CN103077639B - Curve driving detection system and detection method thereof - Google Patents
Curve driving detection system and detection method thereof Download PDFInfo
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Abstract
The invention discloses a curve driving detection system and a detection method thereof, wherein the curve driving detection system comprises a mark plate, a camera, an image analyzer, a transmission network, a server and a client; the detection method comprises the steps that an image of the camera is firstly recorded, a curve corner and the physical size of a training vehicle are manually measured, and the calibrating of a coordinate system is finished; the image analyzer continuously receives monitoring images captured by the camera and identifies the mark plate on the training vehicle, the actual position, gesture and contour range of the vehicle and the shortest distance from the contour to a marker line are calculated through the calibrated coordinate system, and pictures are snapshot when the contour of the vehicle crosses the marker line; and the server receives the measurement data, pictures and video from the image analyzer through the transmission network and works out the training score, and a driver and a trainer can query the information or retrieve the video through a back-end client, so that the driver can be effectively trained, and the learning efficiency of the driving personnel is improved.
Description
Technical field
The present invention relates to a kind of curve driving detection system and detection method thereof.
Background technology
As automobile driver, curve driving is one of driving efficiency that must skillfully grasp.But during traditional driver training, student generally trains with fixed reference, need after causing actual setting out on a journey again to cultivate position sense and turning skill.Although can by installing the sensor collection vehicle position of some on road surface, as Chinese utility model 201120277850.8 the permanent magnet that adopts, or engineering range finding upper conventional infrared ray, laser, ultrasound wave etc., but sensors with auxiliary electrode all can only perception on indivedual point of fixity position, construction, maintenance complexity, overall cost is also expensive, and still needs linkage camera could realize evidence obtaining.
No matter student learns or trainer's teaching, and be all mainly that view-based access control model information judges again, it is also the most received for therefore carrying out detection mode based on machine vision to the whole dynamic process of curve driving.
Although China's utility model 201120489062.5 describes a kind of video detecting device of the straight line distance for examination of driver, but its core is: " image obtained is mapped to HSV and LAB color space by graphics processing unit respectively; and in each spatial threshold value; form straight line pixel; pixel comparing unit uses principle of probability; input pixel is added up, draw the straight line unit meeting right side bearing feature most, calculate the rightmargin of this straight line unit ".Total institute is known, this mode is difficult to possess operability under actual environment, because there are many straight line pixels in vehicle self, as vehicle window, ceiling etc., also often there is a large amount of straight line pixel in background environment simultaneously, as kerbstone, flowers, plants and trees etc., in this case, be difficult in pixel aspect, " car " be extracted from background environment, finally cause detection inaccurate.
Summary of the invention
The object of the invention is to provide a kind of curve driving detection system and detection method thereof, and it can realize the quantitative test carried out training cart in curve driving process, is conducive to Real-Time Monitoring and the tracking of training result.
In order to solve these problems of the prior art, technical scheme provided by the invention is:
A kind of curve driving detection system, it comprises the front end system be arranged near curve driving position and the back-end system being deployed in administrative center, described front end system comprises multiple stage main camera, image analyzer and the sign board be placed on training cart, back-end system comprises server and client, front end system connects back-end system by transmission network, monitored picture covering curve travels the main camera in region, position for shooting with video-corder the travel conditions of warehouse compartment place training cart, the monitoring image that the image analyzer continuous reception main camera be connected with main camera is caught also is compressed into monitoring image, the operation attitude of image analyzer monitor vehicle simultaneously, monitoring result and monitoring image are sent to the server of back-end system by image analyzer, client can be called and check monitoring result in server and monitoring image.
As optimization, described multiple stage main camera is fixed in the vertical rod above curve driving position, respectively can overlook curve bend one section of camber line region.
As optimization, be also provided with auxiliary camera in the both sides of every platform main camera, supplement for auxiliary the running orbit catching training cart in warehouse compartment.
As optimization, described notice plate is arranged on roof, engine top cover or case cover, and the marker graphic on described notice plate is some gauge points, and gauge point is arranged in the specific line segment with fixed angle and unique intersection point.
As optimization, the seat in the plane of main camera, auxiliary camera is other is equipped with light compensating lamp, and the synchronizing signal of described light compensating lamp is provided by main camera or auxiliary camera, for carrying out strobe type light filling when illumination is crossed dark.
