A method for automatic vehicle tracking and driving based on image processing

An automatic tracking and driving method technology, which is applied in the field of automatic vehicle tracking and driving based on image processing, can solve the problems of low sampling efficiency and large amount of calculation, and achieve the effect of simple carrying equipment, accurate tracking position, and alleviating long-distance fatigue

Active Publication Date: 2019-04-26
大连波塞冬汽车电子科技有限公司
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AI Technical Summary

Problems solved by technology

However, the conventional particle filter tracking algorithm has problems such as large amount of calculation and low sampling efficiency, and due to the complexity of the actual tracking scene, it poses great challenges to the conventional particle filter tracking algorithm.

Method used

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  • A method for automatic vehicle tracking and driving based on image processing
  • A method for automatic vehicle tracking and driving based on image processing
  • A method for automatic vehicle tracking and driving based on image processing

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Experimental program
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Embodiment Construction

[0052] The present invention will be further described in detail below in conjunction with the examples.

[0053] A camera is set directly in front of the vehicle to collect images of the vehicle in front.

[0054] Template making and matching:

[0055] First, select the license plate area of ​​the vehicle in front that needs to be tracked in the front camera. The target image with the license plate of the front vehicle is used as a template. Convert the image to HSV space and calculate the histogram of the Hue space in this area. , the chromaticity space is one of the three components of the HSV color space, color, saturation, and value, and the conversion formula with the traditional RGB color space is:

[0056]

[0057] Among them, R, G, and B are the information in the RGB space of the original image, max is the maximum value in RGB, and min is the minimum value in RGB.

[0058] According to the formula, by converting the RGB of the target area into the h space in HSV...

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Abstract

The invention relates to an image processing-based automatic vehicle tracking driving method, comprising the following steps: setting a target vehicle image area as an interest area; converting the RGB color space of the interest area in the current frame image into an HSV color space; Perform histogram statistics on the HSV color space to obtain the histogram vector; collect the next frame image and perform particle filtering according to the histogram vector matching to obtain the position of the target vehicle; control the position of the target vehicle according to the displacement difference between the next frame and the current frame image The vehicle follows the target vehicle. The present invention is based on the image processing technology, based on the long-distance long-distance driving of multiple vehicles at the same time, which can relieve the long-distance fatigue of the drivers behind the vehicle and reduce the situation of vehicle accidents. At the same time, the equipment is simple to carry, and only the front-facing camera and the vehicle-mounted intelligent terminal are needed, that is, Automatic driving of the following vehicle can be easily realized.

Description

technical field [0001] The invention relates to a vehicle semi-automatic driving method, in particular to an image processing-based automatic vehicle tracking driving method. Background technique [0002] The airborne optoelectronic stable tracking system based on detection and search, capture and tracking, and laser aiming has become one of the strategic bases for the development of a new generation of optoelectronic equipment, which is of great significance to modern production and life. In the airborne electro-optical stabilization tracking system, image tracking is a key technology, which directly determines the performance of the tracking system. At the same time, image tracking is also a hot research issue in the field of computer vision, and has a wide range of applications in the fields of visual monitoring, human-computer interaction, and robot navigation. [0003] Image tracking methods can be roughly divided into two categories: probabilistic tracking methods and...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06T7/254
CPCG06T2207/30252G06T2207/20024G06V20/584G06V2201/08
Inventor 田雨农范玉涛周秀田于维双陆振波
Owner 大连波塞冬汽车电子科技有限公司
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