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

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...

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.

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