Present invention also offers a kind of curve driving detection method, described method relates to system and comprises the front end system be arranged near curve driving position and the back-end system being deployed in administrative center, described front end system comprises multiple stage main camera, auxiliary camera, image analyzer and the sign board be placed on training cart, back-end system comprises server and client, front end system connects back-end system by transmission network, monitored picture covers the main camera in warehouse compartment region for shooting with video-corder the travel conditions of warehouse compartment place training cart, image analyzer and main camera, auxiliary camera is connected, concrete detection method comprises the following steps:
Step S1: measure warehouse compartment length and width size by direct labor, runs camera calibration program, realizes the mutual conversion of image coordinate system and world coordinate system;
Step S2: the monitoring image that image analyzer continuous reception main camera is caught, is compressed into video record, simultaneously running mark board recognizer, obtains position and the direction of sign board;
Step S3: image analyzer is according to camera calibration result and sign board recognition result, and operational vehicle position and attitude trace routine, obtains position and the attitude of vehicle; In conjunction with known vehicle dimension, and then determine vehicle ' s contour scope and the profile outer edge bee-line to lane line, and trigger main camera when vehicle line ball or auxiliary camera captures picture; When the sign board of image analyzer identification disappears from the specific region of image, judge that vehicle sails out of corresponding main camera overlay area, image analyzer, by metrical informations such as segmentation used times, is all sent to server together with candid photograph picture, video record;
Step S4: after server receives the metrical information that each image analyzer sends, runs scoring procedures, obtains this curve driving comprehensive grading;
Step S5: student or trainer, by client-access server, browse, download and print curve driving relevant scoring, capture picture and video record.
For above-mentioned detection method, inventor also has further optimal enforcement scheme equally.
As optimization, in step S3, trigger main camera 1 or auxiliary camera 2 when vehicle line ball or distance are less than setting threshold value in docking process and capture picture and be sent to image analyzer.
As optimization, in step S 1, when carrying out camera calibration, (coordinate system of the real world at world coordinate system and vehicle place, by 3 coordinate axis: X-axis, Y-axis, Z axis form, the plane picture of image coordinate system and shot by camera, by 2 coordinate axis: U axle, V axle form), in step S1, when carrying out camera calibration, the step of described camera calibration program is:
Video capture piece image, with any pixel for image coordinate system initial point, hand labeled goes out the image coordinate of four the lane boundary line endpoints in this section of curve bend section;
The physical location point at marking image coordinate origin place, and as world coordinate system initial point, the world coordinates of lane line four end points in actual place, experiment curv bend section;
The world coordinates on four warehouse compartment summits and pixel coordinate are substituted into image-world coordinates transform in system of linear equations, solve image-world coordinates transformed matrix;
Certain point coordinate value under any one world coordinate system is substituted into image-world coordinates transformed matrix known image-world coordinates and transform system of linear equations, the image coordinate of this some correspondence can be calculated;
Under the prerequisite of the known world coordinate height, any one image coordinate is substituted into image-world coordinates transformed matrix known image-world coordinates and transform system of linear equations, the world coordinates of this some correspondence can be calculated; So far, camera calibration is completed.
As optimization, the flow process of carrying out sign board identification in step S2 is as follows:
Threshold segmentation is carried out to image, obtains the image after segmentation;
Connected domain extraction is carried out to the image after Threshold segmentation, judges whether connected domain length and width meets the length and width setting value of sign board gauge point figure, if met, then mark this connected domain;
Can the connected domain of judge mark connect into the shape consistent with real marking board one by one, comprises angle formed by gauge point quantity and gauge point line, if passable, be then reference points detection figure depending on connected region, otherwise give up this connected domain; Repeat this step, until travel through all connected domains;
With reference points detection figure for reference point, identify other additional letter and numeric area and identify, so far completing the identification of whole sign board.
The steps flow chart carrying out vehicle location attitude detection in this detection method in step S3 is:
Image-world coordinates that the image coordinate of the reference points detection figure obtained in sign board recognizer substitutes into camera calibration program is transformed in system of linear equations, the world coordinates of reference points detection figure can be obtained;
In world coordinate system, reference points detection figure is linked to be according to the queueing discipline of sign board mark original tally dot pattern the line segment that there is intersection point;
In world coordinate system, calculate the coordinate of intersection point and the angle of line segment, intersecting point coordinate is vehicle location, and line segment angle is vehicle attitude.
