WO2017116134A1

WO2017116134A1 - Radar and image-fusion vehicle enforcement system

Info

Publication number: WO2017116134A1
Application number: PCT/KR2016/015387
Authority: WO
Inventors: 최광호; 이상만; 심광호; 류승기; 조영태
Original assignee: 건아정보기술 주식회사
Priority date: 2015-12-30
Filing date: 2016-12-28
Publication date: 2017-07-06

Abstract

In an embodiment, provided is a multilane vehicle speed measurement system comprising: a radar for emitting radio waves at a multilane road and receiving reflected waves reflected from vehicles traveling on the multilane road; a camera triggered by the presence of a speeding vehicle, detected by the radar, so as to capture images of the vehicle as a target vehicle with a time difference with respect to the lane at which the target vehicle is located; and a control unit for calculating a first vehicle speed on the basis of information on the target vehicle from the radar, calculating a second vehicle speed on the basis of information from the camera, and comparing the first vehicle speed and the second vehicle speed so as to calculate an average speed of the target vehicle. Therefore, the images of a specific vehicle among the vehicles on the multiple lanes are captured through one camera such that demand for the cameras can be reduced. In addition, a case, in which the speed detected by the radar and a speed obtained according to image analysis do not match and a difference therebetween is not within an error range, is treated as an error, and the speed obtained according to image analysis is transmitted to a control center, thereby providing an effect of eliminating a speed error.

Description

Radar and Image Fusion Vehicle Enforcement System

The present invention relates to a radar and image fusion vehicle enforcement system.

More specifically, the present invention relates to a radar and image fusion vehicle control system using an image captured by one camera and a radar for a vehicle on a multi-lane.

As traffic accidents caused by speeding can develop into life-threatening accidents that can cause fatal damage to drivers, various studies on speed detection devices using advanced equipment such as radar equipment to prevent speeding of vehicles or to detect speeding vehicles are being conducted. In addition, such a speed detection device is installed throughout the road due to the advantage that can detect the speeding vehicle unattended, the use field is expanding.

Currently, a method of measuring information and speed of a vehicle in a domestic ITS system includes a method of embedding a LOOP detector on a road, using a laser sensor, and acquiring information only through an image through a camera.

However, LOOP detector has the disadvantage that the road must be destroyed in the process of embedding on the road, and it can be a factor that hinders the flow of the vehicle in the process of construction.

In addition, it is difficult to obtain proper data on a vehicle changing lanes.

Laser detectors also suffered from the effects of weather and climate (snow, rain, fog, dust, etc.) and had a narrow detection width.

In addition, the image detector also has a disadvantage that is affected by the weather and climate much, especially the detection rate is greatly reduced at night.

On the other hand, radar detectors are relatively less affected by weather and climate than other detectors, and are non-contact, so there is no road destruction.

In addition, since the detection is extensive, it is also possible to detect a vehicle changing lanes, which is a disadvantage of the LOOP or laser detector.

The information output from the radar detector is the speed, distance, and angle of the vehicle. Through this, the exact position and information of the vehicle can be extracted.

However, since the radar also uses radio waves, errors may occur due to the radio wave environment, thereby providing a method of simultaneously using the radar and the image.

However, if the vehicle is multi-lane, a dedicated camera is required for each lane, and images of all of the plurality of cameras must be read to capture the speed of a specific vehicle detected by the radar. Inevitable

In addition, since the position and the error of the actual vehicle may occur according to the position of the image, correction is required.

The present invention provides a system that can calculate the speed of a vehicle accurately by using a radar and an image through a camera when calculating the speed of a vehicle on a multi-lane.

In addition, the present invention provides a system that can reduce the data processing capacity by using the image through the radar and one camera when calculating the speed for the vehicle on the multi-lane.

According to an embodiment of the present invention, a radiation beam is emitted to a multi-lane road, and radar transmission and reception means for receiving a reflected wave reflected from a vehicle traveling on the multi-lane road is triggered by the presence of a target vehicle sensed at high speed by the radar transmission and reception means. Image capturing means for photographing a full frame image including a multi-lane road and the target vehicle, a radar speed calculator configured to generate the driving information for the target vehicle by analyzing the transmitted and received radar signals, and analyzing the driving information of the target vehicle. Determine the location of the target vehicle in the full frame image on the multi-lane road, crop the area in which the vehicle is located in the full-frame image on the multi-lane road, and store the first cropping image; Recognizes the license plate of the target vehicle from a first cropping image and crops an area where the license plate is located And a control unit including an image processing unit for storing the second cropping image as a second cropping image, and a number recognition unit for recognizing the number of the vehicle license plate in the second cropping image.

