KR20160137162A - Method for detecting biased vehicle and apparatus thereof - Google Patents

Method for detecting biased vehicle and apparatus thereof Download PDF

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Publication number
KR20160137162A
KR20160137162A KR1020150071871A KR20150071871A KR20160137162A KR 20160137162 A KR20160137162 A KR 20160137162A KR 1020150071871 A KR1020150071871 A KR 1020150071871A KR 20150071871 A KR20150071871 A KR 20150071871A KR 20160137162 A KR20160137162 A KR 20160137162A
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vehicle
license plate
lane
information
vehicle image
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KR1020150071871A
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Korean (ko)
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KR101690136B1 (en
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안순현
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렉스젠(주)
안순현
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    • G06K9/3258—
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G06K2209/15—

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  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)
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Abstract

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle deviation detection method and apparatus therefor. According to the present invention, there is provided a vehicle deviation detection method using a vehicle deviation detection apparatus, comprising: detecting a license plate area from a vehicle image acquired by a camera of a road; detecting at least one license plate coordinate corresponding to the license plate area And providing bias information corresponding to a degree of deviation of the license plate coordinates in a predetermined direction based on reference coordinates corresponding to the reference line.
According to the vehicle deviation detection method and apparatus therefor, it is possible to easily detect a vehicle that intentionally avoids camera surveillance on a road, and analyze statistical data related to the road segment with frequent camera avoidance frequency in advance And can also be used as a complementary and design data for the illegal surveillance system.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a vehicle-

BACKGROUND OF THE INVENTION 1. Field of the Invention [0002] The present invention relates to a vehicle deviation detection method and apparatus, and more particularly, to a vehicle deviation detection method and apparatus capable of determining a bias of a vehicle running on a road using a license plate of a vehicle.

An intelligent vehicle monitoring system for detecting vehicles that violate traffic regulations such as specified speeds and signal violations for the roads running on the roads is currently being actively operated on most roads.

Such a vehicle monitoring system detects an illegal act of a vehicle by interlocking with a camera installed on the road. Generally, the camera is installed in a place where the vehicle can be easily identified, such as the upper part of a road.

However, the driver of a vehicle often runs in speed without recognizing the existence of the camera until it reaches the position close to the camera. Of course, there are also a large number of cases where the driver intentionally speeds up the vehicle until he or she is aware of the position of the camera through navigation and arrives at the position of the camera.

In this case, a driver of a certain vehicle may intentionally deviate a part or all of the road lane or move on a shoulder road for the purpose of avoiding the interruption of the camera as soon as the camera is detected during the speedy driving. However, there is a problem in this process that it causes a very dangerous situation such as a contact accident with nearby vehicles or a large-scale traffic accident.

The technology of the background of the present invention is disclosed in Korean Utility Model Application No. 2011-0000780 (published on Jan. 24, 2011).

It is an object of the present invention to provide a vehicle deviation detection method and apparatus capable of determining the degree of deviation of a vehicle running on a road using a license plate of a vehicle.

The present invention provides a vehicle deviation detection method using a vehicle deviation detection apparatus, comprising the steps of: detecting a license plate area from a vehicle image acquired by a camera of a road; and detecting at least one license plate Detecting the coordinates and providing the deviation information corresponding to the degree of deviation of the license plate coordinates in the predetermined direction based on the reference coordinates corresponding to the reference line.

Here, the vehicle deviation detection method may further include the step of recognizing the vehicle number of the vehicle from the license plate area, and storing at least one of the bias information and the vehicle number in the vehicle image .

In addition, the providing of the skew information may provide the skew information by matching with the vehicle image.

Also, in the step of providing the bias information, the width of the license plate area may be calculated, and the degree of deviation may be calculated using a ratio of the width of the license plate area divided by the reference coordinates.

The reference line may be a vertical line intersecting the coordinate point corresponding to the y-axis coordinate of the license plate coordinate among the coordinates constituting the critical lane determined by the lane mapped to the vehicle image, , And the width of the set mapped ratio with respect to the width of the mapped mapped line.

The reference line may be a lane line detected from the vehicle image or a reference line selected from a user.

The reference line may be a left end or a right end of the vehicle image.

