Full-automatic camera internal reference calibration method and device, electronic equipment and medium

Abstract

The invention relates to the technical field of cameras, and provides a full-automatic camera internal reference calibration method and device, electronic equipment and a medium. The method includes: positioning angular point positions of a calibration plate; and traversing each angular point, finding an adjacent angular point of each angular point, and sequentially expanding to form a complete calibration structure unit so as to complete calibration. The method only needs to shoot the calibration board picture once, does not need to specify the line number and the column number of the checkerboard in advance, saves time and labor, and is convenient and simple; external interference is avoided, that is, the anti-interference capability is strong; and a calibration structure unit can be formed through automatic expansion and is scientific and intelligent.

Description

Technical Field

[0001] The present disclosure relates to the field of camera technology, and in particular to a method, device, electronic device and medium for fully automatic camera intrinsic parameter calibration. Background Art

[0002] In a monocular vision system, one of the most important parameters is the camera's intrinsic coordinates, which reflects the mapping relationship between environmental information and image information. An accurate intrinsic coefficient is the primary guarantee for observing and measuring the scene through a monocular camera. The camera's intrinsic system is related to the camera's photosensitive film position, lens position, etc. Although the specified standard components can be produced and the camera can be assembled according to the specified size when making the camera, the camera's intrinsic parameters can be calculated through these standards. Unfortunately, due to the limited process level, there is an error between the component size and the standard value, and the assembly position will also deviate from the expected value, making the true intrinsic coefficient have a certain deviation from the theoretical value. Therefore, accurate camera intrinsic calibration methods have become a key research topic in this industry.

[0003] The process of camera intrinsic calibration in the prior art is relatively cumbersome. For example, the number of rows and columns of the chessboard needs to be specified in advance as input, and multiple calibration plate images at different directions and angles need to be taken multiple times. After obtaining multiple calibration images, calibration and verification are performed. In addition, the robustness is poor, and the chessboard cannot have interference, otherwise the corner point detection will fail, and it is impossible to calibrate multiple cameras at the same time. Summary of the invention

[0004] The present invention provides a fully automatic camera intrinsic parameter calibration method, device, electronic device and medium, including: locating the corner point position of the calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the present invention only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0005] In order to achieve the above objectives, the present invention adopts the following technical solutions:

[0006] The first aspect of the present disclosure provides a fully automatic camera intrinsic parameter calibration method, comprising:

[0007] Locate the corner points of the calibration plate.

[0008] Each of the corner points is traversed, and the adjacent corner points of each corner point are found, and are expanded in sequence to form a complete calibration structure unit to complete the calibration.

[0009] Furthermore, the fully automatic camera intrinsic parameter calibration method, after locating the corner points of the calibration plate, further comprises:

[0010] Design the graph based on the corner points and perform gradient calculation:

[0011]

[0012] Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

[0013] Furthermore, in the fully automatic camera intrinsic parameter calibration method, the calibration board comprises:

[0014] The calibration plate is a chessboard, an origin plate or an AprilTag.

[0015] Furthermore, the fully automatic camera intrinsic parameter calibration method locates the corner points of the calibration plate, including:

[0016] The corner point prototype is defined according to the calibration plate graphic.

[0017] Perform convolution operation on the calibration plate:

[0018] ∫ R f(x)h(tx)d(x)

[0019] Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image.

[0020] According to the corner point prototype, the similarity between each pixel point and the corner point is calculated to obtain a similarity probability value of the corner point.

[0021] The neighborhood of the corner point is expanded to find the pixel point with the highest score.

[0022] Calculate the gradient strength:

[0023] G(x,y)=dx(i,j)+dy(i,j)

[0024] dx(i,j)=I(i+1,j)-I(i,j)

[0025] dy(i,j)=I(i,j+1)-I(i,j)

[0026] Wherein, I is the value (RGB value) of the pixel, and (i, j) is the coordinate of the pixel.

[0027] The gradient strength is multiplied by the similarity probability value of the corner point to obtain the corner point score to determine the position of the corner point of the calibration plate.

[0028] Furthermore, the fully automatic camera intrinsic parameter calibration method, before calculating the gradient strength, further includes:

[0029] Filter the pixel points.

