CN114445505A - Camera calibration system and calibration method for road surface detection - Google Patents
Camera calibration system and calibration method for road surface detection Download PDFInfo
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- CN114445505A CN114445505A CN202111631215.XA CN202111631215A CN114445505A CN 114445505 A CN114445505 A CN 114445505A CN 202111631215 A CN202111631215 A CN 202111631215A CN 114445505 A CN114445505 A CN 114445505A
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- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
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- G01N2201/127—Calibration; base line adjustment; drift compensation
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Abstract
The invention provides a camera calibration system and a calibration method for road surface detection, the camera calibration system for road surface detection comprises: the distance measurement sensor module is used for measuring the distance between the distance measurement sensor module and the ground; the two-dimensional attitude sensor module is used for detecting the inclination angle of an imaging chip of the camera relative to the ground; and the distance measuring sensor module and the two-dimensional attitude sensor module are electrically connected with the computing module. The camera calibration system for road surface detection can adjust the camera according to the actual need of road surface detection and perform real-time calibration, and has the advantages of high calibration speed, simple operation, wide application range and high engineering application value.
Description
Technical Field
The invention relates to the technical field of road surface detection, in particular to a camera calibration system and a calibration method for road surface detection.
Background
The road surface detection is a series of operations for observing and measuring road surface disease data by adopting an area-array camera to shoot road surface images. Before pavement detection, the area-array camera needs to be calibrated, and the calibration comprises internal parameter calibration and external parameter calibration, wherein the internal parameter is an internal parameter of the area-array camera and can be set by self, and the external parameter needs to be calibrated by adopting a calibration device.
At present, a checkerboard is generally adopted to shoot a plurality of pictures for calibration, but with the gradual development of road surface detection, an area-array camera gradually develops towards a non-fixed type, and after the area-array camera is moved each time, the checkerboard is required to shoot the plurality of pictures for calibration, so that the operation is very complicated, and the road surface detection efficiency is reduced.
Through the technical analysis, the prior art has the defect that the pavement detection efficiency is reduced due to very complicated operation.
Disclosure of Invention
The embodiment of the invention provides a camera calibration system and a calibration method for road surface detection, which aim to overcome the defect that the road surface detection efficiency is reduced due to very complicated operation in the prior art.
The embodiment of the invention provides a camera calibration system for road surface detection, which comprises:
the distance measurement sensor module is used for measuring the distance between the distance measurement sensor module and the ground;
the two-dimensional attitude sensor module is used for detecting the inclination angle of an imaging chip of the camera relative to the ground;
and the distance measuring sensor module and the two-dimensional attitude sensor module are electrically connected with the computing module.
The camera calibration system for road surface detection has the advantages that: when the distance measurement sensor module and the two-dimensional attitude sensor module can change along with the installation position of the camera, real-time measurement is carried out, and then the calculation module carries out real-time and quick calculation of the external parameter matrix, so that the external parameter of the camera can be conveniently calibrated at a single time and calibrated in real time, a chessboard does not need to be manually adopted to carry out complex repeated photographing calculation calibration, and the workload of manual operation is reduced. The camera calibration system for road surface detection can adjust the camera according to the actual need of road surface detection and perform real-time calibration, and has wide application range and high engineering application value.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the distance measuring sensor module is a laser distance measuring sensor or an infrared distance measuring sensor.
The beneficial effect of adopting the further scheme is that: the distance from the ground is conveniently measured.
Further, the camera calibration system for road surface detection further comprises a communication module, the communication module is used for being in electric signal connection with a controller of the camera, and the distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module are all electrically connected with the communication module.
The beneficial effect of adopting the further scheme is that: the camera controller can send commands to calibrate external parameters, so that manual operation can be performed on the camera.
Further, the communication module is a bluetooth module or a WIFI wireless communication module.
The beneficial effect of adopting the further scheme is that: facilitating the communication connection.
Another aspect of the present disclosure provides a calibration method applied to the above camera calibration system for road surface detection, including the following steps:
the distance measuring sensor module measures the distance L between the distance measuring sensor module and the ground;
the two-dimensional attitude sensor module detects and obtains the inclination angle of an imaging chip of the camera relative to the ground;
and calculating to obtain an external parameter matrix M according to the distance between the ranging sensor module and the ground and the inclination angle of the imaging chip of the camera relative to the ground.