The vehicle deviation detection method further includes the steps of: comparing the calculated deviation information of the vehicle with a plurality of preliminarily stored slope levels, and classifying the slope levels to which the vehicle belongs for each of the plurality of vehicles; Level, the vehicle image or vehicle information corresponding to the selected level may be searched for and provided.

According to another aspect of the present invention, there is provided an image processing apparatus comprising: a license plate detecting unit for detecting license plate regions from a vehicle image acquired by a camera on a road; a coordinate detecting unit for detecting at least one license plate coordinate corresponding to the license plate region; And a deviation information providing unit for providing deviation information corresponding to a degree of deviation of the license plate coordinates in a predetermined direction as a basis.

According to the vehicle deviation detection method and apparatus of the present invention, it is possible to easily detect a vehicle that intentionally avoids camera surveillance on the road, analyze in advance road segments with frequent camera avoidance frequency, And provides the advantage that the data can be utilized as a complementary and design data for the illegal surveillance system

BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a configuration diagram of a vehicle deviation detection apparatus according to an embodiment of the present invention; FIG.
2 is an exemplary diagram in which a reference line is set in a vehicle image in the embodiment of the present invention.
3 is a flowchart of a vehicle deviation detection method using the apparatus of FIG.
FIG. 4 is a diagram illustrating a case where the license plate area does not deviate from the reference line in the embodiment of the present invention. FIG.
5 and 6 are views illustrating a case where the license plate area deviates from the reference line in the embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention.

The present invention relates to a vehicle deviation detection method and apparatus, and more particularly, it relates to a vehicle deviation detection method and apparatus that compares coordinates of a license plate area of a vehicle obtained from a vehicle image with coordinates of a reference line to obtain vehicle deviation information, Thereby providing a function of detecting a vehicle running.

The present invention can provide a preferential search function of a passing vehicle by avoiding a camera, and can be utilized for supplementing and revising a surveillance system by using statistics based on avoidance frequency and history generated in each camera interval.

BRIEF DESCRIPTION OF DRAWINGS FIG. 1 is a configuration diagram of a vehicle deviation detection apparatus according to an embodiment of the present invention; FIG. 1 is a block diagram illustrating a vehicle position detection apparatus according to an embodiment of the present invention. The vehicle position detection apparatus 100 includes a license plate detection unit 110, a coordinate detection unit 120, a reference setting unit 130, a bias information providing unit 140, An analysis unit 160, a search unit 170, and a camera control unit 180. The camera unit 180 includes a camera,

The license plate detection unit 110 detects the license plate area of the vehicle from the vehicle image acquired by the camera 10 on the road. Here, the camera 10 may be an intermittent camera or a security camera installed on the road, and may correspond to a camera installed separately for vehicle deviation detection.

The license plate area may refer to an outer area of the license plate obtained by edge detection or the like in the vehicle image. Generally, the size of the license plate is the same for each vehicle. The embodiment of the present invention can determine whether or not the vehicle leaves the lane and the degree of the lane departure using the license plate area detected from the vehicle image.

The coordinate detection unit 120 detects at least one license plate coordinate corresponding to the license plate area in the vehicle image. For example, the coordinate detecting unit 120 can obtain the x-axis coordinate values of the corner points constituting the license plate area from the vehicle image. Here, the x-axis coordinate value may correspond to the pixel coordinates in the image.

The reference setting unit 130 sets a reference line to be applied to the vehicle image. This reference line can be automatically set to the lane line detected in the vehicle image. Further, the information of the reference line may be directly selected from the user. In addition, the reference line may be set to a line corresponding to the left end or the right end of the vehicle image.

In the embodiment of the present invention, the reference line is a reference index for determining whether or not the vehicle leaves the lane. Therefore, the present embodiment determines that the vehicle has deviated from the lane when the coordinates of the corner point of the license plate area deviate from the reference line.

The bias information providing unit 140 provides bias information corresponding to the degree of deviation of the plate coordinates in a predetermined direction based on the reference coordinates corresponding to the reference line.

If the detected x-axis coordinate of the corner point is deviated in the positive or negative x-axis direction with respect to the reference x-axis coordinate corresponding to the reference line, the deviation information of the vehicle corresponding to the degree of deviation is calculated and provided . As the outermost coordinates of the license plate area deviate from the boundary of the reference line, it means that the degree of deviation is large and the vehicle has a lot of bias.

