing position, and so on. As a result, objective and widely accepted measures of purity and size have proven to be far more difficult, and the measures that exist do not always agree with the subjective beauty of the gemstones being valued by customers. , in different lighting conditions and conventional observation.
The purity of precious stones, in particular, is a quality related to the existence and visual appearance of internal defects often called "inclusions", or "internal characteristics". Purity is also affected by surface defects, or appearance defects. There are different causes of inclusions, which may be, for example, crystals of a foreign body, another crystal of the gemstone itself, or imperfections such as cracks that may appear whitish or cloudy. The purity of a gemstone, like a diamond, depends on the number, size, color, location, orientation and visibility of the inclusions.
The most commonly used purity rating scales are those of the GIA and the Hoge Raad voor Diamant or the Diamond High Council (HRD), where the purity is measured at 10x magnification with illumination. "Black background" specified. This actually involves lighting the base of the stone from the side, and observing the resulting appearance of the stone from the top with a magnification of 10 times. The GIA Diamond Rating Scale offers a total of 11 indices in six categories. The categories and indices are: no fault (FL), no internal fault (IF); tiny inclusions (WS1, WS2); very small inclusions (VS1, VS2); small inclusions (SU, SI2); and many inclusions (II, 12, 13). Gemmologists are trained to assign indexes according to the GIA scale in a consistent manner.
As noted above, complex interactions exist between purity and size. In particular, by defining inclusions in a rough (uncut) gemstone, it is possible, in principle, to de-gem the gem so as to minimize the impact of these inclusions on the purity of the final cut and polished stone. . This is not obvious though. Bruting is one of the most sought-after skills in the diamond industry. Crude stones are valued from an economic point of view, to maximize the value and marketability of rough cut diamonds. All things being equal, larger diamonds (that is, having a higher carat number) are more valuable. Therefore, it is generally desirable to cut the largest stones possible in the crude, assuming that this can be done without causing an unacceptable decrease in the purity of the resulting stone.
Modern diamond bristling is facilitated by sophisticated electronic and computerized tools. Scanning devices, often including digital imaging and laser telemetry technologies, are used to capture a three-dimensional (3D) computer model of rough stone before cutting. At this stage, images of the inclusions can also be captured, and their relative location in the stone is estimated. Computer software tools then help the debrider to place the cut stones proposed in the three-dimensional model of the rough stone, and to evaluate their potential value, before proceeding to a real size.
However, there is still considerable room for improvement in the tools to facilitate the gutting and evaluation of gems. As noted above, the purity estimate is based on visual appearance, with 10x magnification and specified lighting and observation conditions. It must be appreciated that the actual visual appearance of a gemstone under these conditions does not depend solely on the number and / or types of inclusions. In particular, the visual appearance also depends on the location and orientation of the inclusions with respect to the facets of the cut stone. For example, a thin crack may rarely be visible when looking at the edge, while the same cracking seen from the side can substantially compromise the purity of the cut stone. These considerations are significantly complicated by the reflection and refraction of light at the facets of the cut gemstone. In particular, the facets of a diamond are designed to act as mini-mirrors, which reflect the light toward the surface of the diamond, to enhance its visual appearance. However, this mirror effect can also "multiply" the inclusions, so that they may appear more numerous than they really are, and they can be visible, in reflection, from angles different from those directly presented to the observation position.
By taking all these complex factors into account, the bridging is not a simple identification of an optimal compromise between the size of a cut stone and the number of inclusions. The most sophisticated software tools provide the user with a more accurate representation of the visual appearance of the cut stone, taking into account optical effects such as reflection and refraction of light. In the case of internal defects, this may include placement of filiform or false-color representations of inclusions in a three-dimensional model so that the apparent number and actual size of the inclusions in the resulting stone can be evaluated on the screen. Another level of sophistication involves capturing images (such as photographs) of inclusions, and placing these photographs on the visual images displayed to the user. Although these approaches are useful, they are still inadequate because they can not accurately represent the actual visual appearance of inclusions in the finished gemstone. Photographs, in particular, are limited to the presentation of inclusions as they appear when photographed in uncut stone, and not in specific lighting conditions applied for the purity assessment. Existing approaches have, therefore, been found to be inadequate for making a virtual purity estimate during the bridging process, and this aspect of bridging thus remains an imprecise art based on the skills of the de-brush and, inevitably, a certain degree of intuition, or even luck.
In addition to bruting to optimize the purity assessment under the GIA evaluation conditions, it is also often desirable to evaluate the appearance of an existing cut stone, or a proposed gemstone to be cut. in a rough stone, in a variety of alternative lighting conditions. In fact, the lighting conditions used for assessing the purity of the GIA are not the conditions under which the stone is observed by customers in the shop, or during the normal wearing of a diamond jewel. Thus, it may be extremely useful to provide improved computer modeling of gems with internal defects for "virtual observation" in a variety of viewing positions, and in a variety of lighting conditions. In fact, while current ray tracking software is capable of generating virtual images of three-dimensional objects under arbitrary viewing conditions, and even animating these images, there is currently no effective way to obtain a sufficiently accurate model of a gemstone with internal defects that can be used with these software.
An object of the present invention is therefore to provide an improved virtual modeling of the visual appearance of rough and cut diamonds, for example, for their evaluation, their bridging and their virtual observation.
SUMMARY OF THE INVENTION
In one aspect, the present invention provides a method according to claim 1.
Advantageously, the embodiments of the method of the invention mitigate the disadvantages of the prior art by providing an improved virtual optical modeling of inclusions in precious stones. In particular, although the methods of the prior art are based on filiform, false-color or unrealistic models of inclusions, or, alternatively, superimpose images of inclusions captured from fixed locations under lighting conditions. The present invention enables the inclusions to be modeled in three dimensions in a manner that allows the subsequent generation of photo-realistic three-dimensional images of the gemstone under arbitrary viewing conditions. This capacity is considered to be unprecedented in the prior art.
A presently preferred embodiment of the process is defined in claim 2.
The gemstone can be, for example, a diamond. In addition, the gemstone can be rough or cut / polished.
In preferred embodiments, the method of the invention may be used to provide the user with a variety of different types of information relating to the visual characteristics of the gemstone. In an exemplary embodiment, the visual characteristic is a predicted visual appearance of the gemstone observed from a specified viewing position under specified lighting conditions. This can be done by using the virtual gemstone model in combination with computerized optical ray tracking techniques to generate one or more visual images of the gemstone seen from any position. desired observation under any desired lighting and observation conditions.
