WO2022171003A1 - 相机标定方法、装置及电子设备 - Google Patents

相机标定方法、装置及电子设备 Download PDF

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Publication number
WO2022171003A1
WO2022171003A1 PCT/CN2022/074553 CN2022074553W WO2022171003A1 WO 2022171003 A1 WO2022171003 A1 WO 2022171003A1 CN 2022074553 W CN2022074553 W CN 2022074553W WO 2022171003 A1 WO2022171003 A1 WO 2022171003A1
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annular pattern
image
center point
calibration
coordinates
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PCT/CN2022/074553
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English (en)
French (fr)
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吴勇辉
姚金铸
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深圳市汇顶科技股份有限公司
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Publication of WO2022171003A1 publication Critical patent/WO2022171003A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/80Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/11Region-based segmentation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/12Edge-based segmentation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • G06T7/66Analysis of geometric attributes of image moments or centre of gravity
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/70Determining position or orientation of objects or cameras
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/10Image acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/20Image preprocessing
    • G06V10/24Aligning, centring, orientation detection or correction of the image
    • G06V10/245Aligning, centring, orientation detection or correction of the image by locating a pattern; Special marks for positioning
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/20Image preprocessing
    • G06V10/34Smoothing or thinning of the pattern; Morphological operations; Skeletonisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/44Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/56Extraction of image or video features relating to colour
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00Diagnosis, testing or measuring for television systems or their details
    • H04N17/002Diagnosis, testing or measuring for television systems or their details for television cameras
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10004Still image; Photographic image
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20021Dividing image into blocks, subimages or windows
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30244Camera pose

Definitions

  • the present application relates to image processing technology, and in particular, to a camera calibration method, device, and electronic device.
  • Camera parameters include camera internal parameters, such as focal length, imaging center, etc., and camera external parameters, such as rotation matrix and translation matrix.
  • camera calibration The process of determining the internal and external parameters of the camera is called camera calibration.
  • camera calibration is a very critical link.
  • the accuracy of camera calibration results directly affects the accuracy of the results generated by camera work.
  • the image coordinates of the center of the solid circle are further determined by taking a picture of the calibration object with a solid circle pattern, and the internal and external parameters of the camera are determined according to the image coordinates of the center of the circle and the known world coordinates of the center of the circle.
  • the calibration accuracy of this scheme is low.
  • the present application provides a camera calibration method, device and electronic device, which improve the accuracy of camera calibration.
  • the present application provides a camera calibration method, including:
  • the calibration plate image including a plurality of annular patterns
  • each annular pattern determines the image coordinates of the center point of each annular pattern
  • the internal and external parameters of the camera are determined.
  • the acquiring the inner edge and the outer edge of each annular pattern in the calibration plate image includes:
  • the gray value of the pixel point in the calibration plate image determine the inner edge and outer edge of the pixel level of each annular pattern, and determine the inner edge and outer edge of the pixel level of each annular pattern as the The inner and outer edges of each ring pattern.
  • the acquiring the inner edge and the outer edge of each annular pattern in the calibration plate image includes:
  • the inner and outer edges of the pixel level are smoothed to obtain the inner and outer edges of the sub-pixel level, and the inner and outer edges of the sub-pixel level are determined as the inner and outer edges of each annular pattern .
  • the image coordinates of the center point of each annular pattern are determined according to the inner edge and the outer edge of each annular pattern, including:
  • Fitting is performed on the centers of gravity of the plurality of segmented blocks, and the image coordinates of the center point of each annular pattern are determined according to the fitting result.
  • the dividing the area between the inner edge and the outer edge of each annular pattern includes:
  • each annular pattern is segmented according to the normals of the inner and outer edges of each annular pattern.
  • the method further includes:
  • the corresponding relationship between the image coordinates of the center point of each ring pattern and the world coordinates is determined.
  • the internal and external parameters of the camera are determined according to the image coordinates of each center point and the corresponding world coordinates, including:
  • the internal and external parameters of the camera are determined.
  • the present application provides a camera calibration device, comprising:
  • a first acquisition module configured to acquire a calibration plate image, wherein the calibration plate image includes a plurality of annular patterns
  • a second acquisition module configured to acquire the inner edge and the outer edge of each annular pattern in the calibration plate image
  • a determining module for determining the image coordinates of the center point of each annular pattern according to the inner edge and the outer edge of each annular pattern
  • the calibration module is used to determine the internal and external parameters of the camera according to the image coordinates of the center point of each annular pattern and the corresponding world coordinates.
  • the second obtaining module is used for:
  • the gray value of the pixel point in the calibration plate image determine the inner edge and outer edge of the pixel level of each annular pattern, and determine the inner edge and outer edge of the pixel level of each annular pattern as the The inner and outer edges of each ring pattern.
  • the second obtaining module is used for:
  • the inner and outer edges of the pixel level are smoothed to obtain the inner and outer edges of the sub-pixel level, and the inner and outer edges of the sub-pixel level are determined as the inner and outer edges of each annular pattern .
  • the determining module is used for:
  • Fitting is performed on the centers of gravity of the plurality of segmented blocks, and the image coordinates of the center point of each annular pattern are determined according to the fitting result.
  • the determining module is used for:
  • each annular pattern is segmented according to the normals of the inner and outer edges of each annular pattern.