The image processing unit may further include an image speed calculator configured to receive images captured at a predetermined time interval from the image processor and calculate a vehicle speed.

The image velocity calculating unit converts a first coordinate value occupied by the target vehicle in the first cropping image coordinate system into a second coordinate value occupied in the full frame image coordinate system, and calculates a moving distance according to time of the second coordinate value. To calculate the speed of the vehicle.

An image taken at a predetermined time interval by defining the traveling speed of the target vehicle measured by the radar transmission and reception means from the radar speed calculating unit as a first vehicle speed, and receiving the position of the license plate determined by the image processing unit of the target vehicle. When the number of pixels of the moving vehicle number is defined and defined as the second vehicle speed, when both the first vehicle speed, the second vehicle speed, and the second vehicle speed after a predetermined time elapse from the threshold speed, It may include an intermittent determination unit to determine.

The control unit defines the first vehicle speed as the average speed when the deviation between the first vehicle speed and the second vehicle speed is less than a first threshold value, and the deviation between the first vehicle speed and the second vehicle speed is determined. If the range of the second threshold value is satisfied, the average value of the first vehicle speed and the second vehicle speed is defined as the average speed, and if the deviation exceeds the range of the second threshold value, the speed of the target vehicle is discarded. Can be.

The image photographing means may vary a time difference according to the speed of the first vehicle and capture an image of the target vehicle.

The embodiment emits a radar to measure the speed of all the vehicles traveling in the detection zone, and by taking a picture of a specific vehicle of the multi-lane vehicle through one camera, it is possible to reduce the demand of the camera . In addition, by cutting the image of the specific vehicle from the image taken from the camera into the recognition region and reading only the recognition region, the data processing capacity can be reduced, thereby improving the computation speed and reducing the computation amount.

In addition, the embodiment may calculate the speed using only the image of the recognition area, compensate for horizontal and vertical errors that may occur according to the coordinates when calculating the speed, and compensate the error according to the characteristics of the license plate to accurately calculate the speed from the image. Can improve the reliability.

In addition, if the speed detected by the radar and the speed according to the video analysis do not coincide with each other and do not exist within the error range, it is treated as an error and the speed of the video analysis is sent to the control center, thereby eliminating the speed error. to provide.

1 is an overall configuration diagram of a multi-lane vehicle speed measurement system according to an embodiment of the present invention.

FIG. 2 is a detailed block diagram of a multi-lane vehicle speed measuring system according to an embodiment of the present invention of FIG. 1.

3 is a block diagram illustrating an exemplary embodiment of the controller of FIG. 2.

4 is a flowchart illustrating a speed calculating method of the controller.

5 is a diagram illustrating a step of acquiring a recognition region of an image velocity calculating unit.

6 is a flowchart illustrating correction of the recognition region of FIG. 4.

FIG. 7 is a diagram showing obtaining the coordinates of FIG.

8 is a diagram illustrating obtaining a reverse vehicle reference coordinate of FIG. 6.

9 is a detailed flowchart illustrating license plate correction of FIG. 6.

FIG. 10 is a diagram illustrating an operation of extracting a license plate feature of FIG. 9.

FIG. 11 is a diagram illustrating a vehicle model analysis of FIG. 9.

FIG. 12 is a view showing the license plate height measurement of FIG.

As the invention allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present invention to specific embodiments, it should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention. In describing the drawings, similar reference numerals are used for similar elements.

Terms such as first, second, A, and B may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component. The term and / or includes a combination of a plurality of related items or any item of a plurality of related items.

When a component is referred to as being "connected" or "connected" to another component, it may be directly connected to or connected to that other component, but it may be understood that other components may be present in between. Should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that there is no other component in between.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting of the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this application, the terms "comprise" or "have" are intended to indicate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, and one or more other features. It is to be understood that the present invention does not exclude the possibility of the presence or the addition of numbers, steps, operations, components, components, or a combination thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in the commonly used dictionaries should be construed as having meanings consistent with the meanings in the context of the related art and shall not be construed in ideal or excessively formal meanings unless expressly defined in this application. Do not.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is an overall configuration diagram of a multi-lane vehicle speed measurement system 10 according to an embodiment of the present invention, Figure 2 is a multi-lane vehicle speed measurement system 10 according to an embodiment of the present invention of FIG. 3 is a block diagram illustrating an embodiment of the controller 100 of FIG. 2.

