Vehicle Detection System Based on Image Processing

doi:10.13438/j.cnki.jdzk.2019.05.004

Abstract

Abstract:

To obtain traffic information and dispose of traffic accidents in time, and ultimately reduce accidents frequency to a certain extent, a vehicle detection system based on HOG and SVM was designed. Firstly, a large number of vehicle samples were collected to build positive and negative sample sets, and then HOG feature vectors of all these samples were extracted and summarized. Finally, the SVM classifier template was formed. In the video detection process, the HOG features of each frame in the video were extracted and compared with the template that has been trained, and the detected vehicle targets were tagged with a rectangular frame. The actual road monitoring video was adopted to test the vehicle detection system, and the results demonstrated that the algorithm designed shows real-time performance, accuracy, and applicability for different road conditions, different weather and different illumination.

Key words: target detection, histogram of oriented gradient, support vector machine, vehicle detection

QIU Guoshu, ZHANG Xiang, LIU Jun, WANG Lei, TIAN Qing, GUO Jianhua. Vehicle Detection System Based on Image Processing[J]. Journal of Jishou University（Natural Sciences Edition), DOI: 10.13438/j.cnki.jdzk.2019.05.004.

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