WO2021189626A1 - 一种标定板、标定方法及*** - Google Patents

一种标定板、标定方法及*** Download PDF

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Publication number
WO2021189626A1
WO2021189626A1 PCT/CN2020/090925 CN2020090925W WO2021189626A1 WO 2021189626 A1 WO2021189626 A1 WO 2021189626A1 CN 2020090925 W CN2020090925 W CN 2020090925W WO 2021189626 A1 WO2021189626 A1 WO 2021189626A1
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Prior art keywords
calibration
dot
checkerboard
dimensional matrix
characteristic
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PCT/CN2020/090925
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English (en)
French (fr)
Inventor
武立华
刘贤焯
庞敏健
黄志明
王晓梦
曾杰
杨洪飞
Original Assignee
深圳奥比中光科技有限公司
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Application filed by 深圳奥比中光科技有限公司 filed Critical 深圳奥比中光科技有限公司
Publication of WO2021189626A1 publication Critical patent/WO2021189626A1/zh
Priority to US17/825,404 priority Critical patent/US20220284630A1/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00—Diagnosis, testing or measuring for television systems or their details
    • H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30204—Marker
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30244—Camera pose

Definitions

  • This application relates to the technical fields of image processing, computer vision and camera calibration, and in particular to a calibration board, a calibration method and a system.
  • the calibration board is widely used in machine vision, image measurement, photogrammetry, and 3D reconstruction.
  • the camera takes an image of the calibration plate with a fixed-pitch pattern array, and after the calibration algorithm is calculated, the geometric model of the camera can be obtained, thereby obtaining high-precision measurement and reconstruction results.
  • the purpose of this application is to provide a calibration board, a calibration method and a system to solve at least one of the above-mentioned background technical problems.
  • a calibration board includes checkerboard cells arranged on the surface of the calibration board, wherein:
  • At least one dot is separately arranged in each of the checkerboard cells
  • the dots include at least a first characteristic dot and a second characteristic dot, the first characteristic dot and the second characteristic dot are arranged on the checkerboard cell according to a random rule or a specific rule, and The diameter of the first characteristic dot is greater than the diameter of the second characteristic dot.
  • the centers of the first characteristic dot and the second characteristic dot are centroids, wherein the centroids of the characteristic dots have perspective invariance, and the centroids of characteristic dots with different diameters have the Positioning information of the checkerboard cell.
  • the checkerboard unit includes a black and white square grid, wherein the intersection of the black squares is the corner point of the checkerboard unit.
  • a calibration method includes the following steps:
  • S1 Obtain a calibration image of the calibration board taken by the camera; wherein the calibration board includes checkerboard cells arranged on the surface of the calibration board, and each of the checkerboard cells is individually provided with at least one dot; the dot Comprising at least a first characteristic dot and a second characteristic dot, the diameter of the first characteristic dot is greater than the diameter of the second characteristic dot;
  • step S6 According to the dot centroid coordinate number information obtained in step S5, output the corresponding corner point number information of the checkerboard cell where the dot is located. According to the dot centroid coordinate number information, the checkerboard corner point number information and the corresponding camera model, pass The preset calibration algorithm is solved to obtain the calibration data.
  • step S1 the calibration plate is placed in the field of view of the camera, and the camera is used to perform imaging processing at multiple preset distances to obtain multiple calibration images containing the calibration plate.
  • step S3 on the basis of checkerboard cells, each dot that is detected to meet the preset requirements is connected to form a grid to obtain the first two-dimensional matrix.
  • step S4 based on the first two-dimensional matrix, the diameter of the dot that meets the requirements is judged. If the detected dot is the first characteristic dot, then the first The value of the corresponding position in the two-dimensional matrix remains unchanged. If the detected dot is the second characteristic dot, the value of the corresponding position in the first two-dimensional matrix is changed, thereby obtaining the second two-dimensional matrix.
  • step S5 the second two-dimensional matrix is matched with a preset calibration plate number template matrix, wherein the preset calibration plate number template is the same size as the calibration plate used to obtain the calibration image.
  • the point arrangement is also the same.
  • step S5 the second two-dimensional matrix is sequentially traversed, and the second two-dimensional matrix is matched with the preset calibration plate number template matrix. If the matching is successful, the preset calibration plate number is used. The position information of the center of mass of the dot on the template, and the position information of the center of mass of the detected dot is output.