For example, detailed models of ambient lighting conditions can be generated using HDRI (High Dynamic Range Imaging) technology. According to this approach, the actual environmental conditions are recorded by capturing images of a reflecting sphere in the desired environment from multiple viewing locations, and using multiple exposure levels. These images can be converted to an HDRI model of the environment, taking into account all light sources and objects in the environment, which can then be used to generate visual images of the gem such as it appears if it is placed in the same environment.
The generated visual images of the gemstone may also take into account the viewing optics (including, if desired, the optical characteristics of the human eye, as well as optical features such as a magnifying glass, microscope, camera, etc.). These models can use Modulation Transfer Functions (MTF) of the components of the modeled imaging system to simulate the quality of the actual observed image. The models can also take into account other imaging parameters such as magnification, the distance between the imaging system (such as a lens) and the gemstone, the resolution, the focal length, the aperture, depth of field, sharpness, etc.
The three-dimensional photo-realistic images of the gemstone can be presented in a two-dimensional (ie monoscopic) form, like a conventional photograph. Alternatively, the three-dimensional photo-realistic images of the gemstone can be presented in stereoscopic form, such as for example by generating and displaying dual images that can be viewed using a 3D display device, such as two-color lenses (green / red for example), polarized lenses, or liquid crystal shutter glasses.
The color and / or brightness of the generated visual images can / may be adapted if desired, for example to model variations in lighting conditions.
When the gemstone is a rough stone, the visual characteristic may be the predicted visual appearance of a proposed cut and / or polished stone to be carved into the rough stone.
In another exemplary embodiment, the information relating to a visual characteristic of the gemstone may be an index of purity of a gemstone cut and polished. A purity index can be assigned by generating a photo-realistic virtual image of the cut and polished stone under standard GIA lighting conditions, using computerized ray tracking techniques, to produce a virtual image corresponding to the image. actual image that is observed during a standard purity index determination process. The purity index can then be assigned by a qualified gemologist, in reference to a displayed virtual image, or, alternatively, can be automated, by computer software evaluating the size and visual appearance of each visible inclusion and applying Purity index determination rules, such as the purity index determination rules defined by the HRD.
A preferred embodiment is defined in claim 7. The optical characteristics assigned to each inclusion may be preference parameter values selected from a list including color, hue, fluorescence, and transparency. In the case of a point, it is not necessary to assign other parameter values, since the location of an inclusion in the form of a point may be sufficient to fully model its optical properties. via ray tracking methods. Since a cloud is a set of points, additional parameter values may also be unnecessary. However, in order to obtain accurate modeling, it may be useful to evaluate the density of the cloud, which can be measured by its apparent hue and / or transparency. A crack may be given a hue (i.e., apparent brightness or darkness), and / or a degree of transparency / translucency.
Although the prior art digitization and / or gem observation device uses black and white imaging devices, color imaging devices can replace them to capture the color information of each color. inclusion. This color information can then be used to assign corresponding optical characteristics to the inclusion.
In general, however, the optical characteristics attributed to each inclusion preferably comprise a texture or "skin", representing the optical properties of the inclusion. Advantageously, the use of texturing allows an extremely detailed modeling of the visual appearance of the inclusions.
According to the embodiments of the present invention, the texture includes the color or black-and-white imagery information of the inclusion, as well as the mapping of that information to the geometry of the inclusion. Therefore, a texture can consist of a set of pixels, each having properties such as color, brightness, transparency, etc., and a mapping of the set of pixels with corresponding coordinates on the surfaces of the inclusion. The texture is preferably obtained by the projection of images of inclusions calibrated (such as digital photographs) on the geometry of the inclusions, then merging all the projections (as for example the images captured in different orientations) into a single texture. Preferably, the texture is applied to the geometry of the inclusion during a visual image rendering process used to generate three-dimensional photo-realistic images of the gemstone.
A Bidirectional Reflectance Distribution (BRDF) function can be determined and assigned to each inclusion. As is known to one skilled in the field of optical arts, the BRDF describes the relationship between light reflected from a surface and light incident on the surface, taking into account the directions of incident light and light. reflected light. The BRDF formalizes the observation that the hues and brightness of an object depend on the direction of illumination and the direction of the observer.
In different embodiments of the invention, different levels of interaction and operator intervention can be used during the construction of a virtual model of a gemstone. Preferably, each step of the method is partially or fully automated. A user interaction can be obtained, for example, to identify each inclusion and / or map its shape in 3D. User interaction can also be used to assign a type to each inclusion. In addition, the user interaction can be used to assign parameter values to each inclusion. However, it is particularly preferred that each step be automated as much as possible in order to simplify the task of the operator, and to obtain maximum coherence and precision during the construction of the 3D virtual model.
In exemplary embodiments, the process of assigning optical characteristics to each inclusion, and in particular to creating a texture of each inclusion, and assigning a BRDF to the surfaces of the inclusions, can use a process of automated radius tracking. In particular, the step of capturing at least one image of each inclusion is preferably performed under controlled and known lighting conditions, which can be reproduced during the construction of computer generated images using techniques. radius tracking. The computer-generated images can then be compared with the captured images of the inclusion, the assigned optical characteristics can be varied (as for example by selecting or modifying the appropriate textures and BRDFs), and the computerized image generation can repeated, until the computer-generated image matches the actual captured image. Advantageously, this approach provides an automated method for building accurate 3D virtual models of each inclusion.
For simple inclusions, such as dots, needles, or simple cracks, a single captured image may be sufficient to assign an inclusion type, to assign any additional optical characteristics (such as parameter values, textures and / or BRDFs) and to build a 3D virtual model of inclusion. However, for more complex inclusions, such as irregularly shaped clouds, it will be appreciated that the appearance of inclusion may be quite different when viewed at different angles. Therefore, in this case, a plurality of images of the inclusion can be captured from different points of view, and appropriate parameter values, such as texture and / or transparency, can be determined according to the different points. of view, then combined to generate the complete 3D virtual model of inclusion. It may also be desirable to capture multiple images from each viewpoint under different lighting conditions to improve the BRDF estimate.
In another aspect, the present invention provides a device according to claim 14.
The presently preferred embodiments are described in claims 15 to 17.
In another aspect, the present invention provides a system according to claim 18.
The presently preferred embodiments are described in claims 19 to 25.