Relative to scheme of the prior art, advantage of the present invention is:
1. the invention describes a kind of curve driving detection system and detection method thereof, system comprises sign board, video camera, image analyzer, transmission network, server and client side; Detection method: first record camera views, the physical size of manual measurement curve bend, training cart, completes coordinate system and demarcates; The monitoring image that image analyzer continuous reception video camera is caught sign board on recognition training car, extrapolate the physical location of vehicle, attitude, profile and the profile bee-line to mark line by the coordinate system demarcated, and capture picture when vehicle ' s contour crosses over mark line; Server receives from the measurement data of image analyzer and picture, video by transmission network, and calculate training scoring, driver and trainer to be inquired about information by the client of rear end or have access to video record, realization like this, to effective training of driver, improves the learning efficiency of driving training personnel;
2. the present invention is completely based on video technique, does not need ground on the scene to bury other sensor underground, does not also need to increase any electric apparatus mounted on vehicle, and structure is simple, with low cost;
3. the present invention is directly based on video technique, supports to capture the picture of the abnormal conditions such as line ball, and evidence obtaining is convenient.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the invention will be further described:
Fig. 1 is the system architecture schematic diagram of the embodiment of the present invention;
Fig. 2 is the sign board schematic diagram of the embodiment of the present invention;
Fig. 3 is the overall system workflow diagram of the embodiment of the present invention;
Fig. 4 is the camera calibration program flow diagram of the embodiment of the present invention;
Fig. 5 is the sign board recognizer process flow diagram of the embodiment of the present invention;
Fig. 6 is the vehicle location attitude detection process flow diagram of the embodiment of the present invention;
Fig. 7 is the scoring procedures process flow diagram of the embodiment of the present invention.
Wherein: 1, main camera; 2, auxiliary camera; 3, light compensating lamp; 4, image analyzer; 5, sign board; 6, transmission network; 7, server; 8, client.
Embodiment
Embodiment:
Present embodiment describes a kind of curve driving detection system and detection method thereof, as shown in Figure 1, system is made up of the front end system be arranged near curved road and the back-end system being deployed in administrative center system architecture.Front end system mainly contains: main camera 1, auxiliary camera 2, light compensating lamp 3, image analyzer 4 and the sign board 5 be placed on training cart; Back-end system mainly contains: server 7, client 8; Front and back ends system is interconnected by transmission network 6.
Curve bend is made up of the semicircle bend of two 180 degree, take into account saving lower deployment cost to obtain good monitoring effect simultaneously, three main cameras 1 are installed on three sections before, during and after curved road respectively, 135 degree of regions of leading portion main camera 1 covering curve bend first semicircle, stage casing main camera 1 covering curve bend first semicircle residue 45 degree and second semicircle, 45 degree of regions, back segment main camera 1 covering curve bend second semicircle residue 135 degree of regions.Main camera 1 is installed on the vertical rod transverse arm of about 4-8 rice above road, and be on road axis, setting angle needs to guarantee that the lane line of covered local curve road is continuous print in picture, and namely two lane lines and image border respectively exist two intersection points.Main camera 1 adopts the wide temperature design of technical grade, sensor adopts 5,000,000 CCD, resolution is greater than 2592x1936, frame per second is not less than 8 frames/second, built-in gigabit ethernet interface, be equipped with 10mm ~ 35mm many moneys tight shot or zoom wide-angle lens simultaneously, effectively can ensure that monitored picture at least covers the curved areas of 8m x 6m under above-mentioned mounting condition like this, and guarantee that sign board pixels across width is no less than 500 pixels.Auxiliary camera 2 can be installed on the same vertical rod transverse arm of main camera 1, particular location is the outer 0.2-1 rice of left and right lane line, auxiliary camera adopts the wide temperature design of technical grade, sensor adopts 2,000,000 CCD, resolution is greater than 1920x1080, and frame per second is not less than 8 frames/second, built-in gigabit ethernet interface, be equipped with 10mm ~ 25mm many moneys tight shot or zoom lens simultaneously, can effective monitoring wheel line ball under effectively ensureing above-mentioned mounting condition like this.
