• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The present invention relates to a computer implemented method for determining the actual size of a target object within a digital image/video frame. The mothod comprises the steps of: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iva) determining boundaries of the target object from pixel data in the digital image/video frame; v) determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; wherein the determination is made from a pre-calibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object; and vi) calculating the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    公开号:DK201600335A1
    申请号:DKP201600335
    申请日:2016-06-08
    公开日:2017-12-18
    发明作者:Kenneth Gjerulff Obbekjær Kring
    申请人:Blue Sky Tec Aps；
    IPC主号:
    专利说明:

    Background of the invention
    Building products or elements include products used in constructing/remodeling buildings, including non-residential commercial buildings, governmental buildings, and residential or home (single family and multi-family) buildings.
    An improvement project may include a replacement of existing building products (e.g., windows, doors, siding, roof, and gutters), an addition to an existing structure, a new structure, a renovation, etc.
    Selection of materials and options offered in manufactured building products is critical in the delivery of an aesthetically pleasing and satisfying improvement or project and often determines or affects the cost of the products and the project. The building products industry represents a long standing industry directed to manufacturing, delivering, and installing architectural products or elements, e.g., windows, fenestration appurtenances, doors, hardware, etc.
    Building product or element manufacturers face many challenges in providing their dealers/contractors with effective sales tools and support. A further problem faced by dealers and contractors is providing the home/business owner with a representative visual representation (“visualization”) of the final configured product or completed improvement project. A system is needed that allows for easy retrieval of target dimensions (such as a window frame for a window opening in a wall), for visualization of presented product offerings for a specific target, and for firm quotes generated during the sales process.
    Summary of the invention A first aspect relates to a computer implemented method for determining the actual size of a target object within a digital image/video frame comprising the steps ot: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame. A second aspect relates to a computer implemented method for determining the actual size of a target object within a digital image/video frame comprising the steps of: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv.a) determining boundaries of the target object from pixel data in the digital image/video frame; v) determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; wherein the determination is made from a precalibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    In one or more embodiments, step vi) is calculated/determined from a precalibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object. A “target object” of the present invention refers to an object in the digital image/video frame having a constraint dimension that is measured by one or more methods of the present invention. In describing the present invention, “constraint dimension” refers to a measured portion or a multiple of a measured portion of a target object to which a designed part is to conform and a “constraint pixel dimension” refers to the length of a constraint dimension measured in pixels. A target object may contain a “symmetry element” which in the present invention refers to an aspect of the target object that in standard practice resides at a position within the target object such that the symmetry element divides a constraint dimension in an integer number of equal parts.
    As will be appreciated by one skilled in the art, one or more aspects or embodiments of the present invention may be embodied as a system, method, computer program product or any combination thereof. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, the present invention may take the form of a computer program product embodied in any tangible medium of expression having computer usable program code embodied in the medium.
    The invention or portions thereof may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
    Any combination of one or more computer usable or computer readable medium(s) may be utilized. The computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CDROM), optical storage device or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of this document, a computer-usable or computer-readable medium may be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device.
    Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, Swift, C++, C# or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
    In one or more embodiments, image-processing algorithms are used to identify a target object within the digital image/video frame. Image processing algorithms are used to decipher certain attributes of the captured image frame. The processor uses image processing algorithms to identify one or more discernable objects in the image frame and attempts to identify them. For example, the image processing may use edge detection techniques to identify one or more objects in the captured image. For each detected object, identification algorithms are used to determine the likely identity of the object. Any number of techniques might be used for such a task. For example, the object might be normalized and compared to a database of possible objects using geometric and/or size analysis. If an object is viewed askew or at an angle, a normalization routine might rotate it and compensate for skew to result in a rectangular object. The features of the image object can then be compared to the database of known rectangular objects having similar dimensional relationships, (e.g. ratio of length to width, such as other currency) and the denomination can be determined. Other techniques, such as morphological filters, look-up table, trained artificial neural network, some threshold, or an object repository of learned objects may be used as well.
    The content of the image frame may in some embodiments be deciphered by processing the frame for edge pattern detection. The processed edge pattern is classified by artificial neural networks that have been trained on a list of known objects, in a look up table, or by a threshold. Once the pattern is classified, a descriptive sentence is constructed consisting of the object and its certain attributes.
    In other embodiments, a graphical user interface for interactively selecting a target object is used to identify a target object within the digital image/video frame.
    The computer comprises a processor and a memory coupled to the processor. The memory is coupled to the processor, and the memory comprises program instructions implementing a graphical user interface for interactively selecting a target object. Program instructions are executable by the processor for: - displaying the digital image/video frame; and - processing a user input routine that processes selection of a control accepting manual selection by a user of a target object. Preferably, the manual selection of the target object is made directly on the digital image/video frame at one or more particular points on said digital image/video frame.
    The computer/computing device may comprise a central processing unit (CPU), a host/PCI/cache bridge, and a main memory.
