CN113379829A - Camera-based dimension measurement method, device, equipment and storage medium - Google Patents
Camera-based dimension measurement method, device, equipment and storage medium Download PDFInfo
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- 230000005540 biological transmission Effects 0.000 claims description 3
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- G06T7/85—Stereo camera calibration
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Abstract
The invention discloses a camera-based size measurement method, a camera-based size measurement device, equipment and a storage medium. According to the invention, the two cameras respectively acquire the gray-scale images and the point cloud data, the rotation matrix and the translation matrix between the two cameras are obtained according to the gray-scale images and the point cloud data respectively acquired by the two cameras, the calibration between the two cameras is completed, and the cargo size information is calculated based on the rotation matrix and the translation matrix. The algorithm of the invention has wide adaptability, can measure various irregular goods, can measure the size of the goods without dead angles, can finish the camera calibration between two cameras by one-time shooting, has small calibration error, and has reliable robustness and higher accuracy.
Description
Technical Field
The invention relates to the field of machine vision, in particular to a camera-based dimension measuring method, device, equipment and storage medium.
Background
With the proposal of industrial 4.0 and intelligent manufacturing, the industrial field is continuously developed from the traditional manufacturing industry to digitalization, intellectualization and unmanned direction, in the era that all things can be intelligent, the unmanned direction continuously impacts our eyes, the demand of unmanned application in the intelligent warehousing industry is larger and larger, the warehouse management tends to be unmanned more and more, and the measurement of goods size plays an important role in the warehouse management.
At present, some methods for intelligently measuring the size of the goods exist in the market, but most methods are based on the measurement method of the small goods. There are also methods for measuring the size of large goods, but the structure is complex, the robustness effect is not sufficient, and the size measurement of irregular goods cannot be satisfied.
Disclosure of Invention
Aiming at the problems that the intelligent cargo size measuring method in the prior art is complex in structure and cannot meet the size measurement of irregular cargos, the invention provides the camera-based size measuring method, the camera-based size measuring device, the camera-based size measuring equipment and the storage medium, the gray level images and the point cloud data of the two cameras are calculated and processed to obtain cargo size information, the algorithm adaptability is wide, and various irregular cargos can be measured.
To achieve the above object, the present invention provides a camera-based dimension measuring method, comprising the steps of:
two cameras respectively acquire a gray scale image and point cloud data;
obtaining a rotation matrix and a translation matrix between the two cameras according to the gray-scale image and the point cloud data respectively acquired by the two cameras, and completing calibration between the two cameras;
and calculating cargo size information based on the rotation matrix and the translation matrix.
Further, before the step of acquiring the gray-scale image and the point cloud data by the two cameras respectively, the method further comprises the following steps:
the two cameras are arranged on the diagonal line of the goods.
Further, the step of obtaining a rotation matrix and a translation matrix between the two cameras according to the gray-scale map and the point cloud data respectively acquired by the two cameras, and completing calibration between the two cameras specifically includes:
according to the gray-scale image and the point cloud data which are respectively collected by the two cameras, data matching is carried out on the gray-scale image by adopting a checkerboard, and a two-dimensional data point set is obtained;
calculating to obtain a checkerboard corner three-dimensional coordinate based on the two-dimensional data point set;
and solving the rotation matrix and the translation matrix between the two cameras according to the three-dimensional coordinates of the checkerboard corner points, and completing the calibration between the two cameras.
Further, the step of calculating a three-dimensional coordinate of a checkerboard corner point based on the two-dimensional data point set specifically includes:
respectively fitting the point cloud data respectively acquired by the two cameras to obtain a calibration plate plane equation of the checkerboard under the two camera coordinate systems;
calculating to obtain a three-dimensional coordinate X value and a three-dimensional coordinate Y value of a checkerboard corner point according to the two-dimensional data point set on the checkerboard;
and solving a Z value through a calibration plate plane equation of the checkerboard based on the X value and the Y value to obtain the three-dimensional coordinates of the checkerboard angular points.