  • a calibration system includes the calibration board, camera, processor and memory as described in the foregoing technical solution; wherein,
  • the camera is used to take a calibration image of the calibration board
  • the memory is used to store executable instructions for executing the calibration method
  • the processor is used to read executable instructions from the memory, and use the calibration image to calibrate the corresponding camera model to obtain calibration data.
  • the embodiment of the application provides a calibration board, which includes checkerboard cells arranged on the surface of the calibration board, wherein: each of the checkerboard cells is individually provided with at least one dot; the dot includes at least a first characteristic circle Dots and second characteristic dots, the first characteristic dots and the second characteristic dots are set on the checkerboard unit according to random rules or specific rules, and the diameter of the first characteristic dots is greater than The diameter of the second characteristic dot.
  • the calibration board of this application uses the characteristics of high detection accuracy of dot marks and strong anti-blur ability, combined with the corner points of the checkerboard unit to improve the stability and accuracy of the calibration board detection, even if the calibration board is partially blocked or exceeds the camera's field of view,
  • the camera can also be calibrated normally, and the calibration drawing is more flexible; at the same time, it is also suitable for evaluating and verifying the performance of the calibration results.
  • the reprojection error, calibration board reconstruction and other indicators are used to evaluate the calibration data. Accuracy.
  • Fig. 1 is a schematic structural diagram of a calibration plate provided according to an embodiment of the present application.
  • Fig. 2 is a flowchart of a calibration method provided according to an embodiment of the present application.
  • Fig. 3 is a schematic diagram of a two-dimensional matrix of a calibration method provided according to an embodiment of the present application.
  • Fig. 4 is a schematic diagram of a calibration system provided according to another embodiment of the present application.
  • connection can be used for fixing or circuit connection.
  • first and second are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with “first” and “second” may explicitly or implicitly include one or more of these features.
  • “plurality” means two or more, unless otherwise specifically defined.
  • FIG. 1 is a schematic structural diagram of a calibration plate provided according to an embodiment of the present application.
  • the surface of the calibration board 100 is provided with checkerboard cells 101, and each checkerboard cell 101 is individually provided with at least one dot; wherein the dot includes at least a first characteristic dot 102 and a second characteristic dot 103, the first characteristic circle
  • the dots 102 and the second characteristic dots 103 are arranged on a checkerboard according to random rules or specific rules, and the diameter of the first characteristic dots 102 is larger than the diameter of the second characteristic dots 103.
  • the dots can include three or more characteristic dots, and various characteristic dots have different diameters. This application only uses two characteristic dots with different diameters for description, which is not limited here. .
  • the checkerboard unit 101 includes a black and white square grid, wherein the intersection of the black squares is the corner point 104 of the checkerboard unit 101; the first characteristic dot 102 and the second characteristic dot 103
  • the center of the circle is the center of mass, the center of mass of the characteristic dot has perspective invariance, and the center of mass of the characteristic dots of different diameters has the positioning information of the checkerboard unit 101; for example, the dot is similarly binary coded, the first characteristic dot Is 1, the second feature circle is 0, then a local area of the calibration plate is equivalent to a two-dimensional code at this time, so that the calibration plate 100 has directionality, so that the calibration plate 100 has a partial view that is allowed to be blocked during application specialty.
  • the specific color of the checkerboard is not particularly limited in this embodiment, as long as the color contrast between the checkerboard unit and the interval can be greater than a certain preset threshold.
  • the preset threshold can be set according to the intensity of the contrast, so as to meet the requirements of camera calibration.
  • the embodiment of the application utilizes the characteristics of high detection accuracy of the dot mark and strong anti-blur ability, combined with the corner points of the checkerboard unit to improve the stability and accuracy of the calibration board detection, even if the calibration board is partially blocked or exceeds the camera's field of view,
  • the camera can also be calibrated normally, and the calibration drawing is more flexible; at the same time, it is also suitable for the evaluation and verification tasks of the calibration result performance.
  • the calibration data is evaluated by using the obtained calibration data and camera model, using the reprojection error, calibration board reconstruction and other indicators to evaluate the calibration data. Accuracy.
  • FIG. 2 is a flowchart of a calibration method proposed based on the calibration board 100 of the foregoing embodiment. The method includes the following steps:
  • step S6 According to the dot centroid coordinate number information obtained in step S5, output the corresponding corner point number information of the checkerboard cell where the dot is located. According to the dot centroid coordinate number information, the checkerboard corner point number information and the corresponding camera model, pass The preset calibration algorithm is solved to obtain the calibration data.