In preferred embodiments, the digitizer includes a digital image capture device, such as a digital camera, and the instructions executable by the processor for capturing at least one image of each include preferably include instructions enabling the digitizer to capture an image using the digital image capture device, and to transmit the captured image to the computer.
In preferred embodiments, the computer is also configured to display the captured images to the user on the display device, and to generate and display the virtual images of the gemstone on the device. display. The user can provide an entry to the system, including an entry related to the identification of visible inclusions, the location of visible inclusions, the 3D shape of visible inclusions, the type of inclusion, and / or the optical characteristics of the inclusion, via the user input device (s).
In particularly preferred embodiments, the computer is configured to generate and display photo-realistic virtual images of the gemstone and / or other gemstone, using the 3D virtual model. precious stone. In particular, photo-realistic images can be generated using ray tracking methods. More particularly, preferred embodiments of the system are capable of generating images representing a predicted visual appearance of the gemstone observed in a specified viewing position under specified lighting conditions using computerized ray tracking techniques. The generated visual images may be visual images of a rough gem, or may represent the predicted visual appearance of a cut and / or polished gemstone proposed to be carved in a rough stone. A skilled operator may be able to evaluate a purity index of a proposed gemstone cut and polished based on the visual images displayed.
In some embodiments, the computer may also be configured to automatically evaluate a purity index of a proposed gemstone cut and polished using ray tracking methods to generate a visual image of the gemstone in standard purity index determination lighting conditions, and calculating a purity index by analyzing the image and applying index determination rules.
Other features and preferred advantages of the present invention will be apparent to those skilled in the art from the following description of the preferred embodiments of the invention, which should not be construed as limiting the scope of the invention. defined in any of the above statements, or in the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
The preferred embodiments of the invention are described with reference to the accompanying drawings, in which:
Fig. 1 is a diagram of a system for generating a 3D optical model of a gemstone for evaluation according to a preferred embodiment of the present invention;
Fig. 2 is a flowchart illustrating a method of generating a 3D optical model of a gemstone using the system of Fig. 1;
Figure 3 schematically illustrates a 3D model of a gemstone according to an embodiment of the present invention;
Figure 4 schematically illustrates a display of a user interface of the system of Figure 1; and
Fig. 5 is a diagram illustrating a preferred set of image capture of a gemstone cut according to an embodiment of the present invention.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
Figure 1 schematically illustrates an exemplary system 100 according to the present invention. The system 100 includes a gemstone digitizer 102 that is configured to measure a gemstone 104 for the purpose of constructing a three dimensional (3D) model of an outer surface of the gemstone. The scanning device 102, according to the embodiments of the present invention, is also capable of capturing information relating to the identification, location, shape and appearance of inclusions in the gemstone 104 In particular, the digitizing device comprises a support 106 on which the gemstone 104 is fixed. The support 106 is able to rotate and / or translate to reposition the gemstone 104 relative to a light source 108 and an imaging device 110.
In the exemplary embodiment illustrated in Figure 1, the gemstone 104 is a rough diamond. However, the embodiments of the invention can also be used for modeling and evaluating cut diamonds, and / or other precious stones.
Scanning device 102 is generally configured to illuminate gemstone 104 using a light source 108, and to capture images using an imaging device 110, which is preferably a digital imaging device such as 'a digital camera. Scanning device 102 may include additional light sources, to illuminate gemstone 104 at a variety of different angles, for the purpose of capturing differently illuminated images using digital imaging device 110. The sources of light, including the light source 108, can be controlled by computer or manually, to optimize the identification, positioning and visual analysis of inclusions in the gemstone 104. Capturing images of the stone In a variety of different orientations, and possibly in different lighting conditions as well, the precious material 104 is the primary means by which the digitizer 102 performs measurements of the gemstone 104.
Although not shown in FIG. 1, the scanning device may include additional components for measuring the gemstone 104. For example, in some embodiments, the scanning device may also include laser devices (not shown) for scanning the surface of the gemstone 104 to better identify indentations and other surface features.
Various digitizing devices generally suitable for use with the present invention are known in the prior art. These include the device described in US Pat. No. 6,239,867 to Lalit K. Aggarwal, published May 29, 2001, and British Patent Application GB 2081439A to Gersan.
Establishment, filed June 4, 1981 and published February 17, 1982. Preferably, a device of the conventional type described in European Patent Application No. 1211503, in the name of Diamcad and the present inventor, may be used in the embodiments of the present invention.
A scanning device of the type described in EP1211503 has a greater ability to identify the location of inclusions in the interior volume of the gemstone 104. The aforementioned documents are incorporated herein by reference.
Although it is possible, in principle, to provide a single digitizing device 102 implementing all the functionalities of the embodiments of the present invention, in practical terms it is currently preferred that the functions of the device 102 described here are actually provided by two separate devices. As described in more detail below, with reference to Fig. 2, the methods according to the embodiments of the present invention comprise separate steps of digitizing an outer surface of the gemstone 104, and imaging interior features (i.e., inclusions) of the gemstone 104. According to the inventor, there is currently no device 102 that is able to perform these two functions optimally. Products such as Helium ™ supplied by Octonus / Lexus, DiaScan ™ supplied by Sarin, are suitable for digitizing external surfaces of rough and / or cut precious stones. In addition, products such as Oconus / Lexus' Μ-Box ™ and associated Oxygen ™ software, which include a binocular microscope, a digital camera, and a computer-controlled lighting package, are designed to capture pictures of the internal features of gemstones. It will therefore be appreciated that the scope of the present invention covers the use of separate scanning and / or imaging devices to provide corresponding functionality in different embodiments. In addition, it will be appreciated that the term "digitization" as used herein may include mapping (mapping) of the outer surface, and imaging of the interior.
Scanning device 102 is connected to a computer 112 comprising a central processor 114, which interfaces with storage devices, such as a nonvolatile storage device (such as a hard disk) 116 and a volatile storage device (as for example a random access memory) 118. The memory 118 contains program instructions 120 intended to be executed by the processor 114, in order to perform various operations of the computer 112, including those related to the implementation of the present invention. As will be appreciated, the memory 118, and the non-volatile storage device 116, also contain program instructions to be executed by the processor 114 to perform a variety of other support functions, including various functions of the processor. operating system of the computer 112.
The computer 112 further comprises a peripheral interface 122, operably associated with the processor 114, for communicating with the digitizer 102. The peripheral interface 122 may be a standard interface, such as a parallel or serial port ( USB for example), or a proprietary interface.