  • the calibration module is also used for:
  • the corresponding relationship between the image coordinates of the center point of each ring pattern and the world coordinates is determined.
  • the calibration module is used for:
  • the internal and external parameters of the camera are determined.
  • the present application provides an electronic device, comprising a memory and a processor, the memory and the processor are connected;
  • the memory is used to store computer programs
  • the processor is configured to implement the method of the first aspect when the computer program is executed.
  • the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the method according to the first aspect.
  • the present application provides a computer program product, including a computer program, which implements the method described in the first aspect when the computer program is executed by a processor.
  • the present application provides a camera calibration method, device and electronic equipment.
  • a calibration plate with an annular pattern is used for camera calibration. Since the annular pattern has two edges, an inner circle and an outer circle, using these two The two edges jointly determine the image coordinates of the center point of the annular pattern.
  • the image coordinates of the center point obtained by using the two edges of the annular pattern in this embodiment are more accurate, so that the It makes the calibration result of the camera more accurate.
  • FIG. 1 is a schematic flowchart 1 of a camera calibration method provided by an embodiment of the present application
  • FIG. 2 is a schematic diagram of a calibration plate provided in an embodiment of the present application.
  • FIG. 3 is a schematic diagram of an image of a calibration plate provided by an embodiment of the present application.
  • FIG. 4 is a second schematic flowchart of a camera calibration method provided by an embodiment of the present application.
  • FIG. 5 is a schematic diagram of annular pattern segmentation provided by an embodiment of the present application.
  • FIG. 6 is a schematic structural diagram of a camera calibration device according to an embodiment of the present application.
  • FIG. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • Camera calibration can be achieved with the help of a three-dimensional or two-dimensional calibration plate.
  • the calibration plate is used to provide points with known coordinate information (world coordinates), also known as target points.
  • the camera is used to shoot the calibration plate, and the obtained image of the calibration plate is processed. , extract the image coordinates of the target point, and determine the internal and external parameters of the camera based on the image coordinates and world coordinates of each target point.
  • the world coordinate is a world coordinate system based on the three-dimensional world defined by the user, and is used to describe the position of the calibration board in the three-dimensional world.
  • Image coordinates are image pixel coordinates that describe the pixel's position in the image. Both world coordinates and image coordinates are expressed in Cartesian coordinates.
  • the calibration plate Due to the complicated manufacture of the three-dimensional calibration plate, a two-dimensional calibration plate is usually used in practical applications, and the calibration plate has a specific pattern, for example, the calibration plate has solid circles arranged at intervals.
  • the world coordinates of the center of the solid circle (that is, the target point) on the calibration plate can be determined, and then the calibration plate is captured by the camera, the obtained image is processed, and the image coordinates of the center of the solid circle in the image are extracted. , so as to determine the internal and external parameters of the camera according to the image coordinates of the center of the circle and the world coordinates.
  • the accuracy of the camera calibration result is mainly determined by the accuracy of the image coordinates of the target point, that is, extracted from the image The more accurate the image coordinates of the target point, the more accurate the calibration result of the camera.
  • the present application provides a camera calibration method, which improves the pattern of the calibration plate, and proposes to use a calibration plate with an annular pattern for camera calibration.
  • the two edges of the circle and the outer circle jointly determine the center point of the annular pattern, and the obtained image coordinates of the center point are more accurate, so that the calibration result of the camera can be more accurate.
  • FIG. 1 is a schematic flowchart 1 of a camera calibration method provided by an embodiment of the present application. As shown in Figure 1, the method includes:
  • the calibration plate image includes a plurality of annular patterns.
  • the calibration plate used in the embodiment of the present application has a ring pattern as shown in FIG. 2
  • the background of the calibration plate may be white
  • the ring portion may be black.
  • the size of each annular pattern on the calibration plate may be the same or different, and the interval between the annular patterns may also be the same or different, which is not limited in this embodiment of the present application.
  • the base material of the calibration plate in this embodiment may be of a reflective type or a back-illuminated type. When the back-illuminated base material is used, the base material of the calibration plate is transparent, and adding a light source on the back of the calibration plate is beneficial to subsequent image processing and can make the calibration result more accurate.
  • the image of the calibration board needs to include at least three viewing angles of the calibration board.
  • two methods can be used. In one way, a single calibration plate can be photographed multiple times, and the calibration plate includes more than 4 annular patterns. Adjust the pose of the calibration board or camera every time you shoot. In this way, a calibration board can fill the entire field of view of the camera as much as possible, and the number of target points in the calibration board can be more, which is conducive to improving the Calibration accuracy.
  • each calibration board includes more than 4 annular patterns.
  • FIG. 3 four calibration boards with different poses are shot once. The resulting calibration plate image. The poses of each calibration board are different, so that a plurality of images of the calibration board with different viewing angles can be obtained by one shot, and the calibration efficiency is high.
  • the edge of each ring pattern can be obtained by performing edge detection on the image of the calibration plate.
  • the edge of the ring pattern includes the inner edge and the outer edge. That is, the inner circle and the outer circle.
  • the inner edge and the outer edge of the annular pattern jointly determine the circle range of the annular pattern, so that the image coordinates of the center point of the annular pattern can be jointly determined according to the inner edge and the outer edge.
