CN102646334B - Method for automatically obtaining evidences of highway traffic incidents and system adopting method - Google Patents
Method for automatically obtaining evidences of highway traffic incidents and system adopting method Download PDFInfo
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Abstract
The invention relates to the field of intelligent traffic, and discloses a method for automatically obtaining evidence of highway traffic incidents and a system adopting the method. Problems of coordinate errors, difficulty in matching, high cost and the like during monitoring and tracking by the aid of a plurality of cameras are avoided, and a background is adjusted to reduce false targets when a dome camera returns to an original location to monitor again. The method includes steps of A, panoramically monitoring at a preset position by the dome camera; B, automatically tracking and obtaining the evidence by the dome camera when an unlawful target is detected; C, placing the dome camera at the preset position again; and D, shooting a current image by the dome camera, detecting the unlawful target, computing similarity of a target region of the current image and a region, corresponding to the target region, in a background image if the target is detected, fusing the target region into the background image and entering the step A if the similarity is larger than a preset threshold, entering the step B if the similarity is not larger than the preset threshold, and entering the step A if the target is not detected.
Description
Technical field
The present invention relates to intelligent transportation field, particularly a kind of highway panoramic video monitoring technique.
Background technology
By in June, 2011, national private car recoverable amount surpasses 7,206 ten thousand, and high speed total kilometrage is over 7.4 ten thousand kilometers.The thing followed is exactly rolling up of all kinds of violating the regulations, anomalous events.Parking offense, the phenomenon of driving in the wrong direction, often occurring on the highway such as reversing, upper high speed of pedestrian, traffic congestion, have a strong impact on high speed normal operation, to highway, brought serious potential safety hazard.Although the current built highway monitoring system that is provided with, and some is intelligent monitor system, but current intelligent monitor system is mostly used fixed gunlock, can not carry out intelligent-tracking, even if use ball machine can not carry out intelligent-tracking, can only pass through monitor's manual operation, this type systematic can only be reported to the police to highway anomalous event, reminds monitor that this target of this section is paid close attention to and processed.But for the parking offense occurring on road, reversing violating the regulations, the event in short-term of grade of driving in the wrong direction violating the regulations, this type systematic can not be followed the tracks of candid photograph to target, therefore can not this class car owner be punished, and does not have warning function, thereby limited to the management role of highway.
And in principal and subordinate's tracking means, because outdoor ball machine and gunlock are in long-time use procedure, affected by the factors such as outdoor weather and ball machine mechanical precision deficiency, when the image coordinate meeting of overall view monitoring vision sensor and the collection of tracking vision sensor and initial setting up, produce deviation, camera coordinates parameter while causing initial configuration lost efficacy, thereby cause after overall view monitoring camera calibration occurs to event, tracking ball machine can accurately not trace into target.
Simultaneously, when tracking ball machine returns to overall view monitoring state by tracking mode, due to factor impacts such as ball machine machinery control accuracies, monitoring scene is often difficult to accurately get back to original monitoring position, may produce several even deviations of tens pixels, in more existing tracking ball machine treatment mechanisms, can be to Background Reconstruction when ball machine is got back to overall view monitoring position, but can bring so a very large problem: if while now having static target (parking) to be present in image, this target can be updated in background and go, after a period of time, working as vehicle drives away, in the position of former parking, will produce false target causes wrong report to occur.
Summary of the invention
The object of the present invention is to provide a kind of freeway traffic event automatic evidence-collecting method and system thereof, avoiding adopting at present a gunlock to do panorama monitoring finds after target, the coordinate of two video cameras being followed the tracks of by a ball machine has error, coupling is difficult for, the problems such as cost is higher, meanwhile, get back to original position when ball machine and re-start panorama when monitoring, background is adjusted, thus the generation of minimizing false target.
For solving the problems of the technologies described above, embodiments of the present invention disclose a kind of freeway traffic event automatic evidence-collecting method, comprise the following steps:
A ball machine carries out overall view monitoring in precalculated position;
If target violating the regulations detected during B overall view monitoring, ball machine carries out collecting evidence from motion tracking to this target violating the regulations;
C is after motion tracking evidence obtaining finishes, and ball machine is placed in precalculated position again;
D ball machine is taken current frame image, and detects target violating the regulations according to this current frame image,
If the target of detecting, calculates the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region, if similarity is greater than predetermined threshold, target area is incorporated to background image and enter steps A, otherwise entering step B;
If target do not detected, enter steps A.