[0030] Furthermore, the fully automatic camera intrinsic parameter calibration method, after multiplying the gradient strength with the similarity probability value of the corner point to obtain the corner point score to determine the position of the corner point of the calibration plate, further includes:

[0031] The corner point scores are filtered by a preset threshold.

[0032] Furthermore, the fully automatic camera intrinsic parameter calibration method, after traversing each of the corner points, finding the adjacent corner points of each of the corner points, and expanding them in sequence to form a complete calibration structure unit to complete the calibration, further includes:

[0033] The calibration result is stored.

[0034] A second aspect of the present disclosure provides a fully automatic camera intrinsic parameter calibration device, comprising:

[0035] The positioning unit is used to locate the corner points of the calibration plate.

[0036] The calibration unit is used to traverse each of the corner points, find the adjacent corner points of each corner point, and expand them in sequence to form a complete calibration structure unit to complete the calibration.

[0037] Furthermore, the fully automatic camera intrinsic parameter calibration device further includes:

[0038] A calculation unit is used to design a graph based on the corner points and perform gradient calculation:

[0039]

[0040] Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

[0041] Furthermore, in the fully automatic camera intrinsic parameter calibration device, the positioning unit includes:

[0042] A definition module is used to define the corner point prototype according to the calibration plate graphics.

[0043] The convolution module is used to perform convolution operation on the calibration plate:

[0044] ∫ R f(x)h(tx)d(x)

[0045] Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image.

[0046] The first calculation module is used to calculate the similarity between each pixel point and the corner point according to the corner point prototype, and obtain the similarity probability value of the corner point.

[0047] A search module is used to expand the neighborhood of the corner point and search for the pixel point with the highest score.

[0048] The second calculation module is used to calculate the gradient strength:

[0049] G(x,y)=dx(i,j)+dy(i,j)

[0050] dx(i,j)=I(i+1,j)-I(i,j)

[0051] dy(i,j)=I(i,j+1)-I(i,j)

[0052] Wherein, I is the value (RGB value) of the pixel, and (i, j) is the coordinate of the pixel.

[0053] The obtaining module is used to multiply the gradient strength by the similarity probability value of the corner point to obtain the corner point score to determine the corner point position of the calibration plate.

[0054] Furthermore, the fully automatic camera intrinsic parameter calibration device further includes:

[0055] A filtering module is used to filter the pixel points.

[0056] Furthermore, the fully automatic camera intrinsic parameter calibration device further includes:

[0057] The filtering module is used to filter the corner point scores by using a preset threshold.

[0058] Furthermore, the fully automatic camera intrinsic parameter calibration device further includes:

[0059] A storage unit is used to store the calibration result.

[0060] A third aspect of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0061] A fourth aspect of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0062] The present invention provides a fully automatic camera intrinsic parameter calibration method, device, electronic device and medium, including: locating the corner point position of the calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the present invention only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0063] At the same time, the present invention designs a graphic based on the corner points and performs gradient calculations; defines the corner point prototype according to the calibration plate graphic, and performs a convolution operation on the calibration plate; calculates the similarity between each pixel point and the corner point according to the corner point prototype, and obtains the similarity probability value of the corner point; expands the corner point neighborhood to find the pixel point with the highest score; calculates the gradient strength; multiplies the gradient strength by the similarity probability value of the corner point to obtain the corner point score, so as to determine the position of the corner point of the calibration plate, thereby further improving the accuracy of the intrinsic calibration result.

[0064] In addition, the present invention filters the pixel points and filters the corner point scores through a preset threshold, thereby further ensuring the accuracy of the intrinsic calibration results.

[0065] Finally, the present disclosure stores the calibration results for easy searching. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0067] Figure 1 A schematic diagram of a flow chart of a fully automatic camera intrinsic parameter calibration method in an embodiment of the present disclosure;

[0068] Figure 2 It is a schematic diagram of another process flow of a fully automatic camera intrinsic parameter calibration method in an embodiment of the present disclosure;

[0069] Figure 3 It is a schematic diagram of the structure of a fully automatic camera intrinsic parameter calibration device in an embodiment of the present disclosure;

[0070] Figure 4 It is a schematic diagram of the structure of another fully automatic camera intrinsic parameter calibration device in an embodiment of the present disclosure;

[0071] Figure 5 The present invention is a schematic diagram of the structure of a fully automatic camera intrinsic parameter calibration electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0073] Unless otherwise defined, all technical and scientific terms used in the present disclosure have the same meanings as those commonly understood by technicians in the field of the present disclosure; the terms used in the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the terms "including" and "having" and any variations thereof in the specification and claims of the present disclosure and the above-mentioned drawings, and are intended to cover non-exclusive inclusions.