Referring to FIG. 1, the multi-lane vehicle speed measuring system 10 according to an embodiment of the present invention emits radiation waves on a multi-lane road and receives reflected waves reflected from the vehicle 20 traveling on the multi-lane road. The radar 300, one camera 200 for capturing an image of the vehicle 20 sensed by the radar 300, and a speed of the first vehicle 20 from the radar 300. And a controller 100 for calculating, correcting and comparing the second vehicle speed from the camera 200 to calculate the final speed of the vehicle 20.

The radar 300 has a short period and emits the radiation wave, and the camera 200 triggers when the speeding vehicle 20 is recognized as a target by the radiation wave obtained from the radar 300. Then, the photographing is performed twice based on the lane in which the target vehicle 20 is located among the multi lanes.

The control unit 100 receives the reflected wave from the radar 300, reads the radar speed calculation unit 110 for calculating the first vehicle speed of the vehicle 20, and receives an image from the camera 200, An image speed calculator 120 that calculates a second vehicle speed of the vehicle 20 by processing and correcting the same, and a final speed calculator 130 that receives the first vehicle speed and the second vehicle speed and compares them to obtain a final speed. ).

In detail, the radar speed calculating unit 110 obtains information on the emission point of the radiation wave and the reception point of the reflected wave from the radar 300 to calculate distance information of the vehicle 20 spaced apart from the radar 300 to obtain distance information. The speed information is extracted from the first vehicle speed, and the speed information 20 is recognized as the speed vehicle 20 when the first vehicle speed exceeds a critical speed (intermittent speed). When the speeding vehicle 20 is defined as the target vehicle 20, the camera 200 is triggered to capture a full frame image including the target vehicle 20 twice.

In addition, the controller 100 analyzes the driving information of the target vehicle 20 to determine the position of the target vehicle 20 in the full frame image on the multi-lane road, and the full frame image on the multi-lane road. Crop the area in which the vehicle is located and store it as a first cropping image, recognize the license plate of the target vehicle 20 from the first cropping image, and crop the area where the license plate is located. It may further include an image processor (not shown) for storing as two cropping images.

The image processor crops an area in which the target vehicle 20 is located from the two images to obtain a region of interest (ROI) of two first cropped images.

The image processor recognizes a vehicle license plate from the two first cropping images and the first cropping image, and determines the number and position of the vehicle license plate. In this case, the license plate position may be defined as a reference point of a point in the license plate of the target vehicle 20. For example, the reference point may be the center of the license plate, and when the license plate is rectangular, it may be one of four corners.

In addition, the control unit 100 defines the traveling speed of the target vehicle measured by the radar transmission and reception means from the radar speed calculating unit as a first vehicle speed, and transmits the position of the license plate determined by the image processing unit of the target vehicle. The first vehicle speed, the second vehicle speed, and the second vehicle speed after a predetermined time elapse, when the number of pixels of the moved vehicle number is counted and defined as the second vehicle speed in the images photographed at predetermined time intervals. If it is out of the speed may further include an enforcement decision unit (not shown) that is determined to be subject to enforcement.

The apparatus may further include a number recognition unit (not shown) that recognizes the number of the vehicle license plate in the second cropping image.

The image velocity calculating unit 120 converts the first coordinate value occupied by the target vehicle 20 in the first cropping image coordinate system into a second coordinate value occupied in the full frame image coordinate system, and the time of the second coordinate value. Calculate the speed of the vehicle by calculating the distance traveled by

That is, the image speed calculating unit 120 may include an image correcting unit 125 that corrects coordinates of the position of the recognition area within the entire image and corrects it according to the feature of the license plate serving as a reference point.

The image speed calculator 120 may calculate a second vehicle speed based on the corrected second coordinate values from the image corrector 125.

The second vehicle speed may be calculated based on a distance between two corrected second coordinate values for a time difference between two images.

The final speed calculator 130 compares the first vehicle speed with the second vehicle speed to determine whether the two vehicle speeds match each other, whether the first vehicle speed by the radar 300 and the second vehicle speed by the camera 200 are determined. It is determined whether is within the error range to calculate the final speed.

The control unit 100 includes a communication unit 150 for transmitting the calculated final speed and vehicle information to the control center 400 in real time, and stores the captured image, vehicle number, average speed, date, time data Memory 140.