Embodiments of the present invention also disclose a kind of freeway traffic event automatic evidence collecting system, comprising:
Ball machine, for carry out overall view monitoring in precalculated position, to Automatic Target Tracking evidence obtaining violating the regulations, or takes current frame image and detects whether there is target violating the regulations according to current frame image;
Preset module, for Place machine in precalculated position;
Computing module, for calculating the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region;
Judge module, for judging whether similarity is greater than predetermined threshold;
Incorporate module, for target area is incorporated to background image.
Compared with prior art, the key distinction and effect thereof are embodiment of the present invention:
Use a ball machine to carry out overall view monitoring evidence obtaining violating the regulations, can avoid adopting at present a gunlock to do panorama monitoring and find the problems such as after target, the coordinate of two video cameras being followed the tracks of by a ball machine has error, and coupling is difficult for, and cost is higher.
When ball machine, get back to original position and re-start panorama when monitoring, background is adjusted, thereby reduce the generation of false target.
Further, the similarity by edge direction histogram similarity and Yu Gai target area, grey level histogram Similarity-Weighted average acquiring current frame image target area in region corresponding to background image, has further increased the accuracy of target detection violating the regulations.
Further, edge direction histogram similarity and Yu Gai target area, grey level histogram Similarity-Weighted average acquiring current frame image target area are in the similarity in region corresponding to background image, the edge orientation histogram similarity weight more shared than grey level histogram similarity is large, has further increased the accuracy of target detection result violating the regulations.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of a kind of freeway traffic event automatic evidence-collecting method in first embodiment of the invention;
Fig. 2 is the schematic flow sheet of a kind of freeway traffic event automatic evidence-collecting method in second embodiment of the invention;
Fig. 3 is the Video processing analysis process schematic diagram of a kind of freeway traffic event automatic evidence-collecting method in second embodiment of the invention;
Fig. 4 is the coordinate selection schematic diagram of a kind of freeway traffic event automatic evidence-collecting method in the second embodiment;
Fig. 5 is the trace flow schematic diagram of a kind of freeway traffic event automatic evidence-collecting method in the second embodiment;
Fig. 6 is the structural representation of a kind of freeway traffic event automatic evidence collecting system in third embodiment of the invention;
Fig. 7 is the structural representation of a kind of freeway traffic event automatic evidence collecting system in four embodiment of the invention;
Fig. 8 is the structural representation of a kind of freeway traffic event automatic evidence collecting system in four embodiment of the invention.
Embodiment
In the following description, in order to make reader understand the application better, many ins and outs have been proposed.But, persons of ordinary skill in the art may appreciate that even without these ins and outs and the many variations based on following embodiment and modification, also can realize each claim of the application technical scheme required for protection.
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, embodiments of the present invention are described in further detail.
First embodiment of the invention relates to a kind of freeway traffic event automatic evidence-collecting method.Fig. 1 is the schematic flow sheet of this freeway traffic event automatic evidence-collecting method.This freeway traffic event automatic evidence-collecting method comprises the following steps:
A ball machine carries out overall view monitoring in precalculated position.
If target violating the regulations detected during B overall view monitoring, ball machine carries out collecting evidence from motion tracking to this target violating the regulations.
C is after motion tracking evidence obtaining finishes, and ball machine is placed in precalculated position again.
D ball machine is taken current frame image, and detects target violating the regulations according to this current frame image,
If the target of detecting, calculates the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region, if similarity is greater than predetermined threshold, target area is incorporated to background image and enter steps A, otherwise entering step B.
If target do not detected, enter steps A.
Use a ball machine to carry out overall view monitoring evidence obtaining violating the regulations, can avoid adopting at present a gunlock to do panorama monitoring and find the problems such as after target, the coordinate of two video cameras being followed the tracks of by a ball machine has error, and coupling is difficult for, and cost is higher.
When ball machine, get back to original position and re-start panorama when monitoring, background is adjusted, thereby reduce the generation of false target.
In addition, be appreciated that in the present invention, ball machine can be also one to be had overall view monitoring and follows the tracks of module or the unit of evidence obtaining function.
As a preferred embodiment of the present invention, as shown in Figure 1, this freeway traffic event automatic evidence-collecting method comprises the following steps:
In step 101, whether ball machine carries out overall view monitoring in precalculated position have target violating the regulations to occur.
If have, enter step 102; Otherwise, return to step 101, whether ball machine continues overall view monitoring in precalculated position have target violating the regulations to occur.
In step 102, if target violating the regulations detected during overall view monitoring, ball machine carries out collecting evidence from motion tracking to this target violating the regulations.