Light compensating lamp 3 adopts strobe type LED light supplement lamp, and what synchronizing signal was provided by main camera 1 is main light compensating lamp, and what synchronizing signal was provided by auxiliary camera is auxiliary light compensating lamp.Light compensating lamp 3 power and visible angle are determined according to installation site.For avoiding vehicle body reflection to cause video camera overexposure, light compensating lamp 3 should keep at a certain distance away with its synchronous video camera of control and install, and is generally not less than 0.5 meter.When light compensating lamp 2 setting height(from bottom) is 6 meters, when distance parking stall central horizontal distance is 6 meters, visible angle is not less than 40 degree, and power is not less than 15W, and video camera interval 1 meter ampere fills and can satisfy the demands.
Image analyzer 4 adopts built-in industrial control computer, and the integrated heat-dissipating casing of its shell, does not need radiator fan, and effectively the inner laying dust of control, improves system stability; When the ccd video camera of connection 5,000,000 pixel, require that configuration dominant frequency is not less than the CPU of 2.4GHz, be no less than the internal memory of 4GB, be no less than the hard disk of 32GB as external memory and the hardware interface such as gigabit Ethernet, RS232, above-mentioned configuration guarantees that image analyzer 4 has enough calculating, storage and the communication resource to run all kinds of image processing algorithm and application program.
Server 7 can adopt tower server, and select dominant frequency to be greater than four core processors of 2.8GHz, 8MB buffer memory, internal memory is not less than 4GB, to ensure still can ensure system responses real-time when disposing multiple stage image analyzer 4.
Client 8 is common PC, can be equipped with the peripherals such as printer, IC-card card reader or fingerprint capturer.
Transmission network 6 adopts optical fiber or 3G cordless communication network when cross-over connection front and back ends system, and front and back ends system this locality adopts the gigabit Ethernet based on twisted-pair feeder more.
Main camera 1, auxiliary camera 2, image analyzer 4, server 7, client 8 realize exchanges data by transmission network 6.
As shown in Figure 2, sign board 5 schematic diagram of the present invention is made up of three parts: gauge point figure, driving school's code name character, training cart numbering character: the gauge point figure clear and definite indicating signboard position of necessary energy and direction, as adopted T-shaped mark, and its horizontal line segment is made up of 5 black circle diagram shapes of white background, vertical line segment is made up of 3 white with black circle diagram shapes, horizontal line segment and longitudinal line segment after extracting by figure binaryzation, connected domain can be distinguished easily and identify, horizontal line segment and longitudinal line segment exist vertical angle; Driving school's code name character adopts two English alphabets, and as available in " Hua Feng driving school " " HF " refers to; Training cart numbering character adopts three arabic numeral.
Overall system workflow diagram of the present invention as shown in Figure 3:
Step S1: by direct labor's experiment curv road dimensions, runs camera calibration program, realizes the mutual conversion of image coordinate system and world coordinate system;
Step S2: the monitoring image that image analyzer 4 continuous reception main camera 1 is caught, is compressed into video record, simultaneously running mark board recognizer, obtains position and the direction of sign board 5;
Step S3: image analyzer 4 is according to main camera 1 calibration result and sign board 5 recognition result, and operational vehicle position and attitude trace routine, obtains the position in vehicle world coordinate system and attitude; According to vehicle location, attitude and known vehicle dimension, determine vehicle ' s contour position and the profile outer edge bee-line to lane line, and trigger main camera 1 when vehicle line ball or distance are less than setting threshold value or auxiliary camera 2 captures picture.
Step S4: the vehicle location obtained in step S3, attitude, range measurement and data such as candid photograph picture, video record etc. are sent to server 7 by transmission network 6 by image analyzer 4, server 7 service data supervisory routine is analyzed various information and is provided the application data such as comprehensive grading, project used time, in the mode of data record stored in database, by picture, video stored in specified file path, run application services support, administrative client access simultaneously.
Step S5: student's operated client 8, by transmission network 6 logon server 7, browses the information such as data record, picture, video that training is relevant, and according to demand printing, Download Info; Trainer's operated client 8, by transmission network 6 logon server 7, browse the information such as data record, picture, video of teaching person, and print according to demand, Download Info.