[0074] In the description of the embodiments of the present disclosure, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present disclosure, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0075] In the description of the embodiments of the present disclosure, the term "and / or" is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0076] In the description of the embodiments of the present disclosure, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0077] In the description of the embodiments of the present disclosure, the orientations or positional relationships indicated by technical terms such as "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", and "circumferential" are based on the orientations or positional relationships shown in the accompanying drawings and are only for the convenience of describing the embodiments of the present disclosure and simplifying the description. They do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the embodiments of the present disclosure.

[0078] In the description of the embodiments of the present disclosure, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present disclosure can be understood according to the specific circumstances.

[0079] Example 1

[0080] The present disclosure provides a method for fully automatic camera intrinsic parameter calibration. Figure 1 As shown, including:

[0081] 101. Locate the corner points of the calibration plate.

[0082] Calibration Target: In machine vision, image measurement, photogrammetry, 3D reconstruction and other applications, it is necessary to establish a geometric model of camera imaging in order to correct lens distortion, determine the conversion relationship between physical size and pixels, and determine the relationship between the 3D geometric position of a point on the surface of a spatial object and its corresponding point in the image.

[0083] Corner point: It is an extreme point, that is, a point with particularly outstanding properties in some aspect. Of course, you can define the properties of the corner point yourself (set a specific entropy value for corner point detection). A corner point can be the intersection of two lines, or a point located on two adjacent objects with different main directions.

[0084] 102. Traverse each corner point, find the adjacent corner points of each corner point, expand them in sequence, and form a complete calibration structure unit to complete the calibration.

[0085] The disclosed embodiment provides a fully automatic camera intrinsic parameter calibration method, comprising: locating the corner point position of a calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed embodiment only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0086] Example 2

[0087] The present disclosure provides a method for fully automatic camera intrinsic parameter calibration. Figure 2 As shown, including:

[0088] 201. Locate the corner points of the calibration plate.

[0089] 2011. Define the corner point prototype according to the calibration plate graphics.

[0090] Among them, the calibration plate is a checkerboard or an origin plate or an AprilTag. This embodiment is briefly described here using the checkerboard as an example, but the protection scope of the present disclosure is not limited to this. In other embodiments, the implementer can determine the type of calibration according to actual conditions.

[0091] The checkerboard defines two types of corner prototypes, one is parallel to the coordinate axis, and the other is a corner point rotated 45 degrees.

[0092] 2012. Perform convolution operation on the calibration plate:

[0093] ∫ R f(x)h(tx)d(x)

[0094] Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image.

[0095] 2013. According to the corner point prototype, calculate the similarity between each pixel and the corner point, and obtain the similarity probability value of the corner point.

[0096] 2014. Expanding the corner neighborhood to find the pixel with the highest score.

[0097] 2015. Filter the pixels.

[0098] 2016. Calculating Gradient Strength:

[0099] G(x,y)=dx(i,j)+dy(i,j)

[0100] dx(i,j)=I(i+1,j)-I(i,j)

[0101] dy(i,j)=I(i,j+1)-I(i,j)

[0102] Where I is the value of the pixel (RGB value), and (i, j) is the coordinate of the pixel.

[0103] 2017. Multiply the gradient strength by the similarity probability value of the corner point to obtain the corner point score to determine the corner point position of the calibration plate.

[0104] 2018. The corner point scores are filtered by preset thresholds.

[0105] 202. Design graphics based on corner points and calculate gradients:

[0106]

[0107] Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

[0108] 203. Traverse each corner point, find the adjacent corner points of each corner point, expand them in sequence, and form a complete calibration structure unit to complete the calibration.

[0109] 204. Store the calibration result.

[0110] The disclosed embodiment provides a fully automatic camera intrinsic parameter calibration method, comprising: locating the corner point position of a calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed method only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0111] At the same time, the disclosed embodiment performs gradient calculation based on the corner point design graphic; defines the corner point prototype according to the calibration plate graphic, and performs convolution operation on the calibration plate; calculates the similarity between each pixel point and the corner point according to the corner point prototype, and obtains the similarity probability value of the corner point; expands the corner point neighborhood to find the pixel point with the highest score; calculates the gradient strength; multiplies the gradient strength by the similarity probability value of the corner point to obtain the corner point score, so as to determine the position of the corner point of the calibration plate, thereby further improving the accuracy of the intrinsic reference calibration result.