Further, the step of calculating a three-dimensional coordinate X value and a three-dimensional coordinate Y value of a corner point of the checkerboard according to the two-dimensional data point set on the checkerboard specifically includes:
establishing an image plane coordinate system according to the gray level image and the point cloud data acquired by the two cameras respectively;
obtaining a homography matrix H according to the coordinate X value and the coordinate Y value of the three-dimensional data point set corresponding to the two-dimensional data point set coordinate of the calibration plate on the image in the image plane coordinate system;
and obtaining a three-dimensional coordinate X value and a three-dimensional coordinate Y value corresponding to the checkerboard corner points according to the corner point coordinates of the checkerboard in the image plane coordinate system and the homography matrix H.
Further, before the step of calculating cargo size information based on the rotation matrix and the translation matrix, the method further includes:
and respectively collecting the point cloud data of the two cameras according to the rotation matrix and the translation matrix for splicing to obtain spliced point cloud data, and solving a ground normal vector according to the spliced point cloud data.
Further, the step of calculating cargo size information based on the rotation matrix and the translation matrix specifically includes:
respectively solving homography matrixes between vertical downward shooting and images of the two cameras on the basis of the rotation matrix, the translation matrix and the ground normal vector;
performing transmission transformation according to the homography matrix to obtain corrected image information;
furthermore, to achieve the above object, the present invention also proposes a camera-based dimension measuring apparatus, comprising:
the two cameras respectively acquire a gray scale image and point cloud data;
the camera calibration module is used for solving a rotation matrix and a translation matrix between the two cameras according to the gray-scale images and the point cloud data which are respectively collected by the two cameras and completing calibration between the two cameras;
and the size calculation module is used for calculating cargo size information based on the rotation matrix and the translation matrix.
Furthermore, to achieve the above object, the present invention also proposes a camera-based dimension measuring apparatus, comprising: a structured light camera, a memory, a processor and a camera-based sizing program stored on the memory and executable on the processor, the camera-based sizing program being configured to implement the steps of the camera-based sizing method according to any of claims 1 to 7.
Further, to achieve the above object, the present invention also proposes a storage medium having stored thereon a camera-based dimension measuring program which, when executed by a processor, implements the steps of the camera-based dimension measuring method according to any one of claims 1 to 7.
The invention has the beneficial effects that: according to the invention, the two cameras respectively acquire the gray-scale images and the point cloud data, the rotation matrix and the translation matrix between the two cameras are obtained according to the gray-scale images and the point cloud data respectively acquired by the two cameras, the calibration between the two cameras is completed, and the cargo size information is calculated based on the rotation matrix and the translation matrix. The algorithm of the invention has wide adaptability, can measure various irregular goods, can measure the size of the goods without dead angles, can finish the camera calibration between two cameras by one-time shooting, has small calibration error, and has reliable robustness and higher accuracy.
Drawings
FIG. 1 is a schematic flow chart of a camera-based dimensional measurement method provided by the present invention;
FIG. 2 is a camera building architecture diagram of a camera-based dimensional measurement device provided by the present invention;
FIG. 3 is a block diagram of a camera-based dimension measuring device provided by the present invention;
fig. 4 is a schematic structural diagram of a camera-based dimension measuring apparatus provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the method for measuring a dimension based on a camera according to the present invention includes the following steps:
s10: two cameras respectively acquire a gray scale image and point cloud data;
s20: obtaining a rotation matrix and a translation matrix between the two cameras according to the gray-scale image and the point cloud data respectively acquired by the two cameras, and completing calibration between the two cameras;
s30: and calculating cargo size information based on the rotation matrix and the translation matrix.
The invention is further illustrated by the following specific examples;
referring to fig. 2, two cameras of the present invention are disposed on diagonal lines of the cargo, and other angles may be selected to perform the calibration only by shooting, which is slightly poor in calibration accuracy.