The computer 112 is also interfaced with a display device 124, and user input devices 128 (such as for example a keyboard and a mouse), for interaction with a user or an operator.
Although FIG. 1 schematically illustrates a number of essential components of an exemplary microprocessor device for implementing the embodiments of the present invention, it will be appreciated that the drawing does not illustrate all peripherals, all interfaces and all components of the computer 112, which are well known in the art but do not relate to the present description. Those skilled in the art, however, will recognize the other components constituting a conventional computer system.
Fig. 2 is a flowchart 200 which illustrates a method of generating a 3D optical model of a gemstone for evaluation according to the preferred embodiments of the present invention. The method represented by the flow chart 200 may be implemented using the system 100 illustrated in FIG. 1. Each of the steps of a method according to the preferred embodiments of the invention is described in more detail below. Although the flowchart 200 represents a particular sequence of operations, it will be appreciated that the specific order of the steps does not limit the present invention, and it will be apparent from the following description that, in various embodiments, certain distinct steps shown on flow chart 200 may be combined and / or reclassified within the scope of the invention.
Construct a 3D model of the exterior of a gemstone (step 202)
The first step according to an exemplary implementation of the invention consists in making measurements on the gemstone 104 in order to construct a 3D model of an outer surface of the gemstone 104. As indicated above, a Scanning 102 capable of performing this function is known in the prior art. Generally, the gemstone, such as a rough diamond 104, is turned and / or translated on the support 106, successively illuminated with one or more sources (s) of lighting, such as the source of 108, and the corresponding images of the diamond 104 captured using a digital imaging device 110. The images can be processed in the scanning device 102, if the device includes its own processor and associated software, or can be transferred to a separate computer 112 for processing, as in the exemplary embodiment 100 illustrated in Figure 1.
Images of the diamond 104 captured in different rotational orientations relative to the digital imaging device 110 are processed, and, in particular, the processing preferably includes identifying a silhouette of the diamond 104 in accordance with said different rotational orientations. By combining the information from these multiple images, the system 100 is capable of constructing a 3D model of the outer surface of the diamond 104. In addition, as also indicated above, laser devices may be included in the digitizing device. 102, to identify and measure features such as indentations in the outer surface of the diamond 104, which can not be easily seen on the silhouette images captured by the digital imaging device 110.
Inclusion Identification (Step 204) The next step in the exemplary process is to identify inclusions in the diamond 104. Again, by illuminating the diamond and capturing images of it, particularly with appropriate magnification, inclusions in the diamond 104 may be visible on the captured images. The process of identifying the shape and location of the inclusions in the diamond 104 may be done by an operator, or may be partially or fully automated.
For example, images on which inclusions are visible may be displayed on the display device 124. An operator may use the input devices 128 to identify and map the location, shape, and / or size visible inclusions. The computer 112 can then guide the digitizer 102 to perform additional operations of identifying the location and shape of the inclusions indicated by the operator, as described in more detail below with reference. at step 206.
In addition, the operator may be able to use the captured and displayed images, in combination with direct observation of the diamond 104, to identify the shape and location of the inclusions. For example, the operator can remove the diamond 104, with the support 106, from the digitizer 102, to perform a direct visual inspection of each inclusion, such as using a magnifying glass, or other magnifying device, while also being able to observe the corresponding captured images on the display device 124 of the computer 112.
Alternatively, the computer 112 may be programmed to process the captured images by the scanner 102 to identify the likely locations of the inclusions in an automated manner. The image processing may be used to fully automate the process, or to present the operator with specific images on the display 124 for the purpose of checking and / or optimizing the identification of the images. inclusions detected via image processing. Again, the operator can complete this process by a direct visual inspection of the diamond 104, removing it with the support 106 of the device 102 to observe it with a magnifying glass or other magnifying device.
Inclusion modeling (steps 206 to 216)
According to the exemplary process illustrated by flowchart 200, each identified inclusion is then subjected to further processing and further modeling. The objective of the series of steps 206 to 214, which are applied to each inclusion, in turn, is to construct a 3D virtual optical model of each inclusion. Although the flowchart 200 indicates that all inclusions are first identified in step 204, and that each inclusion is subjected to further processing via the iterative sequence of steps 206-216, it will be readily appreciated that the steps 206 to 214 may be executed in relation to each inclusion, as identified. Thus, step 204 may also be included in the loop defined on flowchart 200 by steps 206-216. It will be understood that all such apparent variations are within the scope of the present invention.
Determining the Location and Shape of an Inclusion (Step 206)
As indicated above, for each inclusion identified in step 204, it is necessary to establish the location of the inclusion in diamond 104, as well as its three-dimensional shape.
The precise identification of the location of features inside a diamond is usually quite difficult. This is due to the particular optical properties of the diamond, and more particularly to its relatively high refractive index (about 2.42). The large index difference between the diamond and the surrounding air results in a relatively high reflectivity for incident light at an angle on the inner surfaces, and relatively large degrees of refraction of the light passing between the outside and the inside. diamond, and vice versa. Because of reflections and refraction, inclusions seen from outside a diamond, such as 104, are usually not located in the interior volume of the diamond at the location where they appear on externally captured images. .
Various methods have been developed to more precisely locate inclusions observed in a gemstone, and preferred methods for use with the present invention are described in the aforementioned document EP 1211503. An alternative, but less preferred, approach described in WO 2007/023444, in the name of Galatea Ltd. and published on March 1, 2007, involves immersing a diamond in a high refractive index liquid to minimize reflections and refraction that complicate the location of inclusions in the diamond. This latter process suffers from a number of disadvantages, such as the difficulty of handling, and the conventional toxicity of liquids with adequate refractive index. In addition, immersing the diamond in a high refractive index liquid inevitably prevents the accurate identification of the outer surfaces. Therefore, the use of this technique in the embodiments of the present invention requires that part of the process be performed without immersion, and that a subsequent portion be performed with immersion, thereby creating additional complications of the implementation. implemented.
After identifying and locating each inclusion within the diamond 104, the three-dimensional shape of the inclusion is also determined. Again, this is a process that can be fully or partially automated, or that can rely on more intensive operator intervention. For example, by presenting an operator with one or more images of the identified inclusion (such as, for example, at different viewing angles) on the display 124, the operator can use the input devices 128 to materialize. an outer surface of the inclusion, thus defining its shape. Alternatively, or in addition, the computer 112 may be programmed to process the captured images of the inclusion to automatically determine its three-dimensional shape. Intermediate implementations are also possible, for example when image processing is used to determine the 3D shape of each inclusion, and the operator is then presented with the results, such as in the form of a filiform structure superimposed on one or more image (s) of the inclusion on the display device 124. The operator can then confirm the accuracy of the information of the automatically generated three-dimensional shape, or can make modifications and settings if necessary. Confirmation of the accuracy of the three-dimensional shape information may include a direct visual inspection of the diamond 104 by the operator, removing the diamond 104 from the digitizer 102, and the carrier 106, for direct observation. with a magnifying glass or other magnifying device.