  • S104 Determine the internal and external parameters of the camera according to the image coordinates of the center point of each annular pattern and the corresponding world coordinates.
  • the world coordinates of the center point of each ring pattern can be converted into the image coordinates of the center point of each ring pattern through the transformation of the matrix formed by the internal and external parameters of the camera.
  • the world coordinates of the center point of each annular pattern in the calibration board can be determined in advance. Therefore, after extracting the image coordinates of each center point from the calibration board image, the image coordinates and the corresponding world coordinates , the internal and external parameters of the camera can be determined, and the calibration of the camera can be completed.
  • the pattern of the calibration plate is improved, and a calibration plate with an annular pattern is used for camera calibration. Since the annular pattern has two edges, an inner circle and an outer circle, the annular pattern is jointly determined by these two edges. Compared with using a solid circle to determine the image coordinates of the center point, the image coordinates of the center point obtained by using the two edges of the annular pattern in this embodiment are more accurate, so that the calibration result of the camera can be more accurate. to be accurate.
  • Accurate camera parameters can be obtained by calibrating the camera above, which can further make the results produced by the camera work more accurate. For example, for a TOF depth camera, after the camera is calibrated, the depth information of the photographed object determined based on the camera parameters will be more accurate.
  • FIG. 4 is a second schematic flowchart of a camera calibration method provided by an embodiment of the present application. As shown in Figure 4, the method includes:
  • S401 in this embodiment is similar to S101 in the embodiment shown in FIG. 1 , and details are not repeated here.
  • S402. Determine the inner edge and the outer edge of the pixel level of each annular pattern according to the gray value of the pixel point in the calibration plate image.
  • the edge and edge of the ring pattern can be determined according to the change of the gray value.
  • a grayscale change threshold when the grayscale value change of adjacent pixels is greater than the grayscale change threshold, a pixel with a lower grayscale value is determined as a pixel on the edge of the annular pattern.
  • the inner and outer edges of pixel-level are further smoothed.
  • the interpolation method is used to interpolate the gray values of the pixel points of the inner and outer edges of the pixel level to obtain the inner and outer edges of the sub-pixel level.
  • the inner edge and the outer edge of the sub-pixel level can also be obtained by fitting the gray values of the pixel points of the inner edge and the outer edge at the pixel level.
  • the inner and outer edges of the annular pattern are obtained by smoothing the inner and outer edges of the sub-pixel level in order to improve the calibration accuracy.
  • S401-S403 are performed, that is, the inner and outer edges of each annular pattern at the sub-pixel level are determined, and the inner and outer edges of each annular pattern at the sub-pixel level are determined as each The inner and outer edges of the ring pattern.
  • the subsequent S404-S408 are further performed based on the determined inner and outer edges of each annular pattern.
  • each annular pattern After determining the inner and outer edges of each annular pattern, segment the annular region between the inner and outer edges, optionally by determining normals at multiple locations of the inner and/or outer edges, The area between the inner and outer edges of each annular pattern is segmented according to the normals of the inner and/or outer edges of each annular pattern. Taking the normal line of the inner edge as an example, the inner edge is divided into multiple arc segments.
  • the arc AB shown in FIG. 5 is one of the arc segments, and the arcs are determined at points A and B respectively.
  • the normal line (shown by the dotted line in the figure), the two normal lines intersect with the outer edge respectively, so a grid-like area formed between the two normal lines and the inner and outer edges is a segmented block (for For clarity, the annular area in Figure 5 is not filled with color).
  • the size of the divided block can be set as required.
  • the inner edge is divided into multiple arc segments in units of two pixels, and then divided according to the above method.
  • the center of gravity of the segmented block can be determined according to the grayscale value of the segmented block by the gray-scale barycentric method.
  • the three points shown in FIG. 5 are the centers of gravity of the three segments, respectively, and the other segments and their centers of gravity are not shown in the figure.
  • the centers of gravity of the plurality of segmentation blocks After determining the centers of gravity of the plurality of segmentation blocks, fit the centers of gravity of the plurality of segmentation blocks. For example, the average value method, the least squares method, Gaussian fitting and other methods can be used to mesh the centers of gravity of the plurality of segmentation blocks, thereby Determines the image coordinates of the center point of the ring pattern.
  • S406 Determine the relative positional relationship between the image coordinates of the center point of each annular pattern in the calibration plate image.
  • the camera calibration depends on the conversion between the image coordinates of the target point (the center point of the annular pattern in this embodiment) and the world coordinates, after extracting the image coordinates of the center point of each annular pattern, it is necessary to follow the coordinates
  • the magnitudes of the horizontal axis and the vertical axis of the value determine the relative positional relationship between the center points of each annular pattern, so as to determine the corresponding relationship between the image coordinates and the world coordinates.
  • S407 Determine the correspondence between the image coordinates of the center point of each annular pattern and the world coordinates according to the relative positional relationship and the predetermined world coordinates of the center point of each annular pattern in the calibration plate image.
  • the relative positional relationship between the center points of each ring pattern can be determined, and further combined with the pre-determined world coordinates of the center point of each ring pattern in the calibration plate image, Determine the one-to-one correspondence between the image coordinates and the world coordinates of the center point of each annular pattern.