The skew information providing unit 140 may calculate the skew information, store the skew information, and provide the stored skew information and the skew information. In addition, the skew information providing unit 140 may store at least one of the skew information and the vehicle number in the vehicle image. Here, the vehicle number represents information obtained by the number recognizing unit 150. [ The number recognition unit 150 recognizes the vehicle number from the license plate area of the vehicle. Recognition of the car number within the license plate area can use known image recognition algorithms and the like.

The analysis unit 160 classifies the vehicle into various levels according to the degree of the slip based on the slip information calculated for each vehicle, and provides statistical data related thereto. When the user selects one of the various levels from the user, the search unit 170 searches for and provides vehicle image or vehicle information belonging to the corresponding level.

As described above, the embodiment of the present invention classifies the degree of the license plate area of the vehicle out of the reference line into a plurality of levels, and supports a search function for vehicles belonging to each level based on the classification.

Further, in the case of the embodiment of the present invention, in order to acquire the vehicle image at the beginning, a method of acquiring the vehicle image at all times through the camera or acquiring the vehicle image only when the vehicle is detected can be used. Here, in the latter case of acquiring the vehicle image only when the vehicle is detected, a separate vehicle detection sensor is required, and the camera control unit 180 controls the operation of the camera based on the detection data.

When a vehicle is detected by a vehicle detection sensor (e.g., a loop sensor, a laser, or an image detection sensor) installed on the road, the camera control unit 180 detects a vehicle detected using a camera mapped with a vehicle detection sensor among a plurality of cameras And acquires the vehicle image corresponding to the vehicle. For example, an image within a specific time range can be acquired as a vehicle image based on the sensing time of the image of the corresponding camera mapped with the vehicle detection sensor.

Hereinafter, a reference line serving as a reference for judging whether a vehicle is misaligned will be described in detail in the embodiment of the present invention.

2 is an exemplary diagram in which a reference line is set in a vehicle image in the embodiment of the present invention. In the case of FIG. 2, the reference line L is set as a vertical line in the vehicle image, and the position corresponding to the reference line in the vehicle image can be set by the user through an input method such as screen touch, mouse selection, coordinate value selection,

In addition, when an arbitrary corner point among the four corner points constituting the license plate area is selected from the user, the corresponding reference line may be automatically set on the screen based on the lane information in the vehicle image. Further, at least one reference line corresponding to at least one of the coordinates of the four corner points may be automatically set without selection of the user based on the lane information. Hereinafter, the setting of the reference line will be described in detail.

The reference line is set to a line that vertically intersects the coordinate point portion corresponding to the y-axis coordinate of the license plate coordinate (x, y) among the coordinates constituting the critical lane L determined by the lane mapped to the vehicle image . For example, when the license plate coordinate is arbitrary corner point coordinates of the license plate area, the reference line corresponds to the y-axis coordinate (y1) of arbitrary corner point (x1, y1) among the coordinates constituting the critical lane L And a vertical line positioned on the coordinate point P at which the point P is located. Here, the critical lane may be formed offset to the inside of the lane so as to have the width of the setting ratio (ex, 50%) in comparison with the width of the actual lane mapped to the vehicle image. More specifically, it is as follows.

In FIG. 2, the steady region B means an area where the license plate area A of the vehicle can exist when the vehicle runs normally without leaving the lane. For example, the steady region B may correspond to a region to which the set ratio (ex, 50%) is applied to the width of the lane in the vehicle image. Assuming that the width of the normal lane is 3.6 m, the normal region B may mean a region corresponding to the half of the width of the normal region (B) of 1.8 m.

The critical lane C means a line corresponding to the boundary of this normal region B. [ Since there are two lanes in the image of Fig. 2, there are two critical lanes as well.

The embodiment of the present invention can acquire the lane portion from the captured image of the road in advance and map the lane portion in the vehicle image in advance. 2, the critical lane is offset to the inside of the lane so as to have the width (ex, 1.8%) of the setting ratio (ex, 50%) in comparison with the width (ex, 3.6 m) of the lane mapped to the vehicle image .