Determining the Optical Characteristics of an Inclusion (Steps 210 and 212) The next step in processing each inclusion is to determine relevant optical characteristics of each inclusion. According to the exemplary embodiment of the invention, this step comprises two sub-steps. First, the type of inclusion is identified and assigned. Then, other features of inclusion are attributed, depending on the type and visual appearance of the inclusion. These substeps are described in more detail below.
Assigning an inclusion type (step 210)
There are different types of inclusions in gemstones such as diamonds, and each type can have different optical properties. For example, common inclusions in diamonds include dots, clouds, cracks, and needles. A "point" is an inclusion that appears as a small bright or dark point during magnification, usually caused by the development of a small crystal in the gemstone. A "cloud" is usually a set of points. A "needle" is a long, thin inclusion, which is usually a crystalline growth in the gemstone. A "crack", also known as "deformation" or "cleavage", is usually a small fracture in the gemstone. Cracks generally contain voids or small intervals in the gemstone, and may therefore have complex optical properties, resulting from several reflections and / or refractions of light.
Advantageously, by assigning a type corresponding to each identified inclusion, the most appropriate optical modeling techniques can be chosen to represent the inclusion in the final virtual diamond model 104.
As with the previous steps, assigning an inclusion type to each inclusion may be based on operator input, or may be fully or partially automated. For example, the operator can obtain a captured image of the inclusion on the display 124, with an appropriate user interface input element, such as a drop-down list, in which the appropriate type of inclusion can be chosen on the basis of observation of the image captured by the operator. Alternatively, the computer 112 may be programmed to identify at least some types of inclusions, based on detectable optical properties from the processing of the captured images. The operator may have the opportunity to check and / or modify an inclusion type automatically assigned by the computer 112.
Assignment of optical characteristics (step 212)
As indicated above, different types of inclusions may have different optical properties. For example, cracks generally contain a small gap or gap, and thus have characteristic reflection and refraction properties. The dots usually diffuse the light, and appear darker against a light background (such as a light reflecting facet), and / or light against a dark background (such as an unlit facet). A cloud is a set of points of different densities, and therefore has a degree of translucency, and a diffusion and / or reflection of light.
Appropriate optical characteristics can be attributed to each inclusion, depending on the type of inclusion. The information needed to assign adequate optical characteristics may vary considerably, depending on the type of inclusion. In some cases, no additional optical feature information is needed. In other cases, a large amount of additional information may be needed to properly characterize an inclusion. The information, and the relevant optical characteristics, may be captured and / or generated automatically, or may be provided by, or with the aid of an operator input.
For example, an extremely small point may not require additional information to capture. If information is needed, a single captured image may be sufficient to fully characterize the inclusion, and to locate the inclusion if the external surface through which it is viewed is flat (such as a facet of a trimmed dimmer, or a "Window" voluntarily faceted with a rough stone). An automated process, in general, uses images that have been captured under known lighting conditions, which can therefore be reproduced in a virtual space on the computer 112. Thus, by generating a model of inclusion in the memory of the computer 118, and by performing appropriate ray tracking algorithms using virtual light sources corresponding to the known light set in the digitizer 102, the appearance of the virtual inclusion can be compared with the appearance of the actual inclusion on the corresponding captured image. If the virtual and real images are identical, or almost identical, then it can be concluded that the correct optical characteristics of the inclusion have been attributed.
As noted above, for one point, only one photo may be sufficient to confirm the optical characteristics, or, alternatively, an accurate model may be generated based on a color operator's description. and apparent size under controlled lighting conditions.
For a complex cloud, it may be necessary to capture images according to a number of different orientations and / or using different light sources and / or different magnifications, since the cloud may have different optical properties when it is observed in different positions, due to variations in shape and density. Again, an operator input, such as translucency or transmittance of apparent light, may be used when assigning optical characteristics. In most cases, however, it is desirable that the optical characteristics be assigned in the form of a texture, or "skins", and / or BRDF. Textures and BRDFs are surface models that take into account surface properties, such as roughness, translucency, reflectivity, etc. Appropriate textures can, in general, be determined using the aforementioned method, i.e., estimating an appropriate texture and then comparing a captured image with a corresponding virtual image generated by ray tracking in the computer 112. The chosen texture can then be modified, if necessary, to improve the match between virtual and real images. For complex inclusions, textures can be generated for different parts of the inclusion, viewed in different orientations, and then combined to create an overall texture for the entire surface of the inclusion.
In a similar way, iterative methods can be used to estimate and assign BRDFs to identified inclusions. A BRDF (Bidirectional Reflectance Distribution Function) mathematically describes the ratio of light reflected from a surface to light incident on the surface, taking into account the directions of incidence and reflection. B RD F formalizes the widely observed fact that the hue and / or brightness of a surface depends (ent) on the lighting direction and the direction in which the surface is observed. The BRDF captures this feature, so that the visual appearance of the surface can then be rendered under different lighting and observation conditions. According to preferred embodiments, images of the inclusion can be captured not only according to different viewing orientations, but also under different lighting conditions. Corresponding virtual images can be generated by ray tracking in the computer 112, and compared with the captured images, and an estimated BRDF can then be modified, if necessary, to improve the match between the virtual and real images. . The known geometry of each inclusion can be used to select the optimal lighting conditions for estimating a BRDF of the surface of a selected inclusion. For example, a crack may be intentionally oriented and illuminated to better present a surface thereof with a high contrast from the background (such as a light surface against a dark background, or vice versa). The choice of the appropriate viewing orientation, and the corresponding lighting conditions, can thus facilitate the estimation of the BRDF. The same technique can also facilitate capturing and assigning textures to inclusion surfaces.
Additional optical properties of particular types of inclusions can also be taken into account when implementing appropriate models. For example, the cracks are generally reflective in certain lighting conditions because they contain a vacuum, or air, which leads to optical phenomena such as losses of Fresnel intensity. For cracking, it may be necessary to use specially adapted light sources and positioning techniques to accurately determine the transparency characteristics. All relevant optical effects can be modeled, with appropriate information regarding inclusion type, dimensions, and optical characteristics.