  • S408. Determine the internal and external parameters of the camera according to the correspondence between the image coordinates of the center point of each annular pattern and the world coordinates, and the mapping relationship between the image coordinate system and the world coordinate system.
  • the mapping relationship between the image coordinate system and the world coordinate system is composed of the internal and external parameter matrix of the camera.
  • the internal parameters of the camera are determined by the homography matrices of the plurality of calibration boards, and further, the external parameters of the camera are determined by the homography matrix and the external parameters.
  • the camera calibration method provided in this embodiment uses a calibration plate with an annular pattern to perform camera calibration. Since the annular pattern has two edges, an inner circle and an outer circle, the image coordinates of the center point of the annular pattern are jointly determined by these two edges. Moreover, when performing edge detection, the inner edge and outer edge of the sub-pixel level can be obtained by optimizing the inner edge and outer edge of the pixel level, thereby further improving the edge precision. Determining the image coordinates of the center point of the annular pattern according to the two high-precision annular edges is more accurate than using the solid circle method to determine the image coordinates of the center of the circle, so that the calibration result of the camera can be more accurate.
  • FIG. 6 is a schematic structural diagram of a camera calibration device according to an embodiment of the present application. As shown in FIG. 6 , the camera calibration device 60 includes:
  • the first acquiring module 601 is configured to acquire an image of a calibration plate, and the image of the calibration plate includes a plurality of annular patterns.
  • the second acquiring module 602 is configured to acquire the inner edge and the outer edge of each annular pattern in the calibration plate image.
  • the determining module 603 is configured to determine the image coordinates of the center point of each annular pattern according to the inner edge and the outer edge of each annular pattern.
  • the calibration module 604 is configured to determine the internal and external parameters of the camera according to the image coordinates of the center point of each annular pattern and the corresponding world coordinates.
  • the second obtaining module 602 is used for:
  • the inner and outer edges of the pixel level of each annular pattern are determined, and the inner and outer edges of the pixel level of each annular pattern are determined as the inner and outer edges of each annular pattern. edge and outer edge.
  • the second obtaining module 602 is used for:
  • the inner and outer edges of the pixel level are smoothed to obtain the inner and outer edges of the sub-pixel level, and the inner and outer edges of the sub-pixel level are determined as the inner and outer edges of each annular pattern.
  • the determining module 603 is used for:
  • the determining module 603 is used for:
  • each annular pattern is segmented according to the normals of the inner and outer edges of each annular pattern.
  • the calibration module 604 is further configured to:
  • the corresponding relationship between the image coordinates of the center point of each ring pattern and the world coordinates is determined.