After this enter step 103, ball machine, after motion tracking evidence obtaining finishes, is placed in precalculated position again.
After this enter step 104, ball machine is taken current frame image.
After this enter step 105, ball machine detects whether there is target violating the regulations according to this current frame image.
If have, enter step 106; Otherwise, return to step 101, whether ball machine continues overall view monitoring in precalculated position have target violating the regulations to occur.
In step 106, if target violating the regulations detected, calculate the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region.
After this enter step 107, judge whether similarity is greater than predetermined threshold.
If so, enter step 108; Otherwise return to step 102, ball machine carries out collecting evidence from motion tracking to this target violating the regulations.
In step 108, if similarity is greater than predetermined threshold, target area is incorporated to background image, and return to step 101, whether ball machine continues overall view monitoring in precalculated position have target violating the regulations to occur.
Second embodiment of the invention relates to a kind of freeway traffic event automatic evidence-collecting method.Fig. 2 is the schematic flow sheet of this freeway traffic event automatic evidence-collecting method.
The second embodiment improves on the basis of the first embodiment, main improvements are: the similarity by edge direction histogram similarity and Yu Gai target area, grey level histogram Similarity-Weighted average acquiring current frame image target area in region corresponding to background image, has further increased the accuracy of target detection violating the regulations.Edge direction histogram similarity and Yu Gai target area, grey level histogram Similarity-Weighted average acquiring current frame image target area are in the similarity in region corresponding to background image, the edge orientation histogram similarity weight more shared than grey level histogram similarity is large, has further increased the accuracy of target detection result violating the regulations.Specifically:
As shown in Figure 2, this Yu Gai target area, current frame image target area of above-mentioned calculating, in the step 106 of the similarity in region corresponding to background image, also comprises following sub-step:
In step 201, calculate respectively current frame image target area gradient texture and this target area at the gradient texture of background image corresponding region.
After this enter step 202, object edge image separately described in obtaining.
After this enter step 203, add up the direction histogram of object edge image separately.
After this enter step 204, statistics the histogrammic edge orientation histogram similarity of calculated direction.
After this enter step 205, calculate Yu Gai target area, current frame image target area in the grey level histogram similarity in region corresponding to background image.
After this enter step 206, edge direction histogram similarity and grey level histogram Similarity-Weighted are average, the similarity as Yu Gai target area, current frame image target area in region corresponding to background image, after this process ends.
Above-mentioned steps 201 to step 204 edge calculation direction histogram similarity process and step 205 calculated grey level histogram similarity process can exchange order, first calculates grey level histogram similarity edge calculation direction histogram similarity again.
In addition, be appreciated that, in some other embodiments of the present invention, carry out Yu Gai target area, current frame image target area when the weighted calculation of the similarity in region corresponding to background image, be not limited to the weighted calculation to structural similarity and texture similarity, also comprise the weighted calculation to color similarity, because color similarity calculates, belong to known technology, do not explain here.
In some other embodiments of the present invention, Yu Gai target area, current frame image target area the similarity in region corresponding to background image also can reference texture similarity, in color similarity, grey level histogram similarity one, or also can reference texture similarity, several in color similarity, grey level histogram similarity are weighted average resulting similarity.
The edge orientation histogram similarity weight more shared than grey level histogram similarity is large.
If target violating the regulations detected during overall view monitoring, also target violating the regulations is carried out to interlink warning.
Calculate this Yu Gai target area, current frame image target area in the step of the similarity in region corresponding to background image, the image coordinate system based on identical calculates.
As a preferred embodiment of the present invention, at expressway ramp mouth, high-speed ball camera is installed in intercommunication gateway and each section, makes the effective field of view scope of the vision sensor of video camera cover whole crossing, non-blind area, comprehensive detection vehicular traffic.
Detection module in ball machine detects and panorama tracking automatically to entering the target of guarded region, grasps the movement locus of each target, thereby detects each target in the various act of violating regulations information of guarded region, and specifically processing procedure is as shown in Figure 3:
First day mode carries out background extracting to input picture, and the method for background extracting is existing method, as mixed Gauss model background extracting, extracts after background and relatively can obtain moving target in present image by present image and background image.Night mode is by detecting definite moving target to car light.
In step 301, ball machine gathers or input picture.
After this enter step 302, detection module extracts moving target from the image of input.
After this enter step 303, from motion tracking evidence obtaining module, motion target tracking is collected evidence, after detecting moving target, use Kalman Kalman, the methods such as average drifting Mean Shift or particle filter Particle Filter are followed the tracks of moving target, obtain the movement locus of target.