Further, before the step of measuring the distance between the distance measuring sensor module and the ground by the distance measuring sensor module, the method further comprises the following steps:
establishing a camera coordinate system and a world coordinate system;
an origin O1 of the camera coordinate system is a focus point in the camera pinhole imaging model, a Z1 axis of the camera coordinate system is a camera optical axis, and an X1 axis and a Y1 axis of the camera coordinate system are parallel to two adjacent edges of the camera imaging chip;
the origin O2 of the world coordinate system is the intersection point of the optical axis of the camera and the road surface, the Z2 axis of the world coordinate system is the projection of the optical axis of the camera on the road surface, the X2 axis of the world coordinate system is perpendicular to the projection of the optical axis of the camera on the road surface, and the Y2 axis of the world coordinate system is parallel to the normal line of the road surface.
The beneficial effect of adopting the further scheme is that: the coordinate conversion relation between the camera coordinate system and the world coordinate system can be calculated, and the external reference calibration of the camera can be obtained.
Further, the two-dimensional attitude sensor module detects the inclination angle of the imaging chip of the camera relative to the ground, and includes:
the two-dimensional attitude sensor module measures an included angle P between an axis Z1 of the camera coordinate system and an axis Y2 of the world coordinate system;
the two-dimensional attitude sensor module measures an angle H between an X1 axis of the camera coordinate system and an X2 axis of the world coordinate system.
The beneficial effect of adopting the further scheme is that: the tilt angle of the camera mounting can be corrected.
Further, the calculating according to the distance between the ranging sensor module and the ground and the inclination angle of the imaging chip of the camera relative to the ground to obtain the external parameter matrix M includes:
obtaining a first rotation matrix Rx according to the included angle P;
obtaining a second rotation matrix Rz according to the included angle H;
calculating a rotation matrix R according to the first rotation matrix Rx and the second rotation matrix Rz;
obtaining a translation matrix t according to the distance L between the ranging sensor module and the ground;
determining a coordinate T of an origin O1 of the camera coordinate system in the world coordinate system;
and obtaining an external parameter matrix M according to the rotation matrix R and the translation matrix t.
The beneficial effect of adopting the further scheme is that: and the calculation of the external parameter matrix is facilitated.
Further, the first rotation matrix Rx is
The second rotation matrix Rz is
The rotation matrix R is R ═ RxRz；
The translation matrix t is t ═ 0-L × sin P-L × cos P ];
the external reference matrix M is
The beneficial effect of adopting the further scheme is that: the extrinsic matrix can be directly calculated.
Further, before establishing the camera coordinate system and establishing the world coordinate system, the method further includes:
receiving a calibration instruction sent by a controller of a camera;
and sending the calibration instruction to the distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module.
The beneficial effect of adopting the further scheme is that: the camera is convenient to operate directly on the camera to carry out external parameter calibration, and the operation is simpler and more convenient.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic diagram of the position relationship between a camera coordinate system and a world coordinate system according to the present invention;
FIG. 2 is a flow chart of a calibration method of the present invention;
fig. 3 is a schematic connection diagram of the camera calibration system for road surface detection according to the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
1. a camera.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 and 3, an aspect of the present disclosure provides a camera calibration system for road surface detection, including: the device comprises a distance measurement sensor module, a two-dimensional attitude sensor module and a calculation module.
The distance measuring sensor module is used for measuring the distance between the distance measuring sensor module and the ground. The two-dimensional attitude sensor module is used for detecting the inclination angle of an imaging chip of the camera relative to the ground. The distance measuring sensor module and the two-dimensional attitude sensor module are electrically connected with the computing module.
In this embodiment, the distance measuring sensor module can measure the distance between the distance measuring sensor module and the ground, and the distance measuring sensor module is installed at the axis of the shooting end of the camera, so that the measuring axis of the distance measuring sensor is parallel to or coincident with the optical axis of the camera. The two-dimensional attitude sensor module is provided with two measuring shafts, the two measuring shafts are perpendicular to each other and parallel to two adjacent edges of the imaging chip, so that the two measuring shafts can measure the inclination angles of the two adjacent edges of the imaging chip and the ground. The calculation module is used for calculating an external parameter matrix M from data obtained by measurement of the distance measurement sensor module and data obtained by measurement of the two-dimensional attitude sensor module, and the camera is calibrated through the external parameter matrix M, so that detection and analysis of the road surface condition are facilitated. The distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module are all used for being installed on the camera.
Among the above-mentioned technical scheme, when can change along with camera mounted position through range finding sensor module and two-dimensional attitude sensor module, carry out real-time measurement, the external reference matrix is gone out in real-time quick calculation to the rethread calculation module to conveniently carry out single and mark in real time to the external reference of camera, do not need the manual work to adopt the chess board to carry out the calculation of shooing complicated many times and mark, reduced manual operation's work load. The camera calibration system for road surface detection can adjust the camera according to the actual road surface detection requirement, and perform real-time calibration, and has the advantages of wide application range and high engineering application value.