  • the calibration plate is placed in the field of view of the camera, and the camera is used to perform imaging processing at multiple preset distances to obtain multiple calibration images containing the calibration plate; in some embodiments, Adjust the direction of the calibration board or the camera and the distance between the two, use the camera to obtain multiple sets of calibration images with rich coordinate information at different positions, different angles, and different postures; among them, the calibration image can be a complete calibration board image , It can also be an incomplete calibration plate image.
  • the camera in this embodiment can also be other imaging devices such as video cameras, cameras, etc. It can be a single imaging device or multiple imaging devices arranged in parallel, as long as the calibration board is in multiple imaging devices. It suffices to be within the field of view of each imaging device, and the type and quantity of imaging are not limited in the embodiment of the present application.
  • step S2 the position of the calibration plate in the calibration image is random, and the size of the calibration plate in the calibration image will change with the distance of the position. Therefore, it is necessary to determine the position of the calibration plate in the calibration image before checking the calibration.
  • the dots on the board are detected using the Hough transform circle detection algorithm to detect the position and the center of mass of the dots on the calibration board in the calibration image.
  • each dot that is detected to meet the preset requirements is connected to form a grid to obtain a first two-dimensional matrix.
  • the center of mass is checked in a grid based on checkerboard cells. If the center of mass is detected, the corresponding position in the first two-dimensional matrix is represented by the value 1. If it is based on the checkerboard If the center of mass is not detected in the element-based grid, the corresponding position in the first two-dimensional matrix is represented by the value -1. It should be understood that other values can also be used to represent the result of the centroid detection in the first two-dimensional matrix, and it only needs to indicate whether there is a centroid in the current grid, and there is no limitation here.
  • step S4 based on the first two-dimensional matrix obtained in step S3, the diameter of the dot that meets the requirements is judged, and the dot is divided into the first characteristic dot and the second characteristic dot according to the diameter of the dot.
  • the diameter of a characteristic dot is larger than the diameter of the second characteristic dot. If the detected dot is the first characteristic dot, the value of the corresponding position in the first two-dimensional matrix remains unchanged and remains 1.
  • the dot of is the second characteristic dot, and the value of the corresponding position in the first two-dimensional matrix changes to 0; therefore, the second two-dimensional matrix as shown in Figure 3(b) can be obtained. It should be understood that other values can be used to replace the value of the corresponding position in the first two-dimensional matrix to change, and it only needs to indicate that the value of the current first two-dimensional matrix has changed, and there is no limitation here.
  • step S5 the second two-dimensional matrix is matched with a preset calibration plate number template matrix, where the preset calibration plate number template is the same size as the calibration plate used to obtain the calibration image, and the dot arrangement is also the same ,
  • the calibration board number template not only has number information (such as (1, 2), (2, 3)) on each dot, but also has information such as the corners of the checkerboard, the size of the checkerboard, and the position of the center of mass of the dot. Traverse the second two-dimensional matrix in turn, and match it with the preset calibration board number template matrix.
  • the direction of the calibration board can be calibrated according to the position relationship of the center of mass of the dot, and the rest of the checkerboard cells in the calibration image can be gradually matched according to the diffusion method. If the matching is successful, the position information of the center of mass of the dot will be output according to the position information of the center of mass of the dot on the preset calibration plate number template.
  • step S6 according to the dot centroid number information in step S5, output the corner point number information corresponding to the checkerboard cell where the dot is located.
  • the dot centroid number information, checkerboard corner number information, and the corresponding camera model (such as needle Hole model) and the preset calibration algorithm to solve the calibration data, such as the internal and external parameters of the camera and the lens distortion coefficient.
  • FIG. 4 is a calibration system based on the calibration method of the foregoing embodiment provided according to another embodiment of the present application.
  • the system 400 includes a camera 401, a processor 402, a memory 403, and the calibration board 100 in the foregoing embodiment.
  • the camera 401 is used to capture the calibration image containing the calibration board 100;
  • the processor 402 is used to read the executable instructions containing the calibration method from the memory, use the calibration image to calibrate the corresponding camera model to obtain the calibration data, and It is uploaded to the memory 403 for storage;
  • the memory 403 is used to store the executable instructions of the above-mentioned calibration method and to store the calibration data obtained by the processor 402.
  • the camera is controlled to collect images of the calibration board at a plurality of preset distances to obtain a plurality of calibration images.
  • the calibration data obtained by the processor solution includes an internal parameter matrix, an external parameter matrix, and distortion parameters.