Constructing a 3D Virtual Model of Inclusions (step 214) As soon as all the pertinent information relating to each inclusion has been established (ie the location, the three-dimensional shape, the type of inclusion, the optical characteristics), these are assembled in step 214 into a complete 3D virtual model of the inclusion.
Iteration (step 216) In step 216, the processor checks whether all the inclusions have been modeled, and, if not, goes to the next inclusion. Once all inclusions have been modeled, the process moves to the next step.
Construction and representation of a 3D optical model (Steps 218 and 220) At this point, the computer 112 has constructed a 3D model of the exterior of the gemstone, and 3D models of all inclusions visible in the interior volume of the gemstone. These are combined in step 218 to construct a complete 3D optical model of diamond 104, with the inclusions.
In step 220, a set of data corresponding to the 3D optical model is generated, and is generally stored in the memory 118, or a non-volatile storage device 116, but, in addition or alternatively, can be transmitted by example, via a data communication network, to other locations for further processing. It is envisaged that the size of the data set will generally be in the range of 100 kilobytes to 300 kilobytes for diamonds with a number of small inclusions. Despite their relatively compact size, these datasets include all the information needed to generate photo-realistic visual images of a gemstone under any desired viewing conditions. Thus, files containing these datasets contain a wealth of information that far exceeds that contained in a single digital image of several megabytes. As will be appreciated, these compact files can be easily exchanged between interested parties, such as e-mail attachments, or in the form of Internet downloads. This can allow, for example, the estimation and / or valuation of diamonds remotely, using the photorealistic images generated, by experts and / or diamond dealers located anywhere in the world, without the need direct access to the original gemstone itself.
Subsequent analysis (steps 222 and 224)
According to the preferred embodiments of the invention, as soon as a complete 3D optical model of the diamond 104 has been constructed, and a corresponding data set has been generated, the model can be used for subsequent analysis.
Typical operations that an operator may wish to perform include generating photo-realistic virtual images (step 222) of the observed diamond 104 at selected angles / orientations, and under selected lighting conditions. As is known in the art, with a sufficiently detailed optical model, such as that produced by the embodiments of the present invention, these photorealistic virtual images can be generated using known ray tracking techniques.
Alternatively or additionally, the model may be used to automate the calculation of a purity index (step 224). This can be done using ray tracking methods to generate a photorealistic virtual image of the diamond 104 under standard GIA or HRD purity estimation lighting conditions, and with a standard magnification of 10 times, and using the photo-realistic virtual image to determine the purity index. The estimate may be performed by an operator expert, or may be automated by implementing appropriate purity estimation rules in software executed by processor 114. Automated estimation and manual estimation may also be combined. . For example, if the automated estimate produces a limit or refutable result, one or more expert (s) operator (s) (gemologists and / or supervisors) may / may study the assigned index.
In addition to facilitating automated purity estimation, the embodiments of the present invention may also allow for improved automated and / or semi-automated estimation of other desirable qualities related to gemstone size quality. like shine, sparkle and sparkle. Although existing software products, such as Octonus' DiamCalc ™, allow the calculation and visualization of these properties, they are inherently limited by the inability of prior art methods to fully model the impact of inclusions. With the embodiments of the present invention, the placement, size, and other factors of the inclusions may be included in ray tracking calculations (visual image rendering) to determine their effects on the quantification of properties such as as light return and contrast (which can be combined to provide a gloss index), brightness (probability of seeing dispersion), flickering, and other visual performance criteria. For example, clouds that may be difficult or impossible to see with the naked eye may nevertheless attenuate the light emanating from a diamond, and the products according to the present invention are capable of taking these effects into account.
In preferred embodiments, in which the diamond 104 is a rough stone, software also enables an operator to proceed with the roughening of the cut diamonds in the rough, and the subsequent analysis may include the generation of virtual virtual images. realistic (step 222) and / or the calculation of purity indices (step 224) in relation to the proposed cut diamonds. Therefore, a more complete analysis and visualization of the proposed cut stones can be made compared to what is possible with existing systems, which do not accurately represent the inclusions, without the need to perform a rough diamond size. .
Illustrative example of operation and interface
Figures 3 and 4 serve to illustrate an exemplary application of the invention, and a corresponding operator interface. Figure 3 is a schematic illustration of a 3D model 300 of a rough diamond, such as that which may be produced by the embodiments of the invention. Figure 4 illustrates an aspect of a user interface display 400, which allows the display of the model 300 by an operator.
The 3D model 300 includes a number of inclusions (302 to 312) that have been identified and modeled, such as using the system / method described above. The inclusions may consist of, for example, dots (302), cracks (304, 306), clouds (308, 310) and / or needles (312). Also shown in the rough diamond model 300 is a filiform image of a proposed cut diamond.
The operator has a visual imaging interface 400, on the display 124 for example, through which it is possible to interact with, and view, the 3D model 300 in different ways. As illustrated, the interface 400 is a window comprising, among other elements omitted in FIG. 4 for the sake of clarity / simplicity, four viewing flaps 402, 404, 406, 408. In the example shown, a Three-dimensional image of the 300 model is displayed in the upper left pane 402. The upper right pane 404 displays another image of the model 300, in a different orientation (that is, rotated relative to the first image 402). In the lower left pane 406 is displayed a filiform image of the proposed cut diamond, seen from the top of the cut stone table, illustrating the different locations at which the inclusions are visible in the interior volume of the diamond. The software uses ray tracking techniques in each case to calculate locations where inclusions are visible, taking into account the effects of reflections and refraction of light. As illustrated, the single point 302 is visible at five distinct apparent locations in the cut stone due to reflection and refraction effects. Crack 304 is visible on the edge at two apparent locations.
Since the software "knows" which of several images of a single inclusion is the image directly observed, and which are the result of one or more reflection (s) by the facets of the diamond, it is possible to provide the operator a feature to distinguish these different views. For example, the first view (that is, the most direct, or single refractive) can be displayed with a different color than the many reflected views. Alternatively, or in addition, the software may allow the operator to "cut" the generation of different reflected images, to evaluate the contribution of the reflections to the appearance of the diamond, and to reduce the index of purity of the stone.