The object of camera calibration is the corresponding relation calculating world coordinate system and image coordinate system, the coordinate system of the real world at world coordinate system and vehicle place, by 3 coordinate axis: X-axis, Y-axis, Z axis form, the plane picture of image coordinate system and shot by camera, by 2 coordinate axis: U axle, V axle form.Suppose that the coordinate that certain is put in world coordinate system X, Y, Z tri-coordinate axis is (x
w, y
w, z
w), its corresponding point coordinate in image coordinate system is (u, v), then the corresponding relation of this two point coordinate can be expressed as system of linear equations:
This system of equations is called " image-world coordinates transforms system of linear equations ", and wherein α is the intermediate parameters of computation process, and (u, v) is image pixel coordinates, (x
w, y
w, z
w) be world coordinates, (f
x, f
y) be respectively the focal length of X-axis and Y direction in image coordinate system, (u
0, v
0) be the position of intersection point in image coordinate of camera optical axis and the plane of delineation.T=[t
x, t
y, t
z, 1] and be the mapping parameters of world coordinates initial point in image coordinate, R is orthogonal matrix, is defined as:
Metzler matrix is image-world coordinate system transformation matrix, and contain all camera calibration parameters to be determined, camera calibration is exactly the process solving Metzler matrix.We are by measuring world coordinates the value { (x on four summits obtaining training site
wi, y
wi, z
wi) | i=1 ..., 4}, obtains these 4 angle points coordinate figure { (u in the picture in image by manual markings
i, v
i) | i=1 ..., 4}, the method namely by separating above-mentioned system of linear equations obtains Metzler matrix.
After calculating Metzler matrix, appoint to certain point coordinate value under a world coordinate system, the image coordinate value of this some correspondence can be calculated; Appoint to the coordinate of certain point under an image coordinate system and the height z of these corresponding point in world coordinates known
w, can calculate the world coordinates of corresponding point, therefore the present invention adopts camera calibration program flow diagram as shown in Figure 4:
Step S101: video capture piece image, with any pixel for initial point, hand labeled goes out the image coordinate { (u of this section of curve bend four lane boundary line endpoints
i, v
i) | i=1 ..., 4};
Step S102: the physical location point at marking image coordinate origin place, and as world coordinate system initial point, measure the world coordinates { (x of lane line four end points in this section of actual place of curve bend
wi, y
wi, z
wi) | i=1 ..., 4};
Step S103: the world coordinates of four end points and image coordinate are substituted into image-world coordinates and transforms in system of linear equations, solve image-world coordinates transformed matrix M;
Step S104: certain point coordinate value under any one world coordinate system is substituted into M known image-world coordinates and transform system of linear equations, the image coordinate of this some correspondence can be calculated; Under the prerequisite of the known world coordinate height, any one image coordinate is substituted into image-world coordinates transformed matrix known image-world coordinates and transform system of linear equations, the world coordinates of this some correspondence can be calculated; So far, camera calibration is completed.
When adopting the T-shaped sign board shown in Fig. 2, black circle is the Main Basis of distinguishing mark with white circle, and the present invention can adopt sign board recognizer process flow diagram as shown in Figure 5:
Step S201: establish the pixel value at image coordinate (x, y) place to be designated as p
x,y, define two width Threshold segmentation image LB, LD and be respectively used to detect black circle and circle in vain, its pixel value is for being respectively:
Wherein T
b, T
dit is preset value.The all pixel values of LB, LD are calculated according to above formula.
Step S202: for the white circle of detection, find out in LB be 1 connected region, the length and width value in this region is converted to the length and width value under world coordinate system, judges whether length and width value meets the white round size in sign board 5, meets, be designated as the white circle detected.In like manner, same process is done for LD, black circle can be detected.
Step S203: utilize the white circle that detects and black circle, judge whether one by one to connect into the specific line segment consistent with sign board, if passable, then depending on this in vain circle, black circle be reference points detection figure, otherwise give up this circle or black circle in vain; Repeat this step, until travel through all white circles and black circle;
Step S204: if step S203 finds reference points detection figure, then with reference points detection figure for reference point, locate other additional letter and numeric area, as for the identification of letter and number, the method identifications such as template matches can be adopted, because character and numeral identify it has been the common technology of image procossing, in this patent and non-key technologies point, do not repeat them here simultaneously.So far the identification of whole sign board 5 is completed.
Because sign board 5 is the fixed position and the direction that are pasted on vehicle, so position and the attitude of vehicle can be extrapolated according to the position of sign board 5 and direction.Here suppose the dimensional parameters of vehicle, such as length, and the position of sign board on vehicle body and direction obtain by measuring.