The control center 400 receives vehicle information and final speed information about the speeding vehicle 20 from the multi-lane vehicle 20 speed detection system 10, and displays a vehicle number and an average on the image screen of the vehicle 20. It includes a server that displays and stores speed, date, and time data in a defined area.

Hereinafter, the operation of the multi-lane vehicle 20 speed measurement system 10 according to the present invention will be described in detail.

4 is a flowchart illustrating a speed calculating method of the controller 100, and FIG. 5 is a diagram illustrating a step of obtaining a recognition region of the image speed calculating unit 120.

First, the radar 300 periodically receives a carrier wave and calculates it to generate a first vehicle speed (S110). If it is determined that the first vehicle speed of the vehicle 20 calculated by the radar speed calculating unit 110 exceeds a threshold speed (interruption speed) (s120), the vehicle 20 is defined as the target vehicle 20. In this case, the critical speed may be an intermittent speed of the corresponding multi-lane road.

When the target vehicle 20 is defined, the lane in which the target vehicle 20 is located is recognized (S130), and one camera 200 disposed on the multi-lane road is triggered to adjust the time difference so that the target vehicle 20 is included. Photographing is performed two times (s140).

As an example, two images taken two times may be obtained with a time difference of 80 msec as shown in FIGS. 5A and 5B.

In this case, the time difference may vary according to the first vehicle speed, and may have a time difference of 160 msec when it is 60 km / h or less, and may have a time difference of 120 msec when it is 60 km / h to 80 km / h, and 80 km / h to In the case of 100 km / h, it may have a time difference of 80 msec, and in the case of 100 km / h or more, it may have a time difference of 40 msec.

The image processor obtains vehicle number information of the target vehicle 20 from the two images, and crops an area where the target vehicle 20 is disposed to the recognition area (S150).

That is, as shown in FIGS. 5A and 5B, an area defining the position of the target vehicle 20 is obtained from the recognition area of the radar 300 distance information defined by the red line, and the recognition area including the same is cut out to be a signal processing target. define.

In this case, the size of the recognition area may be adjusted according to the size of the area defining the location of the target vehicle 20 and the size of the vehicle 20 in the image.

5A and 5B, it can be seen that the position of the recognition area is moved according to the speed of the vehicle 20 in two images having a time difference.

The image correcting unit 125 of the image speed calculating unit 120 performs vertical correction and horizontal correction according to the position of the entire image of the recognition area, performs correction with respect to the license plate, and corrects the coordinates of the reference point. It generates (s160).

At this time, the vertical and horizontal correction is to correct the error caused by the difference in perspective as the three-dimensional space is converted to the two-dimensional image, the position of one pixel in the image is located above or below the image. Different distances are displayed depending on whether the image is different from each other.

Therefore, by correcting these errors and performing vertical and horizontal correction, accurate coordinates can be obtained without errors from perspective even if data is read only for the recognition region, not the entire image.

The correction will be described later in detail.

The image speed calculator 120 calculates a second vehicle speed of the target vehicle 20 from the image based on the corrected coordinate value (S170).

Next, the final speed calculator 130 calculates the final speed by comparing the first vehicle speed with the second vehicle speed (S180).

The final speed calculator 130 calculates the speed deviation to define the final speed.

The speed deviation follows the equation

[Equation 1]

Speed deviation = (first vehicle speed / second vehicle speed) ?? 100

The final speed calculating unit defines the first vehicle speed as the speed of the target vehicle when the deviation between the first vehicle speed and the second vehicle speed is less than a first threshold value, and the first vehicle speed and the second vehicle speed. When the deviation of the value satisfies the range between the first threshold value and the second threshold value, the average value of the first vehicle speed and the second vehicle speed is defined as the speed of the target vehicle, and the deviation determines the second threshold value. If exceeded, the speed of the target vehicle may be discarded.

For example, when the first threshold value is 3% and the second threshold value is 7%, if the deviation between the first vehicle speed and the second vehicle speed is less than 3%, the final speed of the target vehicle is the first vehicle speed and the deviation Is 3% to 7%, the final speed of the target vehicle is the average of the first vehicle speed and the second vehicle speed. If the deviation exceeds 7%, the final speed of the target vehicle is determined to be an imaginary number that cannot be calculated. Process.

Finally, when the final speed for the target vehicle 20 is obtained, information about the target vehicle 20, that is, the vehicle number, time, location and the final speed, is transmitted to the control center 400 in real time and detected. End the operation.