Due to the small size of the dots, and the fact that the crack appears only on the edge (i.e. it has a minimum visible surface) when viewed through the cut diamond table, the operator may suspect that the actual visible impact of these inclusions in the finished cut / polished stone may be minimal. In order to verify this hypothesis, a complete photo-realistic image corresponding to the filiform image in the flap 406 can be generated. In the interface 400, a photo-realistic image is displayed in the lower right pane 408. This image allows the operator to observe the actual expected appearance of the inclusions, such as, for example, under purity estimation conditions. standard. This may allow the operator to assign a purity index to the proposed cut diamond, based on the photo-realistic image. Alternatively, an automated purity estimate may be possible, based on software processing of the photo-realistic image using appropriate purity estimation rules.
In addition, when the 3D model is indicated to the user, the limited depth of field (DOF) can be taken into account. When a gemologist observes an inclusion through a magnifying glass, depth of field limitations affect the view obtained. In order not to obtain a lower view quality than would be achieved with magnification, it is advantageous to include conventional depth of field limitations to the generation of the displayed image. This depth of field (DOF) can be used to move closer to or away from the virtual gemstone. The DOF here refers to how it is possible to focus with a lens and see all the inclusions on a certain plane, above and below which everything is blurred. Beyond this field of view in the direction of the top or bottom of a gemstone, inclusions are not visible until the lens has been moved closer or further away.
With a normal digital rendering (not taking into account the DOF limitations), all inclusions and their reflections (and facets) in a gemstone are perfectly sharp. If this is the case, a diamond with a slight inclusion may appear as very poor quality and unsaleable. By adding a digital depth of field, it becomes possible to see the gemstone as a person actually sees it with magnification.
A preferred observation tool of the software for zooming / expanding should take into account the DOF. In particular, when a user zooms in, the depth of field should become smaller (shallower).
Imaging gemstones
Although Fig. 1 illustrates a set 100 for making measurements on a rough diamond 104, as previously indicated, the embodiments of the present invention are equally applicable to the measurement and modeling of gemstones. . In many cases, there may be no especially preferred orientation of a gemstone 104 on a support 106, since the uncut outer surface has no particularly preferred viewing direction. However, this can not be the case with a gemstone cut like an ideal cut diamond.
Fig. 5 is a diagram illustrating a preferred image capturing assembly 500 of an ideal cut diamond 504, positioned on a support 506, using an imaging device 510. The diamond 504 is arranged on the support 506 so that the table 502 (i.e., the "upper" flat surface of the cut diamond) can be oriented to directly face the imaging device 510. This set is desirable because the relatively large flat table makes the capture effective perpendicular image, and because it is also the main observation orientation used to observe and estimate the purity of the diamond 504.
It will be appreciated that other support devices and / or sets for cut / polished precious stones are also within the scope of the present invention. The preferred support device minimizes visual obstructions of a gemstone in all viewing directions, and ensures that optimal viewing orientations are available for the image capture device (such as the set 500 which allows the table 502 of an ideal cut diamond 504 to be oriented towards the imaging device 510). It is further preferred that as many degrees of freedom as possible be provided for the rotation and / or translation of a gemstone with respect to the image capturing devices and / or lighting assemblies. However, as the exemplary embodiments described herein demonstrate, even a single axis of rotation, in combination with one, two or three perpendicular axes of translation, may be sufficient to implement the invention. Moreover, although the exemplary embodiments described and illustrated herein assume, for simplicity, that the imaging device (such as, for example, cameras 110, 510) and lighting devices (such as ) remain stationary, although the gemstone (such as for example 104, 504) is rotated and / or translated, only the orientation of the gemstone with respect to the lighting and capture devices determines the operation of the embodiments of the invention. Therefore, embodiments are contemplated wherein the imaging and / or illumination devices may be movable relative to the gemstone, or wherein a plurality of imaging and / or lighting devices may be provided. in order to obtain adequate images in different observation positions
It will be understood that the embodiments of the invention described above are intended to be exemplary only, and should not be construed as limiting the scope of the invention, as defined in the following claims.

权利要求:
Claims (27)
[1]
A method of constructing a virtual gemstone model comprising the steps of: performing gemstone measurements to construct a three dimensional (3D) model of an exterior surface of the gemstone; identify one or more inclusion (s) visible in an interior volume of the gemstone; for each identified inclusion, perform the following steps: Determine a location and 3D shape of inclusion in the interior volume of the gemstone; capture at least one image of the inclusion; use the image at least to determine relevant optical characteristics of the inclusion; and constructing a 3D virtual model of the inclusion, said model comprising the 3D shape of the inclusion and the optical properties of the inclusion based on said optical characteristics; construct a 3D virtual model of the gemstone that includes the virtual 3D model of the outer surface of the gemstone and the virtual 3D models of the inclusion (s) visible in the interior volume of the stone precious ; and generating a data set representing said 3D virtual model, wherein said data set can be used in a subsequent computer analysis to provide a user with information relating to a visual characteristic of the gemstone.
[2]
The method of claim 1, wherein the step of using at least one image to determine relevant optical features of the inclusion comprises the substeps of: using the at least one image to assign a type of inclusion to inclusion; and based on the inclusion type assigned, assigning zero or more other characteristics at inclusion, said other characteristics being chosen according to the inclusion type and inclusion properties observable on the at least one image.
[3]
A method according to claim 1 or claim 2, wherein the gemstone is a rough stone, and the visual characteristic is a visual characteristic of a gemstone cut and / or polished proposed to be cut from the stone brute.
[4]
The method of any one of claims 1 to 3 including the further step of generating and displaying a predicted visual appearance of the gemstone observed in a specified viewing position under specified lighting conditions.
[5]
The method of any one of claims 1 to 4 including the further step of calculating and producing a purity index of a cut and polished gemstone.
[6]
A method according to any one of the preceding claims comprising the further step of calculating and producing an index value related to a visual performance criterion of a gemstone cut and polished, said visual performance criterion being selected in a list including: light return; the contrast ; the brilliant; shine; and flicker.
[7]
The method of claim 2, wherein the inclusion type assigned to each inclusion is selected from a list comprising: a dot; a cloud ; a needle; and a crack.
[8]
The method of any one of the preceding claims, wherein the optical characteristics of each inclusion are represented using one or more texture (s).
[9]
The method of any of the preceding claims, wherein the optical characteristics of each inclusion are represented using one or more bidirectional reflectance distribution function (BRDF).
[10]
The method of any of the preceding claims, wherein said at least one image of an inclusion comprises a plurality of inclusion images captured from different relative viewpoints, and wherein the method comprises the steps of using said plurality of images to determine relevant optical characteristics of the observed inclusion from different relative viewpoints; and combine optical characteristics when constructing a 3D virtual model of inclusion.