  • the embodiment of the present application also provides a storage medium for storing a computer program, and when the computer program is executed, at least the calibration method described above is executed.
  • the storage medium may be implemented by any type of volatile or non-volatile storage device, or a combination thereof.
  • the non-volatile memory can be read-only memory (ROM, Read Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), and erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only).
  • Memory Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Magnetic Random Access Memory (FRAM, Ferromagnetic Random Access Memory), Flash Memory (Flash Memory), Magnetic Surface Memory, Optical Disks, Or CD-ROM (Compact Disc Read-Only Memory); magnetic surface memory can be disk storage or tape storage.
  • the volatile memory may be a random access memory (RAM, Random Access Memory), which is used as an external cache.
  • RAM random access memory
  • SRAM static random access memory
  • SSRAM synchronous static random access memory
  • Synchronous Static Random Access Memory Synchronous Static Random Access Memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Enhanced Synchronous Dynamic Random Access Memory
  • SLDRAM synchronous connection dynamic random access memory
  • SLDRAM SyncLink Dynamic Random Access Memory
  • DRAM Direct Rambus Random Access Memory
  • the storage media described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memory.

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Abstract

一种标定板（100），包括有设置于标定板（100）表面的棋盘格单元（101），其中：每个棋盘格单元（101）内单独设置有至少一个圆点；圆点至少包括第一特征圆点（102）和第二特征圆点（103），第一特征圆点（102）和第二特征圆点（103）按随机规则或特定的规则设置在棋盘格单元（101）上，且第一特征圆点（102）的直径大于第二特征圆点（103）的直径。标定板（100）利用圆点标识检测精度高、抗模糊能力强等特点，与棋盘格单元（101）的角点（104）结合提高了标定板（100）检测的稳定性和精度。

Description

一种标定板、标定方法及***
本申请要求于2020年3月24日提交中国专利局，申请号为202010210792.0，发明名称为“一种标定板、标定方法及***”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、计算机视觉和相机标定技术领域，尤其涉及一种标定板、标定方法及***。
背景技术
标定板在机器视觉、图像测量、摄影测量、以及三维重建等方面有广泛应用。通过相机拍摄带有固定间距图案阵列的标定板的图像，经过标定算法的计算，可以得出相机的几何模型，从而得到高精度的测量和重建结果。