2, the reference line L is a coordinate point corresponding to the y-axis coordinate (y1) of an arbitrary corner point (x1, y1) of the license plate area among the coordinates constituting the critical lane C offset from the lane in the vehicle image. (P). If the x-axis coordinate (x1) of the corner point of the license plate deviates from the x-axis coordinate (x0) of the reference line L in the negative x-axis direction, the vehicle can be judged to have departed from the lane.

2, when the upper corner point (x2, y2) of the two corner points on the left side of the license plate area is selected, the y-axis coordinate (y2) of the upper corner point among the coordinates forming the critical lane C The reference line will be set vertically on the corresponding coordinate point. In this case, the x-axis coordinate (x0 ') of the set reference line will exist to the right of the case of Fig. 2 (x0'> x0) and the x-axis coordinate to be compared with the reference line will be x2. For reference, in FIG. 2, the license plate area has x1 <x2 and y1 <y2, since the expression of perspective is omitted.

FIG. 2 exemplifies the determination of the deviation of the vehicle from the left lane to the right lane. In the case of the vehicle lane deviation determination in the right lane, the same method may be used.

When the vehicle is shifted to the left lane, the x-axis coordinate (x1) of the left corner point among the corner points constituting the license plate area is compared with its reference x-axis coordinate (x0) , It is possible to judge the vehicle deviation by comparing the x-axis coordinate of the right corner point with the reference x-axis coordinate.

In other words, it is judged whether or not the left corner point of the license plate area deviates in the negative direction based on the left critical lane, and the vehicle lane decision on the right lane is based on the right critical lane It is judged whether or not the right corner of the license plate area deviates in the positive direction.

The reference line L may be formed in correspondence with an arbitrary point selected by the user or may be automatically formed at the corresponding point P when a certain point is selected by the user.

Hereinafter, a vehicle deviation detection method will be described in detail with reference to FIG. 1 to FIG. 3 is a flowchart of a vehicle deviation detection method using the apparatus of FIG.

First, the vehicle deviation detection apparatus 100 acquires the vehicle image from the camera 10 installed on the road (S310). The step S310 may utilize a general intermittent camera installed on the road or a vehicle image obtained from the method camera. In addition, in step S310, when a vehicle is detected from a vehicle detection sensor installed on the road, an image captured through a camera operating in conjunction with the vehicle may be utilized.

When the vehicle image is obtained, the license plate detecting unit 110 detects the license plate region of the vehicle from the vehicle image (S320). The technique of detecting the area of the license plate area from the vehicle image can use the well-known object recognition algorithm.

Next, the coordinate detecting unit 120 detects x-axis coordinates of at least one corner point constituting the license plate area (S330). Here, the x-axis coordinates of all the corner points constituting the license plate area can be detected, or only the x-axis coordinates of one of the left and right corner points can be detected depending on the situation.

After that, the reference setting unit 130 selects the position of the reference line applied to the vehicle image from the user (S340). The concept of the reference line L in the vehicle image has been described above. Here, the process of selecting the reference line may be performed after step S320, and may be omitted when the reference line is automatically set in the vehicle image.

When the detected x-axis coordinate is deviated in the positive or negative x-axis direction with respect to the reference x-axis coordinate corresponding to the reference line, the deviation information providing unit 140 calculates the deviation information of the vehicle (S350).

If the vehicle departs from any of the lanes of both lanes, the license plate area A of the vehicle is also biased toward the direction in which the vehicle departs from the image.

For example, if the vehicle is traveling in a lane lane between the two lanes, the x-axis coordinate of the corner point located on the left of the four corner points of the license plate area (A) Axis direction to the negative x-axis direction. The opposite is true, of course.

FIG. 4 is a diagram illustrating a case where the license plate area does not deviate from the reference line in the embodiment of the present invention. FIG. This corresponds to FIG. 2 and will not be described in detail.

5 and 6 are views illustrating a case where the license plate area deviates from the reference line in the embodiment of the present invention. 5 and 6 show a case where the license plate area A is deviated from the reference line L. It can be seen that the degree of deviation (the difference between x0 and x1) is larger in Fig. 6 than in Fig. Of course, there may be cases in which all of the license plate areas A are out of the lane in addition to those shown in the figure.