[11]
The method of any of the preceding claims, wherein the step of capturing at least one image of each inclusion is performed under predetermined lighting conditions, and wherein the step of determining the relevant optical characteristics. each inclusion uses a ray tracking process comprising the steps of: reproducing the predetermined lighting conditions in a computer-generated virtual environment comprising an inclusion model having estimated optical characteristics; generating at least one virtual image of the inclusion corresponding to the at least one image of the real inclusion; compare the virtual image with the real image; and if the virtual image substantially does not correspond to the actual image, modify the estimated optical characteristics of the inclusion model and repeat the generation and comparison steps.
[12]
The method according to any one of the preceding claims, wherein the at least one image is captured under lighting conditions adapted to the optical characteristics to be determined.
[13]
The method of any of the preceding claims, further comprising generating a visual characteristic of the gemstone taking into account the viewing optics.
[14]
Apparatus for constructing a virtual gemstone model, comprising: a means for making gemstone measurements to construct a three dimensional (3D) model of an outer surface of the gemstone; identification of one or more inclusion (s) visible in an interior volume of the gemstone; means for constructing a 3D virtual model of each identified inclusion; a means of constructing a 3D virtual model of the gemstone including the virtual 3D model of the outer surface of the gemstone and the virtual 3D model of the inclusion (s) visible in the volume interior of the gemstone; and means for generating a data set representing said 3D virtual model, wherein said data set can be used in subsequent computer analysis to provide the user with information relating to a visual characteristic of the gemstone, and wherein the means for constructing a 3D virtual model of each inclusion comprises: means for capturing at least one image of the inclusion; means for using the image at least to determine relevant optical characteristics of the inclusion; and means for constructing a 3D virtual model of the inclusion, said model comprising the 3D shape of the inclusion and the optical properties of the inclusion based on said optical characteristics.
[15]
The device of claim 14, wherein the means for using the at least one image to determine relevant optical characteristics of the inclusion comprises: means for using the at least one image to assign a type of inclusion at inclusion; and an assigned inclusion type responsive means that assigns zero or more other features at inclusion, said other characteristics being selected according to the inclusion type and inclusion properties observable on the at least one image.
[16]
Apparatus according to claim 14 or claim 15 comprising means for generating and displaying a predicted visual appearance of the gemstone observed in a specified viewing position under specified lighting conditions.
[17]
17. Device according to any one of claims 14 to 16, comprising means for calculating and transmitting a purity index of a gemstone cut and polished.
[18]
18. A virtual gemstone model construction system, comprising: a gemstone scanning device configured to perform gemstone measurements to construct a three dimensional (3D) model of an outer surface precious stone; a computer having at least one central processor, a display device, and one or more user input device (s), the computer being operatively connected to the scanning device and configured to receive information from the computer digitizing device defining an outer surface of the gemstone; The computer further comprising at least one storage medium operably associated with the processor and containing executable instructions by the processor for performing the steps of: identifying one or more inclusion (s) visible in a volume interior of the gemstone; for each identified inclusion, build a 3D virtual model of inclusion; construct a 3D virtual model of the gemstone including the virtual 3D model of the outer surface of the gemstone and the 3D virtual model of the inclusion (s) visible in the interior volume of the gemstone ; and generating and storing in the storage medium a data set representing said 3D virtual model, wherein said data set can be used in a subsequent computer analysis to provide a user with information relating to a visual characteristic of the gemstone, and wherein the instructions executable by the processor for performing the step of constructing a 3D virtual model of each include instructions executable by the processor to perform the substeps of: capture at least one image of the inclusion; using the at least one image to determine relevant optical characteristics of the inclusion; and constructing a 3D virtual model of the inclusion, said model comprising the 3D shape of the inclusion and the optical properties of the inclusion based on said optical characteristics.
[19]
The system of claim 18, wherein the instructions executable by the processor for performing the substep of using the at least one image to determine relevant optical features of the include include instructions for performing the other substeps of: using the at least one image to assign an inclusion type to inclusion; and based on the inclusion type assigned, assigning zero or more other characteristics at inclusion, said other characteristics being chosen according to the inclusion type and inclusion properties observable on the at least one image.
[20]
The system of claim 18 or claim 19, wherein the storage medium further contains instructions executable by the processor for displaying captured images to the user on the display device, and generating and display virtual images of the gemstone on the display.
[21]
The system of any one of claims 18 to 20, wherein the storage medium further contains executable instructions by the processor for receiving and processing user input via the user input device (s). , said entry concerning one or more of: the identification of visible inclusions; the location of visible inclusions; the 3D shape of visible inclusions; and the optical characteristics of visible inclusions.
[22]
The system of any one of claims 18 to 21, wherein the storage medium further contains executable instructions by the processor for generating and displaying photo-realistic virtual images of the gemstone and / or other stones cut in the gemstone, using the virtual 3D model of the gemstone.
[23]
The system of claim 22, wherein said photorealistic images comprise images representing a predicted visual appearance of the gemstone observed at a specified viewing position under specified lighting conditions using ray tracking techniques. computerized.
[24]
The system of claim 22 or claim 23, wherein the generated visual images are visual images of a rough gemstone, or images of the predicted visual appearance of a gemstone and / or polished gemstone proposed for to be carved from a raw gemstone.
[25]
The system of any one of claims 18 to 24, wherein the storage medium further contains executable instructions by the processor to automatically evaluate a purity index of a proposed cut and polished gemstone.
[26]
The system of claim 25, wherein the instructions executable by the processor to automatically evaluate a purity index include instructions implementing ray tracking methods to generate a visual image of the gemstone under conditions lighting standards for estimating purity and calculating the purity index by image analysis and applying purity index estimation rules.
[27]
A storage medium storing a program for controlling the process steps according to any one of claims 1 to 13.

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同族专利:

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公开号 | 公开日

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AT504053T|2011-04-15|

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US8639479B2|2014-01-28|

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WO2009068354A1|2009-06-04|

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DE602008005933D1|2011-05-12|

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US20140107986A1|2014-04-17|

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法律状态:

优先权:

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申请号 | 申请日 | 专利标题

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AU2007906469|2007-11-27|

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AU2007906469A|AU2007906469A0|2007-11-27|Method and System for Improved Optical Modeling of Gemstones|

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