在相机标定过程中，目前使用比较广泛的方式是采用棋盘格。但是这种棋盘格没有方向性，不能被遮挡，要求相机标定时所拍摄的图像必须包含整个棋盘格并且棋盘格上的角点能全部被检测出来，否则标定相机采集的数据无效。而现有的经过改进的ChArco标定板在标定过程中，角点位置准确性不高，且如果相机焦距变小时，采集到的图像会出现模糊现象，从而容易导致不能检测出角点。
发明内容
本申请的目的在于提供一种标定板、标定方法及***，以解决上述背景技术问题中的至少一种问题。
为达到上述目的，本申请实施例的技术方案是这样实现的：
一种标定板，包括有设置于标定板表面的棋盘格单元，其中：
每个所述棋盘格单元内单独设置有至少一个圆点；
所述圆点至少包括第一特征圆点和第二特征圆点，所述第一特征圆点和所述第二特征圆点按随机规则或特定的规则设置在所述棋盘格单元上，且所述第一特征圆点的直径大于所述第二特征圆点的直径。
在一些实施例中，所述第一特征圆点及所述第二特征圆点的圆心为质心，其中，特征圆点的质心具有透视不变性，且不同直径的特征圆点的质心具有所述棋盘格单元的定位信息。
在一些实施例中，所述棋盘格单元包括有黑白相间的正方形方格，其中，黑色方格的交点为棋盘格单元的角点。
本申请实施例另一技术方案为：
一种标定方法，包括如下步骤：
S1：获取相机拍摄的标定板的标定图像；其中，所述标定板包括有设置于标定板表面的棋盘格单元，每个所述棋盘格单元内单独设置有至少一个圆点；所述圆点至少包括第一特征圆点和第二特征圆点，所述第一特征圆点的直径大于所述第二特征圆点的直径；
S2：确定标定图像中标定板的位置，检测标定板上的圆点；
S3：基于棋盘格单元，将检测到的圆点网格化，得到第一二维矩阵；
S4：在第一二维矩阵的基础上，根据检测到的圆点的种类对其进行二值化，得到第二二维矩阵；
S5：将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，得到第二二维矩阵的圆点质心坐标编号信息；
S6：根据步骤S5所得到的圆点质心坐标编号信息，输出该圆点所在棋盘格单元的对应角点编号信息，根据圆点质心坐标编号信息、棋盘格角点编号信息及对应相机模型，通过预设标定算法求解得出标定数据。
在一些实施例中，步骤S1中，将所述标定板放置于相机的视野范围内，利 用相机在多个预设距离处进行成像处理以得到多幅包含所述标定板的标定图像。
在一些实施例中，步骤S3中，基于棋盘格单元的基础上，将检测到符合预设要求的每个圆点连接成网格，得到所述第一二维矩阵。
在一些实施例中，步骤S4中，基于所述第一二维矩阵的基础上，对检测符合要求的圆点的直径进行判断，若检测到的圆点为第一特征圆点，则第一二维矩阵中对应位置的数值不变，若检测到的圆点为第二特征圆点，则第一二维矩阵中对应位置的数值发生改变，从而得到所述第二二维矩阵。
在一些实施例中，步骤S5中，将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，其中，预设的标定板编号模板与用于获取标定图像的标定板尺寸相同，圆点排列方式也相同。
在一些实施例中，步骤S5中，依次遍历第二二维矩阵，将所述第二二维矩阵与预设的标定板编号模板矩阵进行匹配，如果匹配成功，则根据预设的标定板编号模板上的圆点质心的方位信息，输出检测到的圆点质心的方位信息。
本申请实施例又一技术方案为：
一种标定***，包括有前述技术方案所述的标定板、相机、处理器以及存储器；其中，
所述相机用于拍摄所述标定板的标定图像；
所述存储器用于存储执行标定方法的可执行指令；
所述处理器用于从存储器中读取可执行指令，利用标定图像对相应的相机模型进行标定得到标定数据。
本申请实施例提供一种标定板，包括有设置于标定板表面的棋盘格单元，其中：每个所述棋盘格单元内单独设置有至少一个圆点；所述圆点至少包括第一特征圆点和第二特征圆点，所述第一特征圆点和所述第二特征圆点按随机规则或特定的规则设置在所述棋盘格单元上，且所述第一特征圆点的直径大于所述第二特征圆点的直径。本申请标定板利用圆点标识检测精度高、抗模糊能力 强等特点，与棋盘格单元的角点结合提高了标定板检测的稳定性和精度，即使标定板部分被遮挡或超出相机视场，也能正常进行相机标定，标定采图更加灵活；同时也适用于对标定结果性能进行评估和验证任务，通过已得到的标定数据及相机模型，利用重投影误差、标定板重建等指标评估标定数据的准确性。
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作简单地介绍，显而易见地，下面描述中的附图仅仅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是根据本申请实施例提供的一种标定板的结构示意图。
图2是根据本申请实施例提供的一种标定方法的流程图。
图3是根据本申请实施例提供的标定方法的二维矩阵示意图。
图4是根据本申请另一实施例提供的一种标定***的示意图。
具体实施方式
为了使本申请实施例所要解决的技术问题、技术方案及有益效果更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅用以解释本申请，并不用于限定本申请。