After this enter step 304, the variation of the movement locus of evaluating objects, when target trajectory and actual track opposite direction or while being greater than set angle, thinks that target drives in the wrong direction; When target trajectory is static and surpass setting-up time restriction, judge that target is as stopping.
When detection module detects after act of violating regulations or event violating the regulations or target violating the regulations, first determine the initial coordinate of following the tracks of in image, can follow the tracks of the selection of initial coordinate and finally see and please have substantial connection by car plate, the angle of following the tracks of the selection of initial point and the type of target, target and camera be relevant.
From projection theory, in the situation that camera heights is constant, target and camera distance are nearer, and angle is larger, and the car plate of target is just the closer to below, target area; Target longer (as semitrailer, motor bus), car plate position in image also below target.Therefore selecting initial type and the camera antenna height that coordinate time needs comprehensive evaluating objects of following the tracks of, camera sets up distance, determines and follows the tracks of the coordinate of initial point in image.
In the distance (pixel) of following the tracks of initial point distance objective lower limb and image, the ratio P of the length (pixel) of target is proportional to the distance d of camera and target, is inversely proportional to camera antenna height h and target length l.In theory when target infinite distance, the position of P be car plate position apart from the ratio P0 of floor level Ph and height of car Vh, as figure, P0=Ph/Vh, conventionally P0=1/4.As shown in Figure 4.
H is the height of camera, and d1 is that in image, headstock is according to the vertical actual range of camera, and d2 is that in image, the tailstock is apart from the vertical actual range of camera, and the formula that calculates P is as follows:
α＝arctan(d1/h)；
β＝arctan(d2/h)；
P＝P0＊Cos(β-α)；
Wherein, α is the vertical angle of headstock and camera lens, and β is the vertical angle of the tailstock and camera lens.
Detection module will initially be followed the tracks of coordinate and pass to after motion tracking quick or module, and quick is controlled PTZ (wherein, P: horizontally rotate angle; T: vertical rotation angle; Z (zoom) focal length) target is amplified, and tracking target is carried out to motion compensation, after motion compensation, mate clarification of objective, upgrade and follow the tracks of coordinate.Until car plate stops multiplying power when high-visible, amplify, and the P (Pan) and the T (Tilt) that continue control marble forming machine follow the tracks of target.
In this overall view monitoring tracking violating the regulations evidence-obtaining system, the video image that tracking module and detection module are used same vision sensor to gather, therefore tracking module and detection module are under same image coordinate, tracking module is after having obtained the initial tracking coordinate that detection module provides, do not need to carry out any coordinate conversion, can directly start trace routine, the feature of evaluating objects in image, drive fire ball machine zoom, the actions such as zoom are followed the tracks of, and in the process of following the tracks of, revise and follow the tracks of coordinate.
After act of violating regulations being detected, ball machine is recorded a video to event violating the regulations, as law enforcement foundation, to car owner, punishes applicable afterwards.
As a preferred embodiment of the present invention, specifically trace flow is as shown in Figure 5:
In step 501, initialization ball machine trace point.
After this enter step 502, automatically track target.
After this enter step 503, target signature coupling.
After this enter step 504, upgrade and follow the tracks of coordinate, after this process ends.
Each method embodiment of the present invention all can be realized in modes such as software, hardware, firmwares.No matter the present invention realizes with software, hardware or firmware mode, instruction code can be stored in the storer of computer-accessible of any type (for example permanent or revisable, volatibility or non-volatile, solid-state or non-solid-state, fixing or removable medium etc.).Equally, storer can be for example programmable logic array (Prog rammable Array Logic, be called for short " PAL "), random access memory (Random Access Memory, be called for short " RAM "), programmable read only memory (Programmable Read Only Memory, be called for short " PROM "), ROM (read-only memory) (Read-Only Memory, be called for short " ROM "), Electrically Erasable Read Only Memory (Electrically Erasable Programmable ROM, be called for short " EEPROM "), disk, CD, digital versatile disc (Digital Versatile Disc, be called for short " DVD ") etc.
Third embodiment of the invention relates to a kind of freeway traffic event automatic evidence collecting system.Fig. 6 is the structural representation of this freeway traffic event automatic evidence collecting system.This freeway traffic event automatic evidence collecting system comprises:
Ball machine, for carry out overall view monitoring in precalculated position, to Automatic Target Tracking evidence obtaining violating the regulations, or takes current frame image and detects whether there is target violating the regulations according to current frame image.