When adopting the T-shaped sign board 5 shown in Fig. 2 and the sign board detection method shown in Fig. 3, the angle Theta of the line segment of multiple black circle composition and the line segment of multiple white circle composition is sign board 5 direction.Suppose that the image coordinate indicated is (u
i, v
i), angle is Theta, and sign board 5 is pasted on roof, then z
w=height of car is known, and therefore the position of positioned vehicle and attitude can adopt vehicle location attitude detection flow process as shown in Figure 6:
Step S301: by the image coordinate (u of reference points detection figure obtained in sign board recognizer
i, v
i) substitute in image-world coordinates conversion system of linear equations of camera calibration program, the world coordinates (x of reference points detection figure can be obtained
w, y
w, z
w);
Step S302: in world coordinate system, is linked to be according to the queueing discipline of the original note dot pattern of sign board mark the line segment that there is intersection point by reference points detection figure;
Step S303: in world coordinate system, calculates the coordinate of intersection point and the angle Theta of line segment
w, intersecting point coordinate is vehicle location, and line segment angle is vehicle attitude.
Scoring procedures process flow diagram of the present invention as shown in Figure 7.
Step S401: whether statistics exists vehicle line ball, the used time exceedes the not obviously misoperation such as in regulation region of maximum time limit, parking spot, if existed, then directly judge that this curve driving is defective, scoring terminates;
Step S402: judge the used time whether in critical field, if the critical field of being no more than, then do not deduct points, if exceeded, then according to setting rule deduction corresponding scores, if time-out reaches the upper limit, then directly judge that this curve driving is defective, such as every time-out detains 1 point in 5 seconds, until overtime 200 seconds, the used time be described in step S401 exceedes the maximum time limit;
Step S403: add up final integrate score, if lower than setting value, then judges defective, otherwise is judged to be qualified and provides judgement mark.
Above-mentioned example, only for technical conceive of the present invention and feature are described, its object is to person skilled in the art can be understood content of the present invention and implement according to this, can not limit the scope of the invention with this.All equivalent transformations of doing according to Spirit Essence of the present invention or modification, all should be encompassed within protection scope of the present invention.
Claims (6)
1. a curve driving detection system, it is characterized in that, it comprises the front end system be arranged near curve driving position and the back-end system being deployed in administrative center, described front end system comprises multiple stage main camera, image analyzer and the sign board be placed on training cart, back-end system comprises server and client, front end system connects back-end system by transmission network, monitored picture covers the main camera in warehouse compartment region for shooting with video-corder the travel conditions of warehouse compartment place training cart, the monitoring image that the image analyzer continuous reception main camera be connected with main camera is caught also is compressed into monitoring image, the operation attitude of image analyzer monitor vehicle simultaneously, monitoring result and monitoring image are sent to the server of back-end system by image analyzer, client can be called and check monitoring result in server and monitoring image,
Described sign board is arranged on roof, engine top cover or case cover, and the marker graphic on described sign board is some gauge points, and gauge point is arranged in the specific line segment with fixed angle and unique intersection point;
Also be provided with auxiliary camera in the both sides of every platform main camera, supplement for auxiliary the running orbit catching training cart in warehouse compartment.
2. curve driving detection system according to claim 1, it is characterized in that, the seat in the plane of main camera, auxiliary camera is other is equipped with light compensating lamp, and the synchronizing signal of described light compensating lamp is provided by main camera or auxiliary camera, for carrying out strobe type light filling when illumination is crossed dark.