需要说明的是，当元件被称为“固定于”或“设置于”另一个元件，它可以直接在另一个元件上或者间接在该另一个元件上。当一个元件被称为是“连接于”另一个元件，它可以是直接连接到另一个元件或间接连接至该另一个元件上。另外，连接即可以是用于固定作用也可以是用于电路连通作用。
需要理解的是，术语“长度”、“宽度”、“上”、“下”、“前”、“后”、“左”、“右”、“竖直”、“水平”、“顶”、“底”“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本 申请实施例和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本申请的限制。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多该特征。在本申请实施例的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
参照图1所示，图1为根据本申请实施例提供的一种标定板的结构示意图。标定板100表面设置有棋盘格单元101，每个棋盘格单元101内单独设置有至少一个圆点；其中，圆点至少包括第一特征圆点102和第二特征圆点103，第一特征圆点102和第二特征圆点103按随机规则或特定的规则设置在棋盘格上，且第一特征圆点102的直径大于第二特征圆点103的直径。应当理解的是，圆点可以包括有三种或三种以上的特征圆点，各种特征圆点具有不同的直径，本申请仅以两种不同直径的特征圆点进行说明，此处不做限制。
在一些实施例中，棋盘格单元101包括有黑白相间的正方形方格，其中，黑色方格的交点为棋盘格单元101的角点104；第一特征圆点102及第二特征圆点103的圆心为质心，特征圆点的质心具有透视不变性，且不同直径的特征圆点的质心具有棋盘格单元101的定位信息；例如，将圆点进行类似于二值化编码，第一特征圆点为1，第二特征圆点为0，则此时标定板的一个局部区域等效于一个二维码，使标定板100具有方向性，以使得标定板100具有在应用时允许被遮挡局部视图的特点。应当理解的是，本实施例对棋盘格的具体颜色不做出特别限定，只要能够满足棋盘格单元与间隔颜色对比度大于一定预设阈值即可。这个预设阈值可以是根据对比度的强烈自行设置，满足相机标定需求即可。
本申请实施例利用圆点标识检测精度高、抗模糊能力强等特点，与棋盘格单元的角点结合提高了标定板检测的稳定性和精度，即使标定板部分被遮挡或超出相机视场，也能正常进行相机标定，标定采图更加灵活；同时也适用于对标定结果性能进行评估和验证任务，通过已得到的标定数据及相机模型，利用 重投影误差、标定板重建等指标评估标定数据的准确性。
参照图2所示，图2为基于前述实施例标定板100提出的一种标定方法的流程图，方法包括以下步骤：
S1：获取相机拍摄的具有前述实施例标定板的标定图像；
S2：确定标定图像中标定板的位置，检测标定板上的圆点；
S3：基于棋盘格单元，将检测到的圆点网格化，得到第一二维矩阵；
S4：在第一二维矩阵的基础上，根据检测到的圆点种类对其进行二值化，得到第二二维矩阵；
S5：将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，得到第二二维矩阵的圆点质心坐标编号信息；
S6：根据步骤S5所得到的圆点质心坐标编号信息，输出该圆点所在棋盘格单元的对应角点编号信息，根据圆点质心坐标编号信息、棋盘格角点编号信息及对应相机模型，通过预设标定算法求解得出标定数据。
具体地，在步骤S1中，标定板放置于相机的视野范围内，利用相机在多个预设距离处进行成像处理以得到多幅包含有标定板的标定图像；在一些实施例中，可通过调整标定板或相机的方向以及两者之间的距离，在不同的位置、不同角度、不同姿态下利用相机获取具有丰富坐标信息的多组标定图像；其中，标定图像可以是完整的标定板图像，也可以是不完整的标定板图像。可以理解的是，本实施例中的相机还可以是摄像机、摄像头等其他的成像设备，可以是单独一台成像设备，亦可以是多台成像设备并列设置，只需标定板处于多台成像设备中每一台成像设备的视野范围内即可，本申请实施例中不对成像的种类和数量作限制。
步骤S2中，标定板在标定图像中出现的位置是随机的，标定板在标定图像中的大小随着位置的远近会有变化，因此，需要先确定标定图像中标定板的位置后再检测标定板上的圆点，利用利用霍夫变换圆检测算法对标定图像中标定板圆点的位置及其质心进行检测。
在步骤S3中，在棋盘格单元的基础上，将检测到符合预设要求的每个圆点连接成网格，得到第一二维矩阵。如图3(a)所示，在基于棋盘格单元基础上的网格中对质心进行检查，若检测到质心，则第一二维矩阵中相应的位置处用数值1表示，若基于棋盘格单元基础的网格中没有检测到质心，则第一二维矩阵中相应的位置处用数值-1表示。应当理解的是，也可用其他数值在第一二维矩阵中表示质心检测的结果，只需表明当前网格中是否存在质心即可，此处不做限制。