Optionally, in an embodiment of the present disclosure, the distance measuring sensor module is a laser distance measuring sensor or an infrared distance measuring sensor.
In this embodiment, the laser distance measuring sensor measures distance by using laser, and the measuring end of the laser distance measuring sensor faces the ground. The infrared distance measuring sensor measures distance by adopting infrared light, and the measuring end of the infrared distance measuring sensor faces the ground. Of course, in other embodiments, the distance measuring sensor module may be other sensors capable of measuring distance.
Optionally, in an embodiment of the present disclosure, the two-dimensional attitude sensor module is a two-axis tilt angle sensor, which measures tilt angles of two adjacent edges of the imaging chip and the ground through two measurement axes respectively. Of course, in other embodiments, the two-dimensional attitude sensor module may also be other sensors capable of measuring the tilt angles of two adjacent sides of the imaging chip and the ground.
Optionally, in an embodiment of the present disclosure, the calculation module is a microprocessor, and the microprocessor is capable of implementing data calculation.
Optionally, in an embodiment of the present disclosure, the camera calibration system for road surface detection further includes a communication module, the communication module is configured to be in electrical signal connection with a controller of the camera, and the distance measurement sensor module, the two-dimensional attitude sensor module, and the calculation module are all electrically connected to the communication module.
In this embodiment, the communication module is configured to transmit a control signal, and the communication module is capable of establishing a communication link with a controller of the camera, so that the controller of the camera can send a signal to the distance measuring sensor module, the two-dimensional attitude sensor module, and the calculation module, and the distance measuring sensor module, the two-dimensional attitude sensor module, and the calculation module can perform a corresponding operation after receiving the signal. In addition, the external parameter matrix M calculated by the calculation module can also be transmitted back to the controller of the camera through the communication module, so that external parameter calibration of the camera is realized.
Optionally, in an embodiment of the present disclosure, the communication module is a bluetooth module or a WIFI wireless communication module.
In this embodiment, when the communication module is a bluetooth module, the controller of the camera can be connected to the communication module via bluetooth, so as to transmit signals in real time. When the communication module is the WIFI wireless communication module, the controller of the camera can be in WIFI wireless communication connection with the communication module, and signals can be conveniently and quickly sent.
Another aspect of the present disclosure further provides a calibration method applied to the above camera calibration system for road surface detection, including the following steps:
the distance measuring sensor module measures the distance L between the distance measuring sensor module and the ground;
the two-dimensional attitude sensor module detects and obtains the inclination angle of an imaging chip of the camera relative to the ground;
and calculating to obtain an external parameter matrix M according to the distance between the ranging sensor module and the ground and the inclination angle of the imaging chip of the camera relative to the ground.
The distance L is a linear distance between the measuring end of the distance measuring sensor module and the ground. The two-dimensional attitude sensor module is provided with two measuring shafts, the two measuring shafts are perpendicular to each other, and the two measuring shafts are parallel to two adjacent edges of the imaging chip, so that the two measuring shafts can measure the inclination angles of the two adjacent edges of the imaging chip and the ground.
Optionally, before the step of measuring, by the ranging sensor module, a distance between the ranging sensor module and the ground, the method further includes:
establishing a camera coordinate system and a world coordinate system;
an origin O1 of the camera coordinate system is a focus point in the camera pinhole imaging model, a Z1 axis of the camera coordinate system is a camera optical axis, and an X1 axis and a Y1 axis of the camera coordinate system are parallel to two adjacent edges of the camera imaging chip;
the origin O2 of the world coordinate system is the intersection point of the optical axis of the camera and the road surface, the Z2 axis of the world coordinate system is the projection of the optical axis of the camera on the road surface, the X2 axis of the world coordinate system is perpendicular to the projection of the optical axis of the camera on the road surface, and the Y2 axis of the world coordinate system is parallel to the normal line of the road surface.
The calibration of the camera external reference is the conversion relation between the camera coordinate system and the world coordinate system, namely, the external reference matrix M is obtained through calculation to facilitate the conversion between the camera coordinate system and the world coordinate system. Wherein the camera coordinate system is located on the camera and the world coordinate system is located on the ground.