    The CPU may comprise one or more general purpose CPU cores and optionally one or more special purpose cores (e.g., DSP core, floating point, etc.). The one or more general purpose cores execute general purpose opcodes, while the special purpose cores executes functions specific to their purpose. The CPU is coupled through the CPU local bus to a host/PCI/cache bridge or chipset. A second level (i.e. L2) cache memory may be coupled to a cache controller in the chipset. For some processors, the external cache may comprise an L1 or first level cache. The bridge or chipset couples to main memory via a memory bus. The main memory comprises dynamic random access memory (DRAM) or extended data out (EDO) memory, or other types of memory such as ROM, static RAM, flash, and non-volatile static random access memory (NVSRAM), bubble memory, etc.
    The computing device may also comprise various system components coupled to the CPU via system bus (e.g., PCI). The host/PCI/cache bridge or chipset interfaces to the system bus, such as peripheral component interconnect (PCI) bus. The system bus may comprise any of several types of well-known bus structures using any of a variety of bus architectures. Example architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Associate (VESA) local bus and Peripheral Component Interconnect (PCI) also known as Mezzanine bus.
    Various components connected to the system bus include, but are not limited to, a non-volatile memory (e.g., disk based data storage), a video/graphics adapter connected to a display, a user input interface (l/F) controller connected to one or more input devices such as a mouse, tablet, microphone, keyboard and modem, network interface controller, and/or a peripheral interface controller connected to one or more external peripherals, such as printer and speakers. The network interface controller is coupled to one or more devices, such as data storage, remote computer running one or more remote applications, via a network, which may comprise the Internet cloud, a local area network (LAN), wide area network (WAN), storage area network (SAN), etc. A small computer systems interface (SCSI) adapter may also be coupled to the system bus. The SCSI adapter can couple to various SCSI devices such as a CD-ROM drive, tape drive, etc.
    The non-volatile memory may include various removable/non-removable, volatile/nonvolatile computer storage media, such as hard disk drives that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive that reads from or writes to a removable, nonvolatile magnetic disk, an optical disk drive that reads from or writes to a removable, nonvolatile optical disk such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. A user may enter commands and information into the computer through input devices connected to the user input interface. Examples of input devices include a keyboard and pointing device, mouse, trackball or touch pad. Other input devices may include a microphone, joystick, game pad, satellite dish, scanner, etc.
    The computer may operate in a networked environment via connections to one or more remote computers, such as a remote computer. The remote computer may comprise a personal computer (PC), server, router, network PC, peer device or other common network node, and typically includes many or all of the elements described supra. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.
    When used in a LAN networking environment, the computer is connected to the LAN via a network interface. When used in a WAN networking environment, the computer includes a modem or other means for establishing communications over the WAN, such as the Internet. The modem, which may be internal or external, is connected to the system bus via a user input interface, or other appropriate mechanism.
    In one embodiment, the software adapted to implement the system and methods of the present invention can also reside in the cloud. Cloud computing provides computation, software, data access and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing encompasses any subscription-based or pay-per-use service and typically involves provisioning of dynamically scalable and often virtualized resources. Cloud computing providers deliver applications via the internet, which can be accessed from a web browser, while the business software and data are stored on servers at a remote location.
    In another embodiment, software adapted to implement the system and methods of the present invention is adapted to reside on a tangible, non-transitory computer readable medium. Computer readable media can be any available media that can be accessed by the computer and capable of storing for later reading by a computer a computer program implementing the method of this invention. Computer readable media includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Communication media typically embodies computer readable instructions, data structures, program modules or other data such as a magnetic disk within a disk drive unit. The software adapted to implement the system and methods of the present invention may also reside, in whole or in part, in the static or dynamic main memories or in firmware within the processor of the computer system (i.e. within microcontroller, microprocessor or microcomputer internal memory).
    It is noted that computer programs implementing the system and methods of this invention will commonly be distributed to users via Internet download or on a distribution medium such as floppydisk, CDROM, DVD, flash memory, portable hard disk drive, etc. From there, they will often be copied to a hard disk or a similar intermediate storage medium. When the programs are to be run, they will be loaded either from their distribution medium or their intermediate storage medium into the execution memory of the computer, configuring the computer to act in accordance with the method of this invention. All these operations are well known to those skilled in the art of computer systems.
    In one or more embodiments, the computer implemented method further comprises the step of iv.b) correlating and/or correcting the object boundaries with a figure shape from a database; and wherein step vi) is based on the correlated and/or corrected figure shape. This is to refine the calculation by removing possible pixel errors or indirectly removing objects covering parts of the target object.
    In one or more embodiments, the computer implemented method further comprises the steps of v.b) adjusting the size of the target object in the digital image/video frame to contain as many pixels as possible within the pixel resolution limits of the original digital image/video frame, while retaining its original horizontal to vertical aspect ratio; and v.c) adjusting the in step v.a) calculated/determined pixel per arbitrary length unit or arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame to the resized target object. This adjustment makes it easier to calculate/determine the actual size of the target object, since the minimum distance (Lmin) thereby will be removed from the equation.