Preset module, for Place machine in precalculated position.
Computing module, for calculating the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region.
Judge module, for judging whether similarity is greater than predetermined threshold.
Incorporate module, for target area is incorporated to background image.
The first embodiment is the method embodiment corresponding with present embodiment, present embodiment can with the enforcement of working in coordination of the first embodiment.The correlation technique details of mentioning in the first embodiment is still effective in the present embodiment, in order to reduce repetition, repeats no more here.Correspondingly, the correlation technique details of mentioning in present embodiment also can be applicable in the first embodiment.
Four embodiment of the invention relates to a kind of freeway traffic event automatic evidence collecting system.Fig. 7 and Fig. 8 are the structural representations of this freeway traffic event automatic evidence collecting system.
The 4th embodiment improves on the basis of the 3rd embodiment, and main improvements are: the edge orientation histogram similarity weight more shared than grey level histogram similarity is large, has further increased the accuracy of target detection result violating the regulations.As shown in Figure 7, specifically:
Computing module, also comprises following subelement:
Texture computation subunit, for calculating respectively current frame image target area gradient texture and this target area at the gradient texture of background image corresponding region.
Edge obtains subelement, the image of object edge separately calculating for obtaining texture computation subunit.
Statistics with histogram subelement, obtains the direction histogram of the image of object edge separately that subelement obtains for adding up edge.
The first similarity subelement, for adding up the edge orientation histogram similarity of the direction histogram that also compute histograms statistics subelement counts.
The second similarity subelement, for calculating Yu Gai target area, current frame image target area in the grey level histogram similarity in region corresponding to background image.
Weighted mean subelement, the grey level histogram Similarity-Weighted going out for edge orientation histogram similarity that the first similarity subunit computes is gone out and the second similarity subunit computes is average, the similarity as Yu Gai target area, current frame image target area in region corresponding to background image.
In addition, be appreciated that, in some other embodiments of the present invention, carry out Yu Gai target area, current frame image target area when the weighted calculation of the similarity in region corresponding to background image, be not limited to the weighted calculation to structural similarity and texture similarity, also comprise the weighted calculation to color similarity, because color similarity calculates, belong to known technology, do not explain here.
In some other embodiments of the present invention, Yu Gai target area, current frame image target area the similarity in region corresponding to background image also can reference texture similarity, in color similarity, grey level histogram similarity one, or also can reference texture similarity, several in color similarity, grey level histogram similarity are weighted average resulting similarity.
The edge orientation histogram similarity weight more shared than grey level histogram similarity is large.
As shown in Figure 8, this freeway traffic event automatic evidence collecting system also comprises:
Interlink warning module, carries out interlink warning if target violating the regulations detected during for ball machine overall view monitoring to target violating the regulations.
Computing module, the image coordinate system based on identical calculates the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region.
The second embodiment is the method embodiment corresponding with present embodiment, present embodiment can with the enforcement of working in coordination of the second embodiment.The correlation technique details of mentioning in the second embodiment is still effective in the present embodiment, in order to reduce repetition, repeats no more here.Correspondingly, the correlation technique details of mentioning in present embodiment also can be applicable in the second embodiment.
It should be noted that, each unit of mentioning in each equipment embodiment of the present invention is all logical block or module, physically, logical block or module can be a physical location or module, also can be a part for a physical location or module, can also realize with the combination of a plurality of physical locations or module, the physics realization mode of these logical blocks or module itself is not most important, and the combination of the function that these logical blocks or module realize is the key that just solves technical matters proposed by the invention.In addition, for outstanding innovation part of the present invention, above-mentioned each equipment embodiment of the present invention is not introduced the unit not too close with solving technical matters relation proposed by the invention or module, and this does not show that the said equipment embodiment does not exist other unit or module.
Although pass through with reference to some of the preferred embodiment of the invention, the present invention is illustrated and described, but those of ordinary skill in the art should be understood that and can do various changes to it in the form and details, and without departing from the spirit and scope of the present invention.
Claims (10)
1. a freeway traffic event automatic evidence-collecting method, is characterized in that, comprises the following steps:
A ball machine carries out overall view monitoring in precalculated position;
If target violating the regulations detected during B overall view monitoring, described ball machine carries out collecting evidence from motion tracking to this target violating the regulations;
C is after motion tracking evidence obtaining finishes, and described ball machine is placed in described precalculated position again;
Described in D, ball machine is taken current frame image, and detects target violating the regulations according to this current frame image,
If the target of detecting, calculates the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region, if described similarity is greater than predetermined threshold, target area is incorporated to background image and enter steps A, otherwise entering step B;
If target do not detected, enter steps A.