Optionally, in an embodiment of the present disclosure, the detecting, by the two-dimensional attitude sensor module, an inclination angle of an imaging chip of the camera with respect to the ground includes:
the two-dimensional attitude sensor module measures an included angle P between an axis Z1 of the camera coordinate system and an axis Y2 of the world coordinate system;
the two-dimensional attitude sensor module measures an angle H between an X1 axis of the camera coordinate system and an X2 axis of the world coordinate system.
In this embodiment, due to the installation of the camera, the camera has a certain rotation angle with respect to the ground, so that two adjacent side edges of the imaging chip of the camera have a certain included angle with respect to the ground, and the camera coordinate system and the world coordinate system which are established can be converted into an included angle P between the Z1 axis of the camera coordinate system and the Y2 axis of the world coordinate system, and an included angle H between the X1 axis of the camera coordinate system and the X2 axis of the world coordinate system. The rotation angle of the camera is corrected through the measured included angle P and the measured included angle H, so that external parameters of the camera can be conveniently calibrated.
Optionally, in an embodiment of the present disclosure, the calculating, according to a distance between the ranging sensor module and the ground and an inclination angle of an imaging chip of the camera relative to the ground, to obtain an external parameter matrix M includes:
obtaining a first rotation matrix Rx according to the included angle P;
obtaining a second rotation matrix Rz according to the included angle H;
calculating a rotation matrix R according to the first rotation matrix Rx and the second rotation matrix Rz;
obtaining a translation matrix t according to the distance L between the ranging sensor module and the ground;
determining a coordinate T of an origin O1 of the camera coordinate system in the world coordinate system;
and obtaining an external parameter matrix M according to the rotation matrix R and the translation matrix t.
Optionally, in an embodiment of the present disclosure, the first rotation matrix Rx is
The second rotation matrix Rz is
The rotation matrix R is R ═ RxRz；
The translation matrix t is t ═ 0-L × sin P-L × cos P ];
the external reference matrix M is
Optionally, in an embodiment of the present disclosure, before establishing the camera coordinate system and establishing the world coordinate system, the method further includes:
the communication module receives a calibration instruction sent by a controller of the camera;
and the communication module sends the calibration instruction to the distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module.
In the embodiment, after the camera is installed, the communication module is in electrical signal connection with the controller of the camera, an operator can operate the camera to enter the external reference calibration mode, at the moment, the controller of the camera sends a calibration instruction to the communication module, and the communication module distributes the instruction to the ranging sensor module, the two-dimensional attitude sensor module and the calculation module to perform external reference calibration.
As shown in fig. 2, the calibration method of the camera calibration system for road surface detection includes the following steps:
s201, the communication module receives a calibration instruction sent by a controller of the camera.
S202, the communication module sends the calibration instruction to the distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module.
S203, establishing a camera coordinate system and a world coordinate system.
And S204, the distance measuring sensor module measures the distance L between the distance measuring sensor module and the ground.
And S2051, measuring an included angle P between the Z1 axis of the camera coordinate system and the Y2 axis of the world coordinate system.
And S2052, measuring an included angle H between an X1 axis of the camera coordinate system and an X2 axis of the world coordinate system.
And S206, calculating an external parameter matrix M.
S2061, obtaining a first rotation matrix Rx according to the included angle P,
s2062, obtaining a second rotation matrix Rz according to the included angle H,
s2063, calculating a rotation matrix R according to the first rotation matrix Rx and the second rotation matrix Rz,
R＝RxRz。
s2064, obtaining a translation matrix t according to the distance L between the ranging sensor module and the ground,
t＝[0 -L×sin P -L×cos P]；
and S2065, determining the coordinate T of the origin O1 of the camera coordinate system in the world coordinate system.
S2066, obtaining an external parameter matrix M according to the rotation matrix R and the translation matrix t,
and S207, after the external parameter matrix M is obtained through calculation by the calculation module, the external parameter matrix M is sent to the communication module and sent to a controller of the camera by the communication module, and calibration of external parameters of the camera is completed.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A camera calibration system for road surface inspection, comprising:
the distance measurement sensor module is used for measuring the distance between the distance measurement sensor module and the ground;
the two-dimensional attitude sensor module is used for detecting the inclination angle of an imaging chip of the camera relative to the ground;
and the distance measuring sensor module and the two-dimensional attitude sensor module are electrically connected with the computing module.
2. The camera calibration system for road surface detection according to claim 1, wherein the distance measurement sensor module is a laser distance measurement sensor or an infrared distance measurement sensor.
3. The camera calibration system for road surface detection as claimed in claim 1, further comprising a communication module for electrical signal connection with a controller of the camera, wherein the ranging sensor module, the two-dimensional attitude sensor module and the calculation module are all electrically connected with the communication module.
