Fast detection and ranging algorithm of blind track obstacles for embedded system application

• Published in: Journal of electronic imaging 2022-03, Vol.31 (2), p.023031-023031
• Main Authors: Han, Dong-Nuo, Sun, Hong-Mei, Li, Yong-Chao, Zhong, Hai-Feng, Jia, Rui-Sheng
• Format: Article
• Language: English
• ISSN: 1017-9909; 1560-229X
• DOI: 10.1117/1.JEI.31.2.023031

Blind track scene has high complexity, and the existing target detection algorithm model is large, which cannot be directly applied to lightweight embedded platform, and it is easy to miss detection for small obstacles in long distance. To solve these problems, a real-time detection and ranging method of blind obstacles based on binocular vision is proposed. The method includes two stages: blind-track obstacle detection and blind-track obstacle ranging. In the obstacle detection stage, considering the requirements of embedded applications for model size and computing speed, a lightweight target detection network is designed. The network uses the deep separable convolution unit to extract the features of the blind road obstacles, and adds the channel attention module to filter and filter out high-quality feature information, so as to realize the fast detection of the blind road obstacles. To solve the problem of missed detection of long-distance small targets and obstacles, a multi-scale features fusion module is designed at the end of the network, which strengthens the detection ability of small targets of complex blind track scenes. In the obstacle ranging stage, an improved algorithm enhanced-speeded up robust features (ENH-SURF) based on binocular video is proposed to realize the real-time ranging of blind obstacles. Experimental results show that the detection accuracy of the detection algorithm is 83.2% in the blind road obstacle data set, and the evaluation indicators, such as model size and FPS, are better than the comparison algorithm. The distance measurement method is within range of 5 m, and the average relative error is 2.77%, which can meet the application needs of the blind.