    In one or more embodiments, step v.a) is calculated/determined by using machine learning algorithms. A third aspect relates to an apparatus for determining the actual size of a target object within a digital image/video frame comprising: - a processor; and - a memory coupled to the processor, wherein the memory comprises program instructions, and wherein the program instructions are executable by the processor for: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame. A fourth aspect relates to a computer program product for determining the actual size of a target object within a digital image/video frame, the computer program product comprising a readable memory device having computer readable program code stored thereon, including program code which, when executed, causes one or more processors to perform the steps of: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    It should be noted that embodiments and features described in the context of one of the aspects of the present invention also apply to the other aspects of the invention.
    Brief description of the figures
    Figure 1 shows a digital image containing a target object that has already been identified, and its boundaries determined;
    Figure 2 shows that the minimum distance (Lmin) from which a target object can be photographed depends on its size;
    Figure 3 shows exemplary part of a look-up table; and
    Figure 4 shows the target object in Figure 1, adjusted to contain as many pixels as possible within the pixel resolution limits of the original digital image/video frame.
    Detailed description of the invention
    Figure 1 shows a digital image containing a target object that has already been identified, and its boundaries determined.
    As shown in Figure 2, the minimum distance (Lmin) from which a target object can be photographed depends on its size. At the same time, the number of pixels used to define the objects is the same. This observation is crucial for the present invention, as different sizes of objects will be defined by a different number of pixels per object arbitrary length unit (e.g. per mm) of the actual object. Hence, fewer pixels are available per area object for showing details in a larger object than in a smaller object. The lack or presence of details may be used to determine the number of pixels per object arbitrary length unit (e.g. per mm) of the actual object by using machine learning methods.
    When calculated/determined, the number of pixels per object arbitrary length unit (e.g. per mm) of the actual object is used to calculate/determine the actual size of the target object. The calculation/determination is made from a pre-calibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object. An exemplary part of a look-up table is shown in Figure 3. In a preferred embodiment, the size of the target object is adjusted to contain as many pixels as possible within the pixel resolution limits of the original digital image/video frame (Figure 4), while retaining its original horizontal to vertical aspect ratio. The calculated/determined number of pixels per object arbitrary length unit (e.g. per mm) of the actual object will be corrected accordingly. This adjustment makes it easier to calculate/determine the actual size of the target object, since the minimum distance (Lmin) thereby will be removed from the equation.
    权利要求:
    Claims (10)
    [1] 1. A computer implemented method for determining the actual size of a target object within a digital image/video frame comprising the steps of: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    [2] 2. A computer implemented method according to claim 1, wherein step vi) is calculated/determined from a pre-calibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object.
    [3] 3. A computer implemented method according to any one of the claims 1 -2, wherein step v.a) is calculated/determined by using machine learning algorithms.
    [4] 4. A computer implemented method according to any one of the claims 1 -3, wherein image-processing algorithms are used to identify a target object within the digital image/video frame.
    [5] 5. A computer implemented method according to any one of the claims 1-4, further comprising the step further comprises the step of of iv.b) correlating and/or correcting the object boundaries with a figure shape from a database; and wherein step vi) is based on the correlated and/or corrected figure shape.
    [6] 6. A computer implemented method according to any one of the claims 1 -5, further comprising the steps of v.b) adjusting the size of the target object in the digital image/video frame to contain as many pixels as possible within the pixel resolution limits of the original digital image/video frame, while retaining its original horizontal to vertical aspect ratio; and v.c) adjusting the in step v.a) calculated/determined pixel per arbitrary length unit or arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame to the resized target object.
    [7] 7. An apparatus for determining the actual size of a target object within a digital image/video frame comprising: - a processor; and - a memory coupled to the processor, wherein the memory comprises program instructions, and wherein the program instructions are executable by the processor for: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    [8] 8. An apparatus according to claim 7, wherein step vi) is calculated/determined from a pre-calibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object.
    [9] 9. A computer program product for determining the actual size of a target object within a digital image/video frame, the computer program product comprising a readable memory device having computer readable program code stored thereon, including program code which, when executed, causes one or more processors to perform the steps of: i) obtaining a digital image/video frame containing a target object; ii) obtaining data about the digital image/video frame containing a target object, the data comprising information about pixel resolution, and horizontal to vertical aspect ratio; iii) identifying a target object within the digital image/video frame; iv. a) determining boundaries of the target object from pixel data in the digital image/video frame; v. a) calculating/determining the pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame; and vi) calculating/determining the actual size of a target object from the number of pixel per arbitrary length unit or the arbitrary length unit per pixel of the actual target object in the horizontal and/or vertical direction of the digital image/video frame.
    [10] 10. A computer program product according to claim 9, wherein step vi) is calculated/determined from a pre-calibrated curve or look-up table based on a digital image/video frame recorded of a reference object with a known size, and wherein the same pixel resolution and horizontal to vertical aspect ratio is used as the digital image/video frame comprising the target object.
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    法律状态:
    2020-01-14| PBP| Patent lapsed|Effective date: 20190608 |
    优先权:
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    DKPA201600335A|DK179255B1|2016-06-08|2016-06-08|A computer implemented method for determining the actual size of a target object within a digital image/video frame|DKPA201600335A| DK179255B1|2016-06-08|2016-06-08|A computer implemented method for determining the actual size of a target object within a digital image/video frame|
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