[0112] In addition, the embodiment of the present disclosure filters the pixel points and filters the corner point scores through a preset threshold, thereby further ensuring the accuracy of the intrinsic parameter calibration result.

[0113] Finally, the embodiment of the present disclosure stores the calibration results for easy searching.

[0114] Example 3

[0115] The present disclosure provides a fully automatic camera intrinsic parameter calibration device. Figure 3 As shown, including:

[0116] The positioning unit 31 is used to locate the corner points of the calibration plate.

[0117] The calibration unit 32 is used to traverse each of the corner points, find the adjacent corner points of each corner point, and expand them in sequence to form a complete calibration structure unit to complete the calibration.

[0118] It should be noted here that the detailed description of each component of this embodiment can refer to other embodiments and will not be repeated here.

[0119] The disclosed embodiment provides a fully automatic camera intrinsic parameter calibration device, comprising: a positioning unit positioning a corner point of a calibration plate; a calibration unit traversing each corner point, finding adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed embodiment only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0120] Example 4

[0121] The present disclosure provides a fully automatic camera intrinsic parameter calibration device. Figure 4 As shown, including:

[0122] The positioning unit 41 is used to locate the corner points of the calibration plate.

[0123] The definition module 411 is used to define the corner point prototype according to the calibration plate pattern.

[0124] The convolution module 412 is used to perform a convolution operation on the calibration plate:

[0125] ∫ R f(x)h(tx)d(x)

[0126] Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image.

[0127] The first calculation module 413 is used to calculate the similarity between each pixel point and the corner point according to the corner point prototype, and obtain the similarity probability value of the corner point.

[0128] The search module 414 is used to expand the neighborhood of the corner point and search for the pixel point with the highest score.

[0129] The filtering module 415 is used to filter the pixel points.

[0130] The second calculation module 416 is used to calculate the gradient strength:

[0131] G(x,y)=dx(i,j)+dy(i,j)

[0132] dx(i,j)=I(i+1,j)-I(i,j)

[0133] dy(i,j)=I(i,j+1)-I(i,j)

[0134] Wherein, I is the value (RGB value) of the pixel, and (i, j) is the coordinate of the pixel.

[0135] The obtaining module 417 is used to multiply the gradient strength by the similarity probability value of the corner point to obtain the corner point score to determine the position of the corner point of the calibration plate.

[0136] The filtering module 418 is used to filter the corner point scores according to a preset threshold.

[0137] The calculation unit 42 is used to design a graph based on the corner points and perform gradient calculation:

[0138]

[0139] Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

[0140] The calibration unit 43 is used to traverse each of the corner points, find the adjacent corner points of each corner point, and expand them in sequence to form a complete calibration structure unit to complete the calibration.

[0141] The storage unit 44 is used to store the calibration result.

[0142] It should be noted here that the detailed description of each component of this embodiment can refer to other embodiments and will not be repeated here.

[0143] The disclosed embodiment provides a fully automatic camera intrinsic parameter calibration device, comprising: a positioning unit positioning a corner point of a calibration plate; a calibration unit traversing each corner point, finding adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed embodiment only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0144] At the same time, the definition module of the embodiment of the present disclosure performs gradient calculation based on the corner point design graphic; the convolution module defines the corner point prototype according to the calibration plate graphic, and performs convolution operation on the calibration plate; the first calculation module calculates the similarity between each pixel point and the corner point according to the corner point prototype, and obtains the similarity probability value of the corner point; the search module expands the corner point neighborhood and searches for the pixel point with the highest score; the second calculation module calculates the gradient strength; the acquisition module multiplies the gradient strength of the corner point by the similarity probability value of the corner point to obtain the corner point score, so as to determine the position of the corner point of the calibration plate, thereby further improving the accuracy of the internal reference calibration result.

[0145] In addition, the filtering module of the embodiment of the present disclosure filters the pixel points and the filtering module filters the corner point scores through a preset threshold, thereby further ensuring the accuracy of the intrinsic parameter calibration result.