2. freeway traffic event automatic evidence-collecting method according to claim 1, is characterized in that, this Yu Gai target area, current frame image target area of described calculating, in the step of the similarity in region corresponding to background image, comprises following sub-step:
Calculate respectively current frame image target area gradient texture and this target area at the gradient texture of background image corresponding region, and object edge image separately described in obtaining;
Add up the direction histogram of object edge image separately;
Add up and calculate the edge orientation histogram similarity of direction histogram separately;
Calculate Yu Gai target area, current frame image target area in the grey level histogram similarity in region corresponding to background image;
Average to described edge orientation histogram similarity and grey level histogram Similarity-Weighted, the similarity as Yu Gai target area, current frame image target area in region corresponding to background image.
3. freeway traffic event automatic evidence-collecting method according to claim 2, is characterized in that, the described edge orientation histogram similarity weight more shared than grey level histogram similarity is large.
4. freeway traffic event automatic evidence-collecting method according to claim 1, is characterized in that, if target violating the regulations detected during overall view monitoring, also described target violating the regulations is carried out to interlink warning.
5. according to the freeway traffic event automatic evidence-collecting method described in any one in claim 1 to 4, it is characterized in that, this Yu Gai target area, current frame image target area of described calculating is in the step of the similarity in region corresponding to background image, and the image coordinate system based on identical calculates.
6. a freeway traffic event automatic evidence collecting system, is characterized in that, comprising:
Ball machine, for carry out overall view monitoring in precalculated position, to Automatic Target Tracking evidence obtaining violating the regulations, or takes current frame image and detects whether there is target violating the regulations according to current frame image;
Preset module, for putting described ball machine in described precalculated position;
Computing module, for calculating the Yu Gai target area, target area of described current frame image in the similarity of background image corresponding region;
Judge module, for judging whether described similarity is greater than predetermined threshold;
Incorporate module, for judging that at described judge module similarity incorporates background image by described target area while being greater than predetermined threshold.
7. freeway traffic event automatic evidence collecting system according to claim 6, is characterized in that, described computing module also comprises following subelement:
Texture computation subunit, for calculating respectively current frame image target area gradient texture and this target area at the gradient texture of background image corresponding region;
Edge obtains subelement, the image of object edge separately calculating for obtaining described texture computation subunit;
Statistics with histogram subelement, obtains the direction histogram of the image of object edge separately that subelement obtains for adding up described edge;
8. freeway traffic event automatic evidence collecting system according to claim 7, is characterized in that, the described edge orientation histogram similarity weight more shared than grey level histogram similarity is large.
9. freeway traffic event automatic evidence collecting system according to claim 6, is characterized in that, also comprises:
Interlink warning module, carries out interlink warning if target violating the regulations detected during for described ball machine overall view monitoring to described target violating the regulations.
10. according to the freeway traffic event automatic evidence collecting system described in any one in claim 6 to 9, it is characterized in that, described computing module, the image coordinate system based on identical calculates the Yu Gai target area, target area of current frame image in the similarity of background image corresponding region.
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| CN103679688B (en) * | 2012-09-18 | 2016-11-09 | 浙江大华技术股份有限公司 | A kind of method and device extracting target image |
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| TWI569212B (en) * | 2015-12-10 | 2017-02-01 | 財團法人工業技術研究院 | Image recognition method |
| CN105679017B (en) * | 2016-01-27 | 2018-09-18 | 福建工程学院 | A kind of method and system of fender-bender auxiliary evidence obtaining |
| CN109935074B (en) * | 2017-12-16 | 2022-07-15 | 杭州青奇科技有限公司 | System, method and device for judging whether user rides safely or not and storage medium |
| CN110321806A (en) * | 2019-06-12 | 2019-10-11 | 浙江大华技术股份有限公司 | Object detection method, image processing equipment and the equipment with store function |
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| KR100837435B1 (en) * | 2006-10-25 | 2008-06-12 | 삼성전자주식회사 | Photographing apparatus for controlling object tracking and method thereof |
| CN101610420A (en) * | 2008-06-20 | 2009-12-23 | 睿致科技股份有限公司 | The method of Automatic white balance |
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| CN102254395A (en) * | 2011-06-07 | 2011-11-23 | 北京引创科技有限责任公司 | Article theft detecting and alarming device and method based on intelligent video analysis |
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