5 and 6 illustrate only the case where the license plate area A is deviated to the left for convenience of explanation, but the present invention is not necessarily limited to this. Generally, when the vehicle is avoiding the camera, it is often avoided to the right with respect to the driving direction in many cases, and it can be seen that the vehicle is deviated to the left as shown in FIG. In some cases, however, the vehicle may be avoided to the left of the road for the purpose of avoiding the camera. Therefore, in the embodiment of the present invention, the direction in which the vehicle leaves the lane is not necessarily limited to the right or left.

If it is determined that the corner of the license plate area A of the vehicle detected in the vehicle image deviates even slightly from the reference line at step S350, it is determined that the vehicle has deviated from the lane. In step S350, the width of the license plate area A may be calculated, and then the degree of deviation may be calculated using a ratio obtained by dividing the calculated width by the reference coordinates.

Specifically, the x-axis coordinate of the detected corner point may correspond to the information corresponding to the ratio of the length (| x0-x1 |) deviating from the reference x-axis coordinate on the basis of the width length of the license plate area A .

FIG. 5 illustrates an example of the skew information of a vehicle. Assuming here that the width of the license plate area A is M, the deviation information of the vehicle in the case of FIG. 5 can be calculated as a value corresponding to | x0-x1 | / M. Of course, the deviation information of the vehicle calculated in step S350 has a larger value as the degree of deviation is larger, and the value of FIG. 6 has a larger value than that of FIG.

Thereafter, the skew information providing unit 140 may match the calculated skew information with the vehicle image, store the skew information, and provide the stored information (S360). Of course, at this time, the information on the recognized car number in the license plate area A of the vehicle can be further matched and stored.

The deviation information of the vehicle obtained from the vehicle image can be classified into several levels according to the degree of deviation of the vehicle. The embodiment of the present invention may further provide a data classification and search function according to the level of smear.

First, the analysis unit 170 compares the calculated vehicle deviation information with each of the plurality of pre-stored slip levels, and then classifies the slip levels to which the vehicle belongs for each vehicle. For example, the smoothing level may be divided into first to n-th plural levels in order of small smoothing.

Based on the analyzed data, the search unit 180 retrieves and provides the vehicle image or vehicle information corresponding to the selected level when one of the plurality of levels is selected from the user. For example, when the first level search request is received from the user, the search unit 180 may provide information such as the vehicle image per se belonging to the first level or the vehicle number or vehicle type recognized from the vehicle image.

In addition, the analysis unit 170 may calculate statistics on the number of vehicles belonging to each level for each of a plurality of bias levels. For example, in the present camera section, it is possible to calculate the level of the inclination of the vehicles intentionally avoided by the camera, and to accumulate the number of vehicles by each level. In this case, it is possible to determine the level occurring at the highest frequency in the current camera section and predict the accident risk index for the current camera section. In addition, if this process is performed for each camera section, a section in which the camera avoidance frequency is high among a plurality of camera sections can be statistically calculated.

As described above, according to the present invention, it is possible to easily detect a vehicle that intentionally avoids camera surveillance on a road, analyze a road section frequently frequented by a camera, Related statistical data can be constructed and the constructed data can be used as a complementary and design data of the illegal surveillance system.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

100: vehicle deviation detecting apparatus 110: license plate detecting section
120: Coordinate detection unit 130: Reference setting unit
140: shifting information providing unit 150: number recognizing unit
160: Analysis unit 170: Search unit
180: camera control unit

Claims (16)