The method comprises the steps of respectively acquiring a gray-scale image and point cloud data through two cameras, acquiring the gray-scale image and the point cloud data at one time, performing data matching on the gray-scale image by adopting a checkerboard according to the gray-scale image and the point cloud data acquired by the two cameras, performing checkerboard searching and matching on the gray-scale image of the two cameras to obtain a two-dimensional data point set, calculating the two-dimensional data point set to obtain a checkerboard corner point three-dimensional coordinate, and obtaining a rotation matrix and a translation matrix between the two cameras according to the checkerboard corner point three-dimensional coordinate, namely completing camera calibration between the two cameras.
It should be noted that, the three-dimensional coordinates of the corner points of the checkerboard calculated from the two-dimensional data point set may also adopt an interpolation algorithm, and the point error obtained by interpolation is large, which may affect the final calibration result and has a slightly poor use effect. Preferably, the planar equation of the checkerboard calibration plate under two camera coordinate systems is obtained by respectively fitting point cloud data respectively collected by two cameras, the X value and the Y value of the three-dimensional coordinate of the checkerboard corner point are obtained by calculating the X value and the Y value of the coordinate of the three-dimensional data point set corresponding to the two-dimensional data point set, the image planar coordinate system is established according to the gray scale image and the point cloud data respectively collected by the two cameras, the homography matrix H is obtained according to the X value and the Y value of the three-dimensional data point set corresponding to the coordinate of the two-dimensional data point set of the calibration plate on the image in the image planar coordinate system, the X value and the Y value of the three-dimensional coordinate of the corner point of the corresponding checkerboard are obtained according to the corner point coordinate of the checkerboard in the image planar coordinate system and the homography matrix H, the Z value is obtained by the planar equation of the checkerboard calibration plate based on the X value and the Y value, and obtaining a three-dimensional data point set, and obtaining a rotation matrix and a translation matrix between the two cameras according to the three-dimensional data point set, namely completing the calibration of the cameras between the two cameras. The three-dimensional coordinate of the calibration plate corresponding to the two-dimensional coordinate of the calibration plate on the image is known, the error is large, and the accurate three-dimensional coordinate can be obtained through the calculation.
Before the cargo size information is obtained through calculation of a rotation matrix and a translation matrix, point cloud data acquired by two cameras are spliced according to the rotation matrix and the translation matrix to obtain spliced point cloud data, a ground normal vector is obtained according to the spliced point cloud data, homography matrixes between vertical downward shooting and images of the two cameras are obtained according to the rotation matrix, the translation matrix and the ground normal vector, corrected image information is obtained through transmission transformation according to the homography matrixes, the image information is mapped to a plane where the ground normal vector is located to obtain cargo size information, the position where the cargo is located can be determined through a depth learning algorithm to remove surrounding point cloud interference, then corresponding 3D coordinates are checked according to the removed point cloud data to obtain the cargo height, and obtaining the minimum external rectangle, namely obtaining the minimum external rectangular body.
Referring to fig. 3, an embodiment of the present invention further provides a camera-based dimension measuring apparatus, including:
a point cloud acquisition module 21, wherein two cameras respectively acquire a gray scale image and point cloud data;
the camera calibration module 22 is used for solving a rotation matrix and a translation matrix between the two cameras according to the gray-scale images and the point cloud data respectively acquired by the two cameras and completing calibration between the two cameras;
and the size calculation module 23 is used for calculating cargo size information based on the rotation matrix and the translation matrix.
Referring to fig. 4, an embodiment of the present invention further provides a camera-based dimension measuring apparatus, including: a structured light camera 33, a memory 32, a processor 31 and a camera-based sizing program stored on said memory 32 and executable on said processor 31, the camera-based sizing program being configured to implement the steps of the camera-based sizing method as described above.
Furthermore, an embodiment of the present invention further provides a storage medium, on which a camera-based dimension measurement program is stored, which when executed by a processor implements the steps of the camera-based dimension measurement method as described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A camera-based dimensional measurement method, characterized in that it comprises the steps of:
two cameras respectively acquire a gray scale image and point cloud data;
obtaining a rotation matrix and a translation matrix between the two cameras according to the gray-scale image and the point cloud data respectively acquired by the two cameras, and completing calibration between the two cameras;
and calculating cargo size information based on the rotation matrix and the translation matrix.