  • the calibration module 604 is used to:
  • the internal and external parameters of the camera are determined.
  • the camera calibration device provided in this embodiment can be used to execute the camera calibration method in the above method embodiments, and the implementation principle and calculation effect thereof are similar, and are not described herein again.
  • FIG. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the electronic device 70 includes a memory 701 and a processor 702 , and the memory 701 and the processor 702 may be connected through a bus 703 .
  • the memory 701 is used to store computer programs.
  • the processor 702 is configured to implement the camera calibration method in the above method embodiments when the computer program is executed.
  • the electronic device may be a computer device, a server, or the like for processing images captured by the camera and calculating internal and external parameters of the camera.
  • the electronic device can also be an electronic device with a camera, and the electronic device can perform parameter calibration on the camera it has.
  • Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, implements the camera calibration method in the above method embodiments.
  • Embodiments of the present application further provide a computer program product, including a computer program, when the computer program is executed by a processor, the camera calibration method in the above method embodiments is implemented.

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Abstract

本申请提供一种相机标定方法、装置及电子设备,该方法包括:获取标定板图像,所述标定板图像中包括多个环形图案;获取所述标定板图像中每个环形图案的内边缘和外边缘;根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标;根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数,提高了相机标定的准确度。

Description

相机标定方法、装置及电子设备
本申请要求于2021年02月09日提交中国专利局、申请号为202110175040.X、申请名称为“相机标定方法、装置及电子设备”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
技术领域
本申请涉及图像处理技术,尤其涉及一种相机标定方法、装置及电子设备。
背景技术
相机成像的几何模型的参数称为相机参数,相机参数包括相机内参,如焦距、成像中心等,以及相机外参,如旋转矩阵和平移矩阵,确定相机内外参数的过程称为相机标定。
在图像测量或者机器视觉等应用中,相机标定都是非常关键的环节,相机标定结果准确与否直接影响相机工作产生的结果的准确性。在进行相机标定时,通过拍摄具有实心圆图案的标定物图片,再进一步确定实心圆的圆心的图像坐标,根据圆心的图像坐标与已知的圆心的世界坐标确定相机的内外参数。这种方案标定准确度较低。
发明内容
本申请提供一种相机标定方法、装置及电子设备,提高了相机标定的准确度。
第一方面,本申请提供一种相机标定方法,包括:
获取标定板图像,所述标定板图像中包括多个环形图案;
获取所述标定板图像中每个环形图案的内边缘和外边缘;
根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标;
根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
在一种可行的实现方式中,所述获取所述标定板图像中每个环形图案的内边缘和外边缘,包括:
根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘,将所述每个环形图案的像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,所述获取所述标定板图像中每个环形图案的内边缘和外边缘,包括:
根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘;
对像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边缘和外边缘,将所述亚像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,所述根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标,包括:
对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块;
计算每个分割块的重心;
对所述多个分割块的重心进行拟合,根据拟合结果确定所述每个环形图案的中心点的图像坐标。
在一种可行的实现方式中,所述对每个环形图案的内边缘和外边缘之间的区域进行分割,包括:
根据每个环形图案的内边缘和外边缘的法线对每个环形图案的内边缘和外边缘之间的区域进行分割。
在一种可行的实现方式中,所述方法还包括:
确定所述标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系;
根据所述相对位置关系以及预先确定的所述标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
在一种可行的实现方式中,所述根据每个中心点的图像坐标和对应的世界坐标,确定相机的内外参数,包括:
根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
第二方面,本申请提供一种相机标定装置,包括:
第一获取模块,用于获取标定板图像,所述标定板图像中包括多个环形图案;
第二获取模块,用于获取所述标定板图像中每个环形图案的内边缘和外边缘;
确定模块,用于根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标;