3. a curve driving detection method, it is characterized in that, described method relates to system and comprises the front end system be arranged near curve driving position and the back-end system being deployed in administrative center, described front end system comprises multiple stage main camera, auxiliary camera, image analyzer and the sign board be placed on training cart, back-end system comprises server and client, front end system connects back-end system by transmission network, monitored picture covers the main camera in warehouse compartment region for shooting with video-corder the travel conditions of warehouse compartment place training cart, image analyzer and main camera, auxiliary camera is connected, concrete detection method comprises the following steps:
Step S1: measure warehouse compartment length and width size by direct labor, runs camera calibration program, realizes the mutual conversion of image coordinate system and world coordinate system;
Step S2: the monitoring image that image analyzer continuous reception main camera is caught, is compressed into video record, simultaneously running mark board recognizer, obtains position and the direction of sign board;
Step S3: image analyzer is according to camera calibration result and sign board recognition result, and operational vehicle position and attitude trace routine, obtains position and the attitude of vehicle; In conjunction with known vehicle dimension, and then determine vehicle ' s contour scope and the profile outer edge bee-line to lane line, and trigger main camera when vehicle line ball or auxiliary camera captures picture; When the sign board of image analyzer identification disappears from the specific region of image, judge that vehicle sails out of corresponding main camera overlay area, image analyzer, by the metrical information of segmentation used time, is all sent to server together with candid photograph picture, video record;
Step S4: after server receives the metrical information that each image analyzer sends, runs scoring procedures, obtains this curve driving comprehensive grading;
Step S5: student or trainer, by client-access server, browse, download and print curve driving relevant scoring, capture picture and video record;
In step S1, when carrying out camera calibration, the step of described camera calibration program is:
Video capture piece image, with any pixel for image coordinate system initial point, hand labeled goes out the image coordinate of four the lane boundary line endpoints in this section of curve bend section;
The physical location point at marking image coordinate origin place, and as world coordinate system initial point, the world coordinates of lane line four end points in actual place, experiment curv bend section;
The world coordinates on four warehouse compartment summits and pixel coordinate are substituted into image-world coordinates transform in system of linear equations, solve image-world coordinates transformed matrix;
Certain point coordinate value under any one world coordinate system is substituted into image-world coordinates transformed matrix known image-world coordinates and transform system of linear equations, the image coordinate of this some correspondence can be calculated; Under the prerequisite of the known world coordinate height, any one image coordinate is substituted into image-world coordinates transformed matrix known image-world coordinates and transform system of linear equations, the world coordinates of this some correspondence can be calculated; So far, camera calibration is completed.
4. curve driving detection method according to claim 3, is characterized in that, in step S3, triggers main camera or auxiliary camera and capture picture and be sent to image analyzer when vehicle line ball or distance are less than setting threshold value in docking process.
5. the curve driving detection method according to claim 3 or 4, is characterized in that, the flow process of carrying out sign board identification in step S2 is as follows:
Threshold segmentation is carried out to image, obtains the image after segmentation;
Connected domain extraction is carried out to the image after Threshold segmentation, judges whether connected domain length and width meets the length and width setting value of sign board gauge point figure, if met, then mark this connected domain;
Can the connected domain of judge mark connect into the shape consistent with real marking board one by one, comprises angle formed by gauge point quantity and gauge point line, if passable, be then reference points detection figure depending on connected region, otherwise give up this connected domain; Repeat this step, until travel through all connected domains;
With reference points detection figure for reference point, identify other additional letter and numeric area and identify, so far completing the identification of whole sign board.
6. curve driving detection method according to claim 5, is characterized in that, step in this detection method
The steps flow chart carrying out vehicle location attitude detection in S3 is:
Image-world coordinates that the image coordinate of the reference points detection figure obtained in sign board recognizer substitutes into camera calibration program is transformed in system of linear equations, the world coordinates of reference points detection figure can be obtained;
In world coordinate system, reference points detection figure is linked to be according to the queueing discipline of sign board mark original tally dot pattern the line segment that there is intersection point;
In world coordinate system, calculate the coordinate of intersection point and the angle of line segment, intersecting point coordinate is vehicle location, and line segment angle is vehicle attitude.
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| CN103996328B (en) * | 2014-06-03 | 2017-01-18 | 湖州师范学院 | Vehicle corner balance testing device and testing method |
| CN106324635B (en) * | 2016-08-01 | 2019-05-10 | 广州展讯信息科技有限公司 | A kind of straight line traveling detection method and device based on satellite navigation and positioning |
| CN107103815A (en) * | 2017-02-28 | 2017-08-29 | 广州地理研究所 | A kind of curve driving checking system and its application process based on vehicle electron identifying |
| CN106969923B (en) * | 2017-05-26 | 2023-09-15 | 交通运输部公路科学研究所 | Vehicle channel circular track testing system and method |
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| CN2600787Y (en) * | 2002-08-21 | 2004-01-21 | 张拥军 | Device for measuring running trace of vehicle starting using digital image identification technology |
| JP2005258364A (en) * | 2004-02-13 | 2005-09-22 | Toshiba Corp | Remote test and course system |
| CN201037962Y (en) * | 2006-06-29 | 2008-03-19 | 北京艾曼特科技有限公司 | Electronic pile examining system |
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Denomination of invention: Curved driving detection system and its detection methods Effective date of registration: 20230522 Granted publication date: 20150520 Pledgee: Bank of Nanjing Limited by Share Ltd. Suzhou branch Pledgor: SUZHOU SUDI INTELLIGENT SYSTEM Co.,Ltd. Registration number: Y2023980041315 |