步骤S4中，基于步骤S3得到的第一二维矩阵的基础上，对检测符合要求的圆点的直径进行判断，根据圆点直径大小分为第一特征圆点和第二特征圆点，第一特征圆点的直径比第二特征圆点的直径大，若检测到的圆点为第一特征圆点，则第一二维矩阵中对应位置的数值不变，仍为1，若检测到的圆点为第二特征圆点，则第一二维矩阵中对应位置的数值发生改变，变为0；因此，可得到如图3(b)所示的第二二维矩阵。应当理解的是，可用其他数值代替第一二维矩阵中对应位置的数值发生变化，只需表明当前第一二维矩阵中的数值发生改变即可，此处不做限制。
在步骤S5中，将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，其中，预设的标定板编号模板与用于获取标定图像的标定板尺寸相同，圆点排列方式也相同，且标定板编号模板除了每个圆点上具有编号信息(如(1，2)、(2，3))外，还具有棋盘格角点、棋盘格尺寸及圆点质心的方位等信息。依次遍历第二二维矩阵，将其与预设的标定板编号模板矩阵进行匹配，根据圆点质心的位置关系可以标定标定板的方向，按扩散的方式逐步匹配标定图像中其余棋盘格单元检测到的圆点质心的位置信息，如果匹配成功，则根据预设的标定板编号模板上的圆点质心的方位信息，输出检测到的圆点质心的方位信息。
步骤S6中，根据步骤S5中圆点质心编号信息，输出该圆点所在的棋盘格单元对应的角点编号信息，通过圆点质心编号信息、棋盘格角点编号信息、对应相机模型(如针孔模型)以及预设的标定算法求解得出标定数据，如相机内 外参数及镜头畸变系数等。
参照图4所示，图4是根据本申请另一实施例提供的一种基于前述实施例标定方法的标定***。***400包括相机401、处理器402、存储器403、以及前述实施例中的标定板100。其中，相机401用于拍摄含有上述标定板100的标定图像；处理器402用于从存储器中读取含有上述标定方法的可执行指令，利用标定图像对相应的相机模型进行标定得到标定数据，并将其上传到存储器403中进行存储；存储器403用于存储上述标定方法的可执行指令，并存储由处理器402得到的标定数据。在一些实施例中，通过控制所述相机在多个预设距离处对标定板进行图像采集，以得到多幅标定图像。在一些实施例中，通过处理器求解得出的标定数据包括有内参矩阵、外参矩阵以及畸变参数。
本申请实施例还提供一种存储介质，用于存储计算机程序，该计算机程序被执行时至少执行如上所述的标定方法。
所述存储介质可以由任何类型的易失性或非易失性存储设备、或者它们的组合来实现。其中，非易失性存储器可以是只读存储器(ROM，Read Only Memory)、可编程只读存储器(PROM，Programmable Read-Only Memory)、可擦除可编程只读存储器(EPROM，ErasableProgrammable Read-Only Memory)、电可擦除可编程只读存储器(EEPROM，ElectricallyErasable Programmable Read-Only Memory)、磁性随机存取存储器(FRAM，FerromagneticRandom Access Memory)、快闪存储器(Flash Memory)、磁表面存储器、光盘、或只读光盘(CD-ROM，Compact Disc Read-Only Memory)；磁表面存储器可以是磁盘存储器或磁带存储器。易失性存储器可以是随机存取存储器(RAM，Random Access Memory)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(SRAM，Static Random Access Memory)、同步静态随机存取存储器(SSRAM，SynchronousStatic Random Access Memory)、动态随机存取存储器(DRAM，Dynamic Random AccessMemory)、同步动态随机存取存储器(SDRAM，Synchronous Dynamic Random AccessMemory)、双倍数据速率同步动 态随机存取存储器(DDRSDRAM，Double Data RateSynchronous Dynamic Random Access Memory)、增强型同步动态随机存取存储器(ESDRAM，Enhanced Synchronous Dynamic Random Access Memory)、同步连接动态随机存取存储器(SLDRAM，SyncLink Dynamic Random Access Memory)、直接内存总线随机存取存储器(DRRAM，Direct Rambus Random Access Memory)。本申请实施例描述的存储介质旨在包括但不限于这些和任意其它适合类型的存储器。
可以理解的是，以上内容是结合具体/优选的实施方式对本申请所作的进一步详细说明，不能认定本申请的具体实施只局限于这些说明。对于本申请所属技术领域的普通技术人员来说，在不脱离本申请构思的前提下，其还可以对这些已描述的实施方式做出若干替代或变型，而这些替代或变型方式都应当视为属于本申请的保护范围。在本说明书的描述中，参考术语“一种实施例”、“一些实施例”、“优选实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一些实施例或示例中。