A method for detecting a vehicle deviation using a vehicle deviation detection apparatus,
Detecting a license plate area from the vehicle image acquired from the camera of the road;
Detecting at least one license plate coordinate corresponding to the license plate area; And
And providing the deviation information corresponding to the degree of deviation of the license plate coordinates in a predetermined direction based on the reference coordinates corresponding to the reference line. The method according to claim 1,
Recognizing the vehicle number of the vehicle from the license plate area; And
Further comprising the step of matching at least one of the shift information and the vehicle number to the vehicle image and storing the vehicle image. The method according to claim 1,
Wherein the providing of the bias information comprises:
And provides the skew information to the vehicle image. The method according to claim 1,
Wherein the providing of the bias information comprises:
Calculating a width of the license plate area, and calculating the degree of detachment using a ratio obtained by dividing the width by the reference coordinates. The method according to claim 1,
The reference line may include:
A vertical line intersecting the coordinate point corresponding to the y-axis coordinate of the license plate coordinate among the coordinates constituting the critical lane determined by the lane mapped to the vehicle image,
The critical lane may include:
The width of the mapped lane is set so as to have a width of a set ratio with respect to the width of the mapped lane. The method according to claim 1,
The reference line may include:
A lane line detected from the vehicle image or a reference line selected from a user. The method according to claim 1,
The reference line may include:
Wherein the left or right end of the vehicle image. The method according to claim 1,
Comparing the calculated deviation information of the vehicle with a plurality of pre-stored skew levels, and classifying the skew levels to which the vehicle belongs for each of the skew levels; And
Further comprising searching and providing vehicle image or vehicle information corresponding to the selected level when one of the plurality of shift levels is selected from the user. A license plate detecting unit for detecting license plate area from the vehicle image acquired from the camera of the road;
A coordinate detector for detecting coordinates of at least one license plate corresponding to the license plate area; And
And a skew information providing unit that provides skew information corresponding to a degree of deviation of the license plate coordinates in a predetermined direction based on reference coordinates corresponding to the reference line. The method of claim 9,
Further comprising a number recognizing section for recognizing the vehicle number of the vehicle from the license plate area,
The skew information providing unit,
The shift information, and the vehicle number to the vehicle image and stores the same. The method of claim 9,
The skew information providing unit,
And provides the skew information matching with the vehicle image to provide the skew detection information. The method of claim 9,
Wherein the providing of the bias information comprises:
Calculating a width of the license plate area, and calculating the degree of detachment using a ratio obtained by dividing the width by the reference coordinates. The method of claim 9,
The reference line may include:
A vertical line intersecting the coordinate point corresponding to the y-axis coordinate of the license plate coordinate among the coordinates constituting the critical lane determined by the lane mapped to the vehicle image,
The critical lane may include:
The width of the mapped lane is set so as to have a width of a set ratio with respect to the width of the mapped lane. The method of claim 9,
The reference line may include:
And a reference line selected from a lane line detected by the vehicle image or a user. The method of claim 9,
The reference line may include:
Wherein the left or right end of the vehicle image. The method of claim 9,
An analysis unit for comparing the calculated shift information of the vehicle with a plurality of pre-stored shift amounts for each of the plurality of vehicles, and classifying the shift level to which the vehicle belongs for each of the plurality of shift amounts; And
Further comprising: a search unit for searching for and providing vehicle image or vehicle information corresponding to the selected level when one of the plurality of shift levels is selected from the user.
KR1020150071871A 2015-05-22 2015-05-22 Method for detecting biased vehicle and apparatus thereof KR101690136B1 (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108022427A (en) * 2017-10-30 2018-05-11 深圳市赛亿科技开发有限公司 A kind of recognition methods of fake license plate vehicle and system
CN108417046A (en) * 2018-04-28 2018-08-17 上海与德科技有限公司 Driving behavior monitoring method, traffic monitoring method, apparatus, terminal and medium
CN110459064A (en) * 2019-09-19 2019-11-15 上海眼控科技股份有限公司 Vehicle illegal behavioral value method, apparatus, computer equipment

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KR101322162B1 (en) * 2013-07-09 2013-10-28 한국비전기술(주) Method for detection using detection system of vehicles
KR101517181B1 (en) * 2014-02-28 2015-05-04 주식회사 코아로직 System and method for warning lane departure

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Publication number Priority date Publication date Assignee Title
KR101153981B1 (en) * 2011-12-14 2012-06-08 주식회사 디아이랩 Video monitoring service method
KR101322162B1 (en) * 2013-07-09 2013-10-28 한국비전기술(주) Method for detection using detection system of vehicles
KR101517181B1 (en) * 2014-02-28 2015-05-04 주식회사 코아로직 System and method for warning lane departure

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Publication number Priority date Publication date Assignee Title
CN108022427A (en) * 2017-10-30 2018-05-11 深圳市赛亿科技开发有限公司 A kind of recognition methods of fake license plate vehicle and system
CN108417046A (en) * 2018-04-28 2018-08-17 上海与德科技有限公司 Driving behavior monitoring method, traffic monitoring method, apparatus, terminal and medium
CN110459064A (en) * 2019-09-19 2019-11-15 上海眼控科技股份有限公司 Vehicle illegal behavioral value method, apparatus, computer equipment

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