标定模块,用于根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
在一种可行的实现方式中,所述第二获取模块用于:
根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘,将所述每个环形图案的像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,所述第二获取模块用于:
根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘;
对像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边缘和外边缘,将所述亚像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,所述确定模块用于:
对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块;
计算每个分割块的重心;
对所述多个分割块的重心进行拟合,根据拟合结果确定所述每个环形图案的中心点的图像坐标。
在一种可行的实现方式中,所述确定模块用于:
根据每个环形图案的内边缘和外边缘的法线对每个环形图案的内边缘和外边缘之间的区域进行分割。
在一种可行的实现方式中,所述标定模块还用于:
确定所述标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系;
根据所述相对位置关系以及预先确定的所述标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
在一种可行的实现方式中,所述标定模块用于:
根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
第三方面,本申请提供一种电子设备,包括存储器和处理器,所述存储器和处理器连接;
所述存储器用于存储计算机程序;
所述处理器用于在所述计算机程序被执行时,实现如第一方面所述的方法。
第四方面,本申请提供一种计算机可读存储介质,其上存储有计算机程序,所述计算机程序被处理器执行时,实现如第一方面所述的方法。
第五方面,本申请提供一种计算机程序产品,包括计算机程序,所述计算机程序被处理器执行时实现第一方面所述的方法
本申请提供一种相机标定方法、装置及电子设备,通过对标定板的图案进行改进,采用具有环形图案的标定板进行相机标定,由于环形图案具有内圆和外圆两个边缘,利用这两个边缘共同确定环形图案的中心点的图像坐标,相比于采用实心圆方式来确定圆心的图像坐标,本实施例中利用环形图案的两个边缘得到的中心点的图像坐标更精确,从而可使得相机的标定结果更为准确。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图做一简单地介绍,显而易见地,下面描述中的附图是本申请的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动性的前提下,还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的一种相机标定方法的流程示意图一;
图2为本申请实施例提供的一种标定板示意图;
图3为本申请实施例提供的一种标定板图像示意图;
图4为本申请实施例提供的一种相机标定方法的流程示意图二;
图5为本申请实施例提供的环形图案分割示意图;
图6为本申请实施例提供的一种相机标定装置的结构示意图;
图7为本申请实施例提供的一种电子设备的结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚,下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。
在图像测量、机器视觉等各类应用中,常常需要从相机获取的图像信息出发计算三维空间中物体的几何信息,例如,进行三维物体重建,识别物体的深度信息等,而物体表面某点的三维位置与其在图像中对应点之间的相互关系是由相机成像的几何模型,也就是相机参数决定的。因此,进行相机参数的标定直接影响相机工作产生结果的准确性。
相机标定可以借助三维或二维标定板实现,标定板用于提供已知坐标信息(世界坐标)的点,也称为靶标点,利用相机拍摄标定板,通过对获得的标定板的图像进行处理,提取靶标点的图像坐标,基于每个靶标点的图像坐标和世界坐标确定相机的内外参。其中,世界坐标是基于由用户定义的三维世界的世界坐标系,用于描述标定板在三维世界里的位置。图像坐标是图像像素坐标,用于描述像素在图像中的位置。世界坐标和图像坐标均采用笛卡尔坐标表示。
由于三维标定板制作复杂,因此在实际应用中通常采用二维标定板,标定板上具有特定图案,例如,标定板上具有间隔排列的实心圆。将标定板放置好之后,标定板上实心圆的圆心(即靶标点)的世界坐标即可确定,再通过相机拍摄标定板,对得到的图像进行处理,提取图像中实心圆的圆心的图像坐标,从而根据圆心的图像坐标和世界坐标确定相机的内外参。
在上述相机标定的过程中,由于靶标点的世界坐标可以预先获得,且世界坐标较为准确,因此,相机的标定结果的准确度主要由靶标点的图像 坐标的精度决定,即,从图像中提取的靶标点的图像坐标越精确,则相机的标定结果越准确。
然而,在采用具有实心圆图案的标定板进行相机标定时,从图像中提取实心圆的圆心的图像坐标的精度通常较低。特别是对于分辨率较低的相机,例如飞行时间法(Time of flight,TOF)深度相机,从图像中提取实心圆的圆心的图像坐标的精度会更低,从而导致标定结果更不准确。
为了提高相机标定精度,本申请提供一种相机标定方法,对标定板的图案进行改进,提出采用具有环形图案的标定板进行相机标定,由于环形图案具有内圆和外圆两个边缘,利用内圆和外圆两个边缘共同确定环形图案的中心点,得到的中心点的图像坐标更精确,从而可使得相机的标定结果更为准确。
下面,将通过具体的实施例对本申请提供的相机标定方法进行详细地说明。可以理解的是,下面这几个具体的实施例可以相互结合,对于相同或相似的概念或过程可能在某些实施例不再赘述。
图1为本申请实施例提供的一种相机标定方法的流程示意图一。如图1中所示,该方法包括:
S101、获取标定板图像。
其中,标定板图像中包括多个环形图案。示例的,本申请实施例采用的标定板具有如图2中所示的环形图案,标定板的背景可以为白色,圆环部分可以为黑色。标定板上的每个环形图案的大小可以相同或不同,环形图案之间的间隔也可以相同或不同,本申请实施例对此不做限定。此外,本实施例中的标定板的基材可以为反射式或背照式。采用背照式基材时,标定板基材透明,在标定板背面增加光源,有利于后续的图像处理,可使得标定结果更准确。
为了实现相机标定,标定板图像需要包括标定板的至少三个视角,相机在对标定板进行拍摄时,可以采用两种方式。一种方式中,可以对一张标定板进行多次拍摄,该标定板上包括4个以上环形图案。每次拍摄时调整标定板或相机的位姿,采用这种方式时,一张标定板可以尽可能的占满相机的整个视场,标定板中的靶标点的数量可以更多,有利于提高标定精度。
另一种方式中,可以对多张标定板进行一次拍摄,每个标定板上包括 4个以上环形图案,示例的,如图3中所示是对不同位姿的4张标定板进行一次拍摄得到的标定板图像。每张标定板的位姿不同,这样,通过一次拍摄即可获得多个不同视角的标定板的图像,标定效率较高。
S102、获取标定板图像中每个环形图案的内边缘和外边缘。
S103、根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标。
由于标定板中的环形图案与标定板的背景部分的颜色有明显区分,因此可以通过对标定板图像进行边缘检测,获取到每个环形图案的边缘,环形图案的边缘包括内边缘和外边缘,即内圆和外圆。
环形图案的内边缘和外边缘共同确定了环形图案的圆环的范围,从而,根据内边缘和外边缘即可共同确定环形图案的中心点的图像坐标。
S104、根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