As such, the number of the cameras 200 can be reduced by performing the speed of the vehicle 20 in the multi-lane through one radar 300 and one camera 200, and recognition of the data processing target in the captured image. Cropping areas can reduce data throughput and speed up processing.

Meanwhile, the multi-lane vehicle speed measuring system 10 of the present invention can calculate a more reliable speed by correcting errors that may occur in processing data by cropping the recognition area.

Hereinafter, the coordinate correction of the recognition area of FIG. 4 will be described in detail with reference to FIGS. 6 to 8.

6 is a flowchart illustrating correction of the recognition region of FIG. 4, FIG. 7 is a diagram illustrating obtaining the coordinates of FIG. 6, and FIG. 8 is a diagram illustrating obtaining the inverse vehicle reference coordinates of FIG. 6.

Referring to FIG. 6, in a state where a coordinate system in a full frame image and a coordinate system in a first cropping region are respectively defined, the image corrector 125 may determine an area of a region corresponding to the first cropping region in the full frame image coordinate system. A coordinate value is obtained (s161).

The coordinate values in the full frame image coordinate system of the first cropping region are basic data for correcting a distance error generated according to where the first cropping region is located in the full frame image.

Next, the vehicle reference coordinate value of the target vehicle 20 is obtained in the first cropping area coordinate system (S163).

The vehicle reference coordinate value may be a coordinate value of the license plate and may be one point or a plurality of points of the license plate. For example, as shown in FIG. 7, the coordinate values of the upper left corner and the lower right corner may be recognized as the vehicle reference coordinate.

Next, when the first cropping image is converted into a full frame image, two first cropping images t1 and first cropping images t2 taken at a time difference as shown in FIG. The batch moves (s165).

Next, the vehicle reference coordinate value in the first cropping area is obtained by converting the vehicle reference coordinate value into the coordinate value of the full frame video coordinate system (S167).

Thus, as shown in FIGS. 7 and 8, the y-axis coordinate value difference between the lower right corners of the two first cropping images from the two images having the time difference is 74 pixels. The coordinate difference is 124 pixels.

That is, the data processing is performed only by recognizing the coordinates of the recognition area, thereby increasing the computation speed and ensuring the accuracy of the data.

Next, vertical and horizontal corrections are performed to the full-frame video coordinate system (S168).

The vertical correction and the horizontal correction are performed by correcting the moving distance of the 3D real vehicle 20 from the 2D image by weighting the coordinate values in which region of the full frame image.

That is, by correcting an error occurring in the difference of perspective as the 3D space is converted into 2D image association, one pixel in the image has the same distance value, but the pixel is positioned up or down in the 2D image. The distance value of the corresponding pixel is different depending on whether the pixel is arranged at the position of the pixel, and the distance value is different depending on which position is disposed at the left or right side of the pixel.

Accordingly, the moving distance of the vehicle 20 may be calculated from the corrected full frame coordinate value by multiplying the reference value with weights according to the position of each pixel.

In this case, the image correction unit 125 may further perform license plate correction after performing vertical and horizontal correction to the full frame image coordinate value (S169).

FIG. 9 is a detailed flowchart illustrating license plate correction of FIG. 6, FIG. 10 is a diagram illustrating an operation of extracting license plate features of FIG. 9, FIG. 11 is a diagram illustrating a vehicle model analysis of FIG. 9, and FIG. 12 is a license plate of FIG. 9. This figure shows the height measurement.

Referring to FIG. 9, when the license plate correction starts, the image corrector 125 extracts features of the license plate of the target vehicle 20 from two captured images (S200).

At this time, the license plate features may be the size, color, aspect ratio, etc. of the license plate.

Next, vehicle type analysis of the target vehicle 20 is performed from the two captured images (S210). The vehicle model analysis is classified into a large, medium, and small vehicle 20 according to the size of the vehicle 20, and performs detailed vehicle classification.

That is, the vehicle 20 may be classified into a passenger car, a bus, a truck, and other vehicles 20, and the speed correction may be performed only for other vehicle types without performing speed correction in the case of a bus.

Next, the height d of the license plate is measured (s220).

The license plate height d may be defined as the shortest distance from the bottom of the vehicle 20, that is, from the bottom of the tire of the vehicle 20 to a reference point of the license plate, for example, the lower right corner of the license plate, and FIGS. 11A to 11D. As shown in FIG. 12A and FIG. 12B, different heights may be provided depending on the vehicle type, and even in the same vehicle type as shown in FIGS. 12A and 12B.