4. The camera calibration system for road surface detection according to claim 3, wherein the communication module is a Bluetooth module or a WIFI wireless communication module.
5. A calibration method applied to the camera calibration system for road surface inspection according to any one of claims 1 to 4, characterized by comprising the steps of:
the distance measuring sensor module measures the distance L between the distance measuring sensor module and the ground;
the two-dimensional attitude sensor module detects and obtains the inclination angle of an imaging chip of the camera relative to the ground;
and calculating to obtain an external parameter matrix M according to the distance between the ranging sensor module and the ground and the inclination angle of the imaging chip of the camera relative to the ground.
6. The calibration method according to claim 5, wherein before the step of measuring the distance between the ranging sensor module and the ground by the ranging sensor module, the calibration method further comprises:
establishing a camera coordinate system and a world coordinate system;
an origin O1 of the camera coordinate system is a focus point in the camera pinhole imaging model, a Z1 axis of the camera coordinate system is a camera optical axis, and an X1 axis and a Y1 axis of the camera coordinate system are parallel to two adjacent edges of the camera imaging chip;
the origin O2 of the world coordinate system is the intersection point of the optical axis of the camera and the road surface, the Z2 axis of the world coordinate system is the projection of the optical axis of the camera on the road surface, the X2 axis of the world coordinate system is perpendicular to the projection of the optical axis of the camera on the road surface, and the Y2 axis of the world coordinate system is parallel to the normal line of the road surface.
7. The calibration method according to claim 6, wherein the detecting of the two-dimensional attitude sensor module to obtain the inclination angle of the imaging chip of the camera with respect to the ground includes:
the two-dimensional attitude sensor module measures an included angle P between an axis Z1 of the camera coordinate system and an axis Y2 of the world coordinate system;
the two-dimensional attitude sensor module measures an angle H between an X1 axis of the camera coordinate system and an X2 axis of the world coordinate system.
8. The calibration method according to claim 7, wherein the calculating an external parameter matrix M according to the distance between the ranging sensor module and the ground and the inclination angle of the imaging chip of the camera relative to the ground includes:
obtaining a first rotation matrix Rx according to the included angle P;
obtaining a second rotation matrix Rz according to the included angle H;
calculating a rotation matrix R according to the first rotation matrix Rx and the second rotation matrix Rz;
obtaining a translation matrix t according to the distance L between the ranging sensor module and the ground;
determining a coordinate T of an origin O1 of the camera coordinate system in the world coordinate system;
and obtaining an external parameter matrix M according to the rotation matrix R and the translation matrix t.
9. Calibration method according to claim 8, wherein the first rotation matrix Rx is
The second rotation matrix Rz is
The rotation matrix R is R ═ RxRz；
The translation matrix t is t ═ 0-L × sinP-L × cosP ];
the external reference matrix M is
10. The calibration method according to claim 6, further comprising, before establishing the camera coordinate system and establishing the world coordinate system:
receiving a calibration instruction sent by a controller of a camera;
and sending the calibration instruction to the distance measurement sensor module, the two-dimensional attitude sensor module and the calculation module.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111631215.XA CN114445505A (en) | 2021-12-28 | 2021-12-28 | Camera calibration system and calibration method for road surface detection |
| PCT/CN2022/072384 WO2023123574A1 (en) | 2021-12-28 | 2022-01-17 | Camera calibration system for pavement detection, and calibration method |
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| CN202111631215.XA CN114445505A (en) | 2021-12-28 | 2021-12-28 | Camera calibration system and calibration method for road surface detection |
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| KR101271639B1 (en) * | 2011-12-13 | 2013-06-17 | (주)팜비젼 | A extrinsic parameter calibration method and system for camera on mobile device |
| CN106127787B (en) * | 2016-07-01 | 2019-04-02 | 北京美讯美通信息科技有限公司 | A kind of camera calibration method based on Inverse projection |
| CN106558080B (en) * | 2016-11-14 | 2020-04-24 | 天津津航技术物理研究所 | Monocular camera external parameter online calibration method |
| CN109859278B (en) * | 2019-01-24 | 2023-09-01 | 惠州市德赛西威汽车电子股份有限公司 | Calibration method and calibration system for camera external parameters of vehicle-mounted camera system |
| CN112308930B (en) * | 2020-10-30 | 2023-10-10 | 杭州海康威视数字技术股份有限公司 | Camera external parameter calibration method, system and device |
| CN113686314B (en) * | 2021-07-28 | 2024-02-27 | 武汉科技大学 | Monocular water surface target segmentation and monocular distance measurement method for shipborne camera |
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