中国光学2018，Vol.11Issue(2)：174-181,8.DOI:10.3788/CO.20181102.0174
基于改进HOG特征提取的车型识别算法
Vehicle type recognition algorithm based on improved HOG feature
摘要
Abstract
Aiming at problems of vehicle type recognition in high-speed environment,an improved HOG algo-rithm based on oriented steerable filter is proposed in this paper. Vehicle image features are extracted by com-bining the oriented steerable filter algorithm and HOG algorithm. The principle component analysis(PCA) is used to reduce dimensions of the eigenvector for decreasing the computational complexity. The support vector machine(SVM) algorithm is used to train the extracted features to realize the recognition of vehicle′s appear-ance features. The simulation results indicate that average vehicle type recognition accurate of proposed algo-rithm reaches 92.36%. At the same time, the recognition speed is 3.45% higher than the traditional HOG feature algorithm. In conclusion,the proposed algorithm can effectively improve the efficiency of vehicle type recognition and is therefore better than the traditional HOG algorithm.关键词
车型识别/HOG特征/方向可控滤波器Key words
vehicle type recognition/HOG feature/steerable filter分类
信息技术与安全科学引用本文复制引用
耿庆田,赵浩宇,于繁华,王宇婷,赵宏伟..基于改进HOG特征提取的车型识别算法[J].中国光学,2018,11(2):174-181,8.基金项目
吉林省省级产业创新专项资金项目(No.2016C078) （No.2016C078）
吉林省产业技术研究和开发专项项目(No.2017C031-2) （No.2017C031-2）
吉林省教育厅"十三五"科学技术研究项目(No.2018269)Supported by Jilin Provincial Industrial Innovation Special Fund Project(No.2016C078) （No.2018269）
Jilin Provincial Indus-trial Technology Research and Development Special Project(No.2017C031-2) （No.2017C031-2）
Jilin Province Education Depart-ment:the 13th Five-year Plan Science and Technology Research Project(No.2018269) （No.2018269）