When the position analysis of the license plate is completed as described above, the vehicle 20 performs headlight position analysis (S230).

The headlight analysis may estimate the width of the vehicle 20 at intervals between the headlights to distinguish the large vehicle 20, and analyze the reference point position of the license plate from the headlight of the vehicle 20.

Next, the license plate coordinate correction is performed based on previously performed license plate features, vehicle type, license plate height, and headlight analysis contents (S240).

That is, when the license plate a and the license plate b of FIG. 10 are examined, the size of the license plate may be enlarged by 5 to 15% as the vehicle 20 approaches. Accordingly, the coordinate correction of the pixel may be performed by weighting the enlargement ratio, and the coordinate may be a reference point, for example, an edge or a center of the license plate.

In addition, the height (d) of the license plate from the ground may vary according to the arrangement of the vehicle model and the license plate as shown in Figs. 11 and 12 to generate the vertical error described above.

Therefore, the coordinates of the reference point that compensates for the error can be generated by weighting the vehicle according to the height of the model and the license plate. In this case, the weight may be given only when the height d of the license plate is greater than or equal to a threshold.

As such, the speed of the vehicle 20 may be calculated from the coordinates of the corrected reference point on which the license plate correction is performed, thereby obtaining data having improved reliability.

As mentioned above, although the preferred embodiment of this invention was described in detail with reference to attached drawing, this is only an illustration.

Those skilled in the art will appreciate that various modifications and changes can be made in the present invention without departing from the spirit and scope of the invention as set forth in the claims below.

Claims

Radar transmitting and receiving means for emitting radiation on a multi-lane road and receiving reflected waves reflected from a vehicle traveling on the multi-lane road;

Image capturing means for capturing a full frame image including the multi-lane road and the target vehicle triggered by the presence of a target vehicle detected by the radar transmitting / receiving means at speed;

A radar speed calculator configured to analyze the radar signals transmitted and received to generate driving information for the target vehicle;

Analyzing the driving information of the target vehicle to determine the position of the target vehicle in a full frame image on the multi-lane road, and cropping an area where the vehicle is located in the full-frame image on the multi-lane road An image processing unit for storing the first cropping image, recognizing the license plate of the target vehicle from the first cropping image, cropping an area where the license plate is located, and storing the cropping image as a second cropping image; and

A control unit including a number recognition unit recognizing a number of the license plate number in the second cropping image;

Radar and image fusion vehicle control system comprising a.
The method of claim 1,

And an image speed calculator configured to receive the images captured at a predetermined time interval from the image processor and calculate a speed of the vehicle.
The method of claim 2,

The image velocity calculating unit converts a first coordinate value occupied by the target vehicle in the first cropping image coordinate system into a second coordinate value occupied in the full frame image coordinate system, and calculates a moving distance according to time of the second coordinate value. Radar and image fusion vehicle enforcement system for calculating the speed of the vehicle.
The method of claim 5,

And the image photographing means changes the time difference according to the first vehicle speed and captures an image of the target vehicle.
Emitting radiation on a multi-lane road and receiving reflected waves reflected from a vehicle traveling on the multi-lane road,

Capturing a full frame image including the multi-lane road and the target vehicle triggered by the presence of the target vehicle detected at an excessive speed by the received reflected wave;

Generating driving information about the target vehicle by analyzing the transmitted and received radar signals;

Analyzing the driving information of the target vehicle to determine the position of the target vehicle in a full frame image on the multi-lane road, and cropping an area where the vehicle is located in the full-frame image on the multi-lane road Storing a first cropping image, recognizing the license plate of the target vehicle from the first cropping image, cropping an area where the license plate is located, and storing the cropping image as a second cropping image; and

Recognizing a number of the license plate number in the second cropping image;

Radar and image fusion vehicle control method comprising a.
The method of claim 5,

The radar and image convergence vehicle cracking method further comprising the step of receiving the images taken at a predetermined time interval, calculating the speed of the vehicle.
The method of claim 6,

Calculating the speed

Convert the first coordinate value occupied by the target vehicle in the first cropping image coordinate system to a second coordinate value occupied in the full frame image coordinate system, and calculate a moving distance according to time of the second coordinate value to calculate the speed of the vehicle. How to crack radar and image fusion vehicle.
The method of claim 7, wherein

Taking the image of the vehicle,

And radar and image convergence vehicle control method of capturing an image of the target vehicle while varying a time difference according to the first vehicle speed.