[0146] Finally, the storage unit of the embodiment of the present disclosure stores the calibration results for easy searching.

[0147] Example 5

[0148] The present disclosure provides a fully automatic camera intrinsic parameter calibration electronic device, such as Figure 5 As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned fully automatic camera intrinsic parameter calibration method are implemented.

[0149] A processing device (e.g., a central processing unit, a graphics processing unit, etc.) 51 can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 52 or a program loaded from a storage device 58 into a random access memory (RAM) 53. Various programs and data required for the operation of the electronic device are also stored in the RAM 53. The processing device 51, the ROM 52, and the RAM 53 are connected to each other via a bus 54. An input / output (I / O) interface 55 is also connected to the bus 54.

[0150] Typically, the following devices may be connected to the I / O interface 55: an input device 56 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 57 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 58 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 59. The communication device 59 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Figure 5 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 5 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0151] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 59, or installed from the storage device 58, or installed from the ROM 52. When the computer program is executed by the processing device 51, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0152] The disclosed embodiment provides a fully automatic camera intrinsic parameter calibration electronic device, comprising: locating the corner point position of a calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed embodiment only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0153] At the same time, the disclosed embodiment performs gradient calculation based on the corner point design graphic; defines the corner point prototype according to the calibration plate graphic, and performs convolution operation on the calibration plate; calculates the similarity between each pixel point and the corner point according to the corner point prototype, and obtains the similarity probability value of the corner point; expands the corner point neighborhood to find the pixel point with the highest score; calculates the gradient strength; multiplies the gradient strength by the similarity probability value of the corner point to obtain the corner point score, so as to determine the position of the corner point of the calibration plate, thereby further improving the accuracy of the intrinsic reference calibration result.

[0154] In addition, the embodiment of the present disclosure filters the pixel points and filters the corner point scores through a preset threshold, thereby further ensuring the accuracy of the intrinsic parameter calibration result.

[0155] Finally, the embodiment of the present disclosure stores the calibration results for easy searching.

[0156] Example 6

[0157] An embodiment of the present disclosure provides a computer-readable storage medium for fully automatic camera intrinsic parameter calibration, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by one or more processors, the above-mentioned fully automatic camera intrinsic parameter calibration method is implemented.

[0158] It should be noted that the computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0159] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0160] The computer-readable medium may be included in the device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: locates the corner points of the calibration plate; traverses each corner point, finds the adjacent corner points of each corner point, expands them in sequence, and forms a complete calibration structure unit to complete the calibration.

[0161] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0162] The disclosed embodiment provides a computer-readable storage medium for fully automatic camera intrinsic parameter calibration, including: locating the corner point position of a calibration plate; traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration. Compared with the prior art, the disclosed embodiment only needs to take a calibration plate picture once, and does not need to specify the number of rows and columns of the chessboard in advance, which saves time and effort, is convenient and simple; is not subject to external interference, that is, has strong anti-interference ability; can automatically expand to form a calibration structure unit, and is scientific and intelligent.

[0163] At the same time, the disclosed embodiment performs gradient calculation based on the corner point design graphic; defines the corner point prototype according to the calibration plate graphic, and performs convolution operation on the calibration plate; calculates the similarity between each pixel point and the corner point according to the corner point prototype, and obtains the similarity probability value of the corner point; expands the corner point neighborhood to find the pixel point with the highest score; calculates the gradient strength; multiplies the gradient strength by the similarity probability value of the corner point to obtain the corner point score, so as to determine the position of the corner point of the calibration plate, thereby further improving the accuracy of the intrinsic reference calibration result.

[0164] In addition, the embodiment of the present disclosure filters the pixel points and filters the corner point scores through a preset threshold, thereby further ensuring the accuracy of the intrinsic parameter calibration result.

[0165] Finally, the embodiment of the present disclosure stores the calibration results for easy searching.

[0166] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0167] The units described in some embodiments of the present disclosure may be implemented by software or hardware. The units described may also be set in a processor, for example, it may be described as: a processor includes a receiving unit, an information acquisition unit, a target determination unit, and a distribution unit. The names of these units do not constitute limitations on the units themselves in some cases.