每个环形图案的中心点的世界坐标经过由相机的内外参数构成的矩阵的转换,即可转换为每个环形图案的中心点的图像坐标,在本实施例中,由于标定板是预先按照一定的位姿放置的,标定板中每个环形图案的中心点的世界坐标可以提前确定,因此,在从标定板图像中提取出每个中心点的图像坐标之后,根据图像坐标和对应的世界坐标,即可确定相机的内外参数,完成相机的标定。
本实施例提供的相机标定方法,对标定板的图案进行改进,采用具有环形图案的标定板进行相机标定,由于环形图案具有内圆和外圆两个边缘,利用这两个边缘共同确定环形图案的中心点的图像坐标,相比于采用实心圆方式来确定圆心的图像坐标,本实施例中利用环形图案的两个边缘得到的中心点的图像坐标更精确,从而可使得相机的标定结果更为准确。
通过对相机进行上述标定,获取准确的相机参数,可进一步使得相机工作产生的结果更为准确。示例的,对于TOF深度相机,在对相机标定后,基于相机参数确定的拍摄对象的深度信息会更准确。
在上述实施例的基础上,进一步对从标定板图像中提取每个环形图案的中心点的图像坐标进行说明。图4为本申请实施例提供的一种相机标定方法的流程示意图二。如图4所示,该方法包括:
S401、获取标定板图像。
本实施例中S401与图1所示实施例中S101类似,此处不再赘述。
S402、根据标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘。
由于标定板中的环形图案与标定板的背景部分的颜色有明显区分,因此,通过检测标定板图像中各个像素点的灰度值,根据灰度值的变化即可确定环形图案的边缘和边缘。示例的,通过设置灰度变化阈值,在相邻像素的灰度值变化大于该灰度变化阈值时,将灰度值较低的像素确定为环形图案边缘的像素。通过对整个标定板图像中的像素点的灰度值的检测,即可确定出每个环形图案的像素级别的内边缘和外边缘。
S403、对像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边缘和外边缘。
对于分辨率较低,即像素较低的相机,基于像素级别的边缘进行后续处理,可能造成精度较低,因此,本实施中进一步对像素级别的内边缘和外边缘进行平滑处理,示例的,采用插值法对像素级别的内边缘和外边缘的像素点的灰度值进行插值,以得到亚像素级别的内边缘和外边缘。示例的,还可以通过对像素级别的内边缘和外边缘的像素点灰度值进行拟合以得到亚像素级别的内边缘和外边缘。
需要说明的是,S403中对环形图案的内边缘和外边缘进行平滑处理得到亚像素级别的内边缘和外边缘是为了提高标定精确度,在实际标定过程中可以根据需要选择执行或跳过S403。即,在一种实现方式中,可以仅执行S401-S402,在确定每个环形图案的像素级别的内边缘和外边缘后,将将每个环形图案的像素级别的内边缘和外边缘确定为每个环形图案的内边缘和外边缘。在另一种实现方式中,执行S401-S403,即确定出每个环形图案的亚像素级别的内边缘和外边缘,将每个环形图案的亚像素级别的内边缘和外边缘确定为每个环形图案的内边缘和外边缘。之后再进一步基于确定出的每个环形图案的内边缘和外边缘执行后续的S404-S408。
S404、对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块,并计算每个分割块的重心。
在确定每个环形图案的内边缘和外边缘后,对内边缘和外边缘之间的环形区域进行分割,可选的,通过确定内边缘和/或外边缘的多个位置处的法线,根据每个环形图案的内边缘和/或外边缘的法线,对每个环形图案的 内边缘和外边缘之间的区域进行分割。以采用内边缘的法线为例进行说明,将内边缘分为多个弧线段,图5中示意的弧线AB为其中一个弧线段,在A点和B点处分别确定弧线的法线(图中虚线所示),两条法线分别与外边缘相交,从而两条法线以及内外边缘之间组成的以网格状示意的一个区域即为分割得到的一个分割块(为清楚示意,图5中环形区域未填充颜色)。需要说明的是,在对圆环分割时,分割块的大小可以根据需要设置,示例的,以两个像素为单位将内边缘分为多个弧线段,再按照上述方法进行分割。
对于分割得到的每个分割块,计算其重心位置的图像坐标。示例的,可以通过灰度重心法,根据分割块的灰度值确定分割块的重心。如图5中所示的三个点即分别为三个分割块的重心,图中其他分割块和其重心未示意。
S405、对多个分割块的重心进行拟合,根据拟合结果确定每个环形图案的中心点的图像坐标。
在确定多个分割块的重心后,对多个分割块的重心进行拟合,示例的,可以采用平均值法、最小二乘法、高斯拟合等方式对多个分割块的重心进行啮合,从而确定环形图案的中心点的图像坐标。
S406、确定标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系。
由于相机标定是依赖于靶标点(本实施例中环形图案的中心点)的图像坐标与世界坐标之间的转换,因此,在提取到每个环形图案的中心点的图像坐标之后,需要按照坐标值的横轴和纵轴的大小确定各环形图案的中心点之间的相对位置关系,以便于确定图像坐标和世界坐标之间的对应关系。
S407、根据相对位置关系以及预先确定的标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
根据每个环形图案的中心点的图像坐标,可以确定每个环形图案的中心点之间的相对位置关系,再进一步结合预先确定的标定板图像中各环形图案的中心点的世界坐标,即可确定每个环形图案的中心点的图像坐标和世界坐标之间的一一对应关系。
S408、根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
图像坐标系与世界坐标系之间的映射关系由相机的内外参数矩阵构成,在进行参数标定时,首先根据每个标定板中的环形图案的图像坐标和世界坐标确定每个标定板对应的单应矩阵,由多个标定板的单应矩阵确定相机的内参,进一步的,通过单应矩阵和外参确定相机的外参。
本实施例提供的相机标定方法,通过采用具有环形图案的标定板进行相机标定,由于环形图案具有内圆和外圆两个边缘,利用这两个边缘共同确定环形图案的中心点的图像坐标,并且,在进行边缘检测时,可以通过对像素级别的内边缘和外边缘进行优化处理,得到亚像素级别的内边缘和外边缘,从而进一步提高边缘精度。根据高精度的两个环形边缘确定环形图案的中心点的图像坐标,相比于采用实心圆方式来确定圆心的图像坐标更精确,从而可使得相机的标定结果更为准确。
图6为本申请实施例提供的一种相机标定装置的结构示意图。如图6所示,相机标定装置60包括:
第一获取模块601,用于获取标定板图像,标定板图像中包括多个环形图案。
第二获取模块602,用于获取标定板图像中每个环形图案的内边缘和外边缘。
确定模块603,用于根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标。
标定模块604,用于根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
在一种可行的实现方式中,第二获取模块602用于:
根据标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘,将每个环形图案的像素级别的内边缘和外边缘确定为每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,第二获取模块602用于:
根据标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘;
对像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边缘和外边缘,将亚像素级别的内边缘和外边缘确定为每个环形图案的内边缘和外边缘。
在一种可行的实现方式中,确定模块603用于:
对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块;
计算每个分割块的重心;
对多个分割块的重心进行拟合,根据拟合结果确定每个环形图案的中心点的图像坐标。
在一种可行的实现方式中,确定模块603用于:
根据每个环形图案的内边缘和外边缘的法线对每个环形图案的内边缘和外边缘之间的区域进行分割。
在一种可行的实现方式中,标定模块604还用于:
确定标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系;
根据相对位置关系以及预先确定的标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
在一种可行的实现方式中,标定模块604用于:
根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
本实施例提供的相机标定装置可用于执行上述方法实施例中的相机标定方法,其实现原理和计算效果类似,此处不再赘述。
图7为本申请实施例提供的一种电子设备的结构示意图。如图7所示,电子设备70包括存储器701和处理器702,存储器701和处理器702可以通过总线703连接。
存储器701用于存储计算机程序。
处理器702用于在计算机程序被执行时,实现上述方法实施例中的相机标定方法。
可选的,该电子设备可以是用于对相机拍摄的图像进行处理并进行相机内外参数计算的计算机设备、服务器等。或者,该电子设备也可以为具 有相机的电子设备,该电子设备可对自身具有的相机进行参数标定。
本申请实施例还提供一种计算机可读存储介质,其上存储有计算机程序,计算机程序被处理器执行时,实现上述方法实施例中的相机标定方法。
本申请实施例还提供一种计算机程序产品,包括计算机程序,计算机程序被处理器执行时实现上述方法实施例中的相机标定方法。
本领域普通技术人员可以理解:实现上述各方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成。前述的程序可以存储于一计算机可读取存储介质中。该程序在执行时,执行包括上述各方法实施例的步骤;而前述的存储介质包括:ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是:以上各实施例仅用以说明本申请的技术方案,而非对其限制;尽管参照前述各实施例对本申请进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分或者全部技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本申请各实施例技术方案的范围。

Claims (17)

  1. 一种相机标定方法,其特征在于,包括:
    获取标定板图像,所述标定板图像中包括多个环形图案;
    获取所述标定板图像中每个环形图案的内边缘和外边缘;
    根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标;
    根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
  2. 根据权利要求1所述的方法,其特征在于,所述获取所述标定板图像中每个环形图案的内边缘和外边缘,包括:
    根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘,将所述每个环形图案的像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
  3. 根据权利要求1所述的方法,其特征在于,所述获取所述标定板图像中每个环形图案的内边缘和外边缘,包括:
    根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘;
    对所述像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边缘和外边缘,将所述亚像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
  4. 根据权利要求1-3任一项所述的方法,其特征在于,所述根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标,包括:
    对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块;
    计算每个分割块的重心;
    对所述多个分割块的重心进行拟合,根据拟合结果确定所述每个环形图案的中心点的图像坐标。
  5. 根据权利要求4所述的方法,其特征在于,所述对每个环形图案的内边缘和外边缘之间的区域进行分割,包括:
    根据每个环形图案的内边缘和/或外边缘的法线对每个环形图案的内边缘和外边缘之间的区域进行分割。
  6. 根据权利要求1-3任一项所述的方法,其特征在于,所述方法还包括:
    确定所述标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系;
    根据所述相对位置关系以及预先确定的所述标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
  7. 根据权利要求6所述的方法,其特征在于,所述根据每个中心点的图像坐标和对应的世界坐标,确定相机的内外参数,包括:
    根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
  8. 一种相机标定装置,其特征在于,包括:
    第一获取模块,用于获取标定板图像,所述标定板图像中包括多个环形图案;
    第二获取模块,用于获取所述标定板图像中每个环形图案的内边缘和外边缘;
    确定模块,用于根据每个环形图案的内边缘和外边缘,确定每个环形图案的中心点的图像坐标;
    标定模块,用于根据每个环形图案的中心点的图像坐标和对应的世界坐标,确定相机的内外参数。
  9. 根据权利要求8所述的装置,其特征在于,所述第二获取模块用于:
    根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘,将所述每个环形图案的像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
  10. 根据权利要求8所述的装置,其特征在于,所述第二获取模块用于:
    根据所述标定板图像中的像素点的灰度值,确定每个环形图案的像素级别的内边缘和外边缘;
    对像素级别的内边缘和外边缘进行平滑处理,得到亚像素级别的内边 缘和外边缘,将所述亚像素级别的内边缘和外边缘确定为所述每个环形图案的内边缘和外边缘。
  11. 根据权利要求8-10任一项所述的装置,其特征在于,所述确定模块用于:
    对每个环形图案的内边缘和外边缘之间的区域进行分割,得到多个分割块;
    计算每个分割块的重心;
    对所述多个分割块的重心进行拟合,根据拟合结果确定所述每个环形图案的中心点的图像坐标。
  12. 根据权利要求11所述的装置,其特征在于,所述确定模块用于:
    根据每个环形图案的内边缘和外边缘的法线对每个环形图案的内边缘和外边缘之间的区域进行分割。
  13. 根据权利要求8-10任一项所述的装置,其特征在于,所述标定模块还用于:
    确定所述标定板图像中每个环形图案的中心点的图像坐标之间的相对位置关系;
    根据所述相对位置关系以及预先确定的所述标定板图像中各环形图案的中心点的世界坐标,确定每个环形图案的中心点的图像坐标和世界坐标之间的对应关系。
  14. 根据权利要求13所述的装置,其特征在于,所述标定模块用于:
    根据每个环形图案的中心点的图像坐标和世界坐标之间的对应关系,以及图像坐标系与世界坐标系之间的映射关系,确定相机的内外参数。
  15. 一种电子设备,其特征在于,包括存储器和处理器,所述存储器和处理器连接;
    所述存储器用于存储计算机程序;
    所述处理器用于在所述计算机程序被执行时,实现如权利要求1-7任一项所述的方法。
  16. 一种计算机可读存储介质,其上存储有计算机程序,其特征在于,所述计算机程序被处理器执行时,实现如上述权利要求1-7中任一项所述的方法。
  17. 一种计算机程序产品,包括计算机程序,其特征在于,所述计算 机程序被处理器执行时实现权利要求1-7中任一项所述的方法。
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