2. The camera-based dimensional measurement method of claim 1, wherein the step of acquiring the grayscale map and the point cloud data by the two cameras further comprises:
the two cameras are arranged on the diagonal line of the goods.
3. The camera-based dimension measuring method according to claim 1, wherein the step of obtaining a rotation matrix and a translation matrix between the two cameras according to the gray scale map and the point cloud data respectively acquired by the two cameras and completing calibration between the two cameras comprises:
according to the gray-scale image and the point cloud data which are respectively collected by the two cameras, data matching is carried out on the gray-scale image by adopting a checkerboard, and a two-dimensional data point set is obtained;
calculating to obtain a checkerboard corner three-dimensional coordinate based on the two-dimensional data point set;
and solving the rotation matrix and the translation matrix between the two cameras according to the three-dimensional coordinates of the checkerboard corner points, and completing the calibration between the two cameras.
4. The camera-based dimensional measurement method of claim 3, wherein the step of calculating three-dimensional coordinates of checkerboard corner points based on the set of two-dimensional data points comprises:
respectively fitting the point cloud data respectively acquired by the two cameras to obtain a calibration plate plane equation of the checkerboard under the two camera coordinate systems;
calculating to obtain a three-dimensional coordinate X value and a three-dimensional coordinate Y value of a checkerboard corner point according to the two-dimensional data point set on the checkerboard;
and solving a Z value through a calibration plate plane equation of the checkerboard based on the X value and the Y value to obtain the three-dimensional coordinates of the checkerboard angular points.
5. The camera-based dimensional measurement method of claim 4, wherein the step of calculating three-dimensional coordinates X and Y of checkerboard corner points from the set of two-dimensional data points on the checkerboard comprises:
establishing an image plane coordinate system according to the gray level image and the point cloud data acquired by the two cameras respectively;
obtaining a homography matrix H according to the coordinate X value and the coordinate Y value of the three-dimensional data point set corresponding to the two-dimensional data point set coordinate of the calibration plate on the image in the image plane coordinate system;
and obtaining a three-dimensional coordinate X value and a three-dimensional coordinate Y value corresponding to the checkerboard corner points according to the corner point coordinates of the checkerboard in the image plane coordinate system and the homography matrix H.
6. The camera-based dimensional measurement method of claim 1, wherein said step of calculating cargo dimension information based on said rotation matrix and said translation matrix is preceded by the step of:
and respectively collecting the point cloud data of the two cameras according to the rotation matrix and the translation matrix for splicing to obtain spliced point cloud data, and solving a ground normal vector according to the spliced point cloud data.
7. The camera-based dimensional measurement method of claim 6, wherein the step of calculating cargo dimensional information based on the rotation matrix and the translation matrix comprises:
respectively solving homography matrixes between vertical downward shooting and images of the two cameras on the basis of the rotation matrix, the translation matrix and the ground normal vector;
performing transmission transformation according to the homography matrix to obtain corrected image information;
and mapping the image information to a plane where the ground normal vector is located to obtain the cargo size information.
8. A camera-based dimensional measurement device, the device comprising:
the two cameras respectively acquire a gray scale image and point cloud data;
the camera calibration module is used for solving a rotation matrix and a translation matrix between the two cameras according to the gray-scale images and the point cloud data which are respectively collected by the two cameras and completing calibration between the two cameras;
and the size calculation module is used for calculating cargo size information based on the rotation matrix and the translation matrix.
9. A camera-based dimensional measurement device, characterized in that the device comprises: a structured light camera, a memory, a processor and a camera-based sizing program stored on the memory and executable on the processor, the camera-based sizing program being configured to implement the steps of the camera-based sizing method according to any of claims 1 to 7.
10. Storage medium, characterized in that the storage medium has stored thereon a camera-based sizing program which, when executed by a processor, carries out the steps of the camera-based sizing method according to any one of claims 1 to 7.
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