在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。尽管已经详细描述了本申请的实施例及其优点，但应当理解，在不脱离由所附权利要求限定的范围的情况下，可以在本文中进行各种改变、替换和变更。
此外，本申请的范围不旨在限于说明书中所述的过程、机器、制造、物质组成、手段、方法和步骤的特定实施例。本领域普通技术人员将容易理解，可以利用执行与本文所述相应实施例基本相同功能或获得与本文所述实施例基本相同结果的目前存在的或稍后要开发的上述披露、过程、机器、制造、物质组成、手段、方法或步骤。因此，所附权利要求旨在将这些过程、机器、制造、 物质组成、手段、方法或步骤包含在其范围内。

Claims (12)

  1. 一种标定板，其特征在于，包括有设置于标定板表面的棋盘格单元，其中：
    每个所述棋盘格单元内单独设置有至少一个圆点；
    所述圆点至少包括第一特征圆点和第二特征圆点，所述第一特征圆点和所述第二特征圆点按随机规则或特定的规则设置在所述棋盘格单元上，且所述第一特征圆点的直径大于所述第二特征圆点的直径。
  2. 如权利要求1所述的标定板，其特征在于：所述第一特征圆点及所述第二特征圆点的圆心为质心，其中，特征圆点的质心具有透视不变性，且不同直径的特征圆点的质心具有所述棋盘格单元的定位信息。
  3. 如权利要求2所述的标定板，其特征在于：所述棋盘格单元包括有黑白相间的正方形方格，其中，黑色方格的交点为棋盘格单元的角点。
  4. 一种标定方法，其特征在于，包括如下步骤：
    S1：获取相机拍摄的标定板的标定图像；其中，所述标定板包括有设置于标定板表面的棋盘格单元，每个所述棋盘格单元内单独设置有至少一个圆点；所述圆点至少包括第一特征圆点和第二特征圆点，所述第一特征圆点的直径大于所述第二特征圆点的直径；
    S2：确定标定图像中标定板的位置，检测标定板上的圆点；
    S3：基于棋盘格单元，将检测到的圆点网格化，得到第一二维矩阵；
    S4：在第一二维矩阵的基础上，根据检测到的圆点的种类对其进行二值化，得到第二二维矩阵；
    S5：将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，得到第二二维矩阵的圆点质心坐标编号信息；
    S6：根据步骤S5所得到的圆点质心坐标编号信息，输出该圆点所在棋盘格单元的对应角点编号信息，根据圆点质心坐标编号信息、棋盘格角点编号信息及对应相机模型，通过预设标定算法求解得出标定数据。
  5. 如权利要求4所述的标定方法，其特征在于：在步骤S1中，将所述标定板放置于相机的视野范围内，利用相机在多个预设距离处进行成像处理以得到多幅包含所述标定板的标定图像。
  6. 如权利要求4所述的标定方法，其特征在于：在步骤S3中，基于棋盘格单元的基础上，将检测到符合预设要求的每个圆点连接成网格，得到所述第一二维矩阵。
  7. 如权利要求4所述的标定方法，其特征在于：在步骤S4中，基于所述第一二维矩阵的基础上，对检测符合要求的圆点的直径进行判断，若检测到的圆点为第一特征圆点，则第一二维矩阵中对应位置的数值不变，若检测到的圆点为第二特征圆点，则第一二维矩阵中对应位置的数值发生改变，从而得到所述第二二维矩阵。
  8. 如权利要求4所述的标定方法，其特征在于：在步骤S5中，将第二二维矩阵与预设的标定板编号模板矩阵进行匹配，其中，预设的标定板编号模板与用于获取标定图像的标定板尺寸相同，圆点排列方式也相同。
  9. 如权利要求8所述的标定方法，其特征在于：在步骤S5中，依次遍历第二二维矩阵，将所述第二二维矩阵与预设的标定板编号模板矩阵进行匹配，如果匹配成功，则根据预设的标定板编号模板上的圆点质心的方位信息，输出检测到的圆点质心的方位信息。
  10. 一种标定***，其特征在于：包括权利要求1所述的标定板、相机、处理器以及存储器；其中，
    所述相机用于拍摄所述标定板的标定图像；
    所述存储器用于存储执行标定方法的可执行指令；
    所述处理器用于从存储器中读取可执行指令，利用标定图像对相应的相机模型进行标定得到标定数据。
  11. 一种标定***，其特征在于：包括权利要求2所述的标定板、相机、处理器以及存储器；其中，
    所述相机用于拍摄所述标定板的标定图像；
    所述存储器用于存储执行标定方法的可执行指令；
    所述处理器用于从存储器中读取可执行指令，利用标定图像对相应的相机模型进行标定得到标定数据。
  12. 一种标定***，其特征在于：包括权利要求3所述的标定板、相机、处理器以及存储器；其中，
    所述相机用于拍摄所述标定板的标定图像；
    所述存储器用于存储执行标定方法的可执行指令；
    所述处理器用于从存储器中读取可执行指令，利用标定图像对相应的相机模型进行标定得到标定数据。
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