[0168] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0169] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

[0170] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention. In particular, as long as there is no structural conflict, the various technical features mentioned in each embodiment can be combined in any way. The present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A fully automatic camera intrinsic parameter calibration method, characterized in that: include: Position the corner points of the calibration plate; Each of the corner points is traversed, and the adjacent corner points of each corner point are found, and are expanded in sequence to form a complete calibration structure unit to complete the calibration.

2. The fully automatic camera intrinsic parameter calibration method according to claim 1, characterized in that: After locating the corner points of the calibration plate, it also includes: Design the graph based on the corner points and perform gradient calculation: Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

3. The fully automatic camera intrinsic parameter calibration method according to claim 1, characterized in that: The calibration plate comprises: The calibration plate is a chessboard, an origin plate or an AprilTag.

4. The fully automatic camera intrinsic parameter calibration method according to claim 1, characterized in that: Position the corner points of the calibration plate, including: According to the calibration plate graphics, defining the corner point prototype; Perform convolution operation on the calibration plate: ∫ R f(x)h(t-x)d(x) Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image; According to the corner point prototype, calculating the similarity between each pixel point and the corner point, and obtaining a similarity probability value of the corner point; Expand the corner point neighborhood to find the pixel with the highest score; Calculate the gradient strength: G(x,y)=dx(i,j)+dy(i,j) dx(i,j)=I(i+1,j)-I(i,j) dy(i,j)=I(i,j+1)-I(i,j) Wherein, I is the value (RGB value) of the pixel, and (i, j) is the coordinate of the pixel; The gradient strength is multiplied by the similarity probability value of the corner point to obtain the corner point score to determine the position of the corner point of the calibration plate.

5. The fully automatic camera intrinsic parameter calibration method according to claim 4, characterized in that: Before calculating the gradient strength, also include: Filter the pixel points.

6. The fully automatic camera intrinsic parameter calibration method according to claim 4, characterized in that: After the gradient strength is multiplied by the similarity probability value of the corner point to obtain the corner point score to determine the position of the corner point of the calibration plate, the method further includes: The corner point scores are filtered by a preset threshold.

7. The fully automatic camera intrinsic parameter calibration method according to claim 1, characterized in that: After traversing each corner point, finding the adjacent corner points of each corner point, and expanding them in sequence to form a complete calibration structure unit to complete the calibration, the method further includes: The calibration result is stored.

8. A fully automatic camera intrinsic parameter calibration device, characterized in that: include: A positioning unit, used to locate the corner points of the calibration plate; The calibration unit is used to traverse each of the corner points, find the adjacent corner points of each corner point, and expand them in sequence to form a complete calibration structure unit to complete the calibration.

9. The fully automatic camera intrinsic parameter calibration device according to claim 8, characterized in that: Also includes: A calculation unit is used to design a graph based on the corner points and perform gradient calculation: Where c is the ideal corner point position, p is a pixel point in the local neighborhood of c, and gp is the image gradient vector of point p.

10. The fully automatic camera intrinsic parameter calibration device according to claim 8, characterized in that: The positioning unit comprises: A definition module, used to define the corner point prototype according to the calibration plate pattern; The convolution module is used to perform convolution operation on the calibration plate: ∫ R f(x)h(t-x)d(x) Where h is the corresponding filter kernel, f is the entire image, and t is the product of the convolution kernel and the corresponding position of the image; A first calculation module, used for calculating the similarity between each pixel point and the corner point according to the corner point prototype, and obtaining a similarity probability value of the corner point; A search module, used for expanding the neighborhood of the corner point and searching for the pixel point with the highest score; The second calculation module is used to calculate the gradient strength: G(x,y)=dx(i,j)+dy(i,j) dx(i,j)=I(i+1,j)-I(i,j) dy(i,j)=I(i,j+1)-I(i,j) Wherein, I is the value (RGB value) of the pixel, and (i, j) is the coordinate of the pixel; The obtaining module is used to multiply the gradient strength by the similarity probability value of the corner point to obtain the corner point score to determine the corner point position of the calibration plate.

11. The fully automatic camera intrinsic parameter calibration device according to claim 10, characterized in that: Also includes: A filtering module is used to filter the pixel points.

12. The fully automatic camera intrinsic parameter calibration device according to claim 10, characterized in that: Also includes: The filtering module is used to filter the corner point scores by using a preset threshold.

13. The fully automatic camera intrinsic parameter calibration device according to claim 8, characterized in that: Also includes: A storage unit is used to store the calibration result.

14. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

15. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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