| 摘 要: 随着道路监控系统的数字化和智能化发展，车辆类型识别成为智能交通系统的研究重点之一。本文基于道路监控系统中的视频图像，对车前脸进行粗定位，并在粗定位车脸的基础上对车脸进行精确定位。对精确定位的车前脸进行水平梯度水平投影和水平梯度垂直投影，提取车标的方向梯度直方图——HOG特征，由此提出了基于HOG特征描述的车脸特征点提取方法，并采用支持向量机(SVM)对车标特征向量进行了分类识别。实验结果表明，只有选择适当的HOG特征参数，才能提高车型识别率。 |
| 关键词: 车脸识别；视频识别；方向梯度直方图；支持向量机 |
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中图分类号: TP311.5
文献标识码: A
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| 基金项目: 2021年江苏省现代教育技术研究“应用型网络安全人才的教学模式创新研究”(2021-R-93916). |
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| Research on Vehicle Face Recognition Method based on Histogram of Oriented Gradients Features |
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QU Aiyan1,2, ZHANG Zheng1, LIANG Yinghong1, WU Qiuling1, HUANG Xiaoting3
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( 1.College of Network Security, Jinling Institute of Technology, Nanjing 211169, China ;
2.College of Command and Control Engineering, Army Engineering University, Nanjing 210001, China ;
3.College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China )
quaiyan@jit.edu.cn; zhangzheng@jit.edu.cn; liangyh@jit.edu.cn; Wuqiuling@jit.edu.cn; 934246903@qq.com
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| Abstract: With the digital and intelligent development of road monitoring system, vehicle type recognition has become one of the research focuses of intelligent traffic systems. Based on video images of the road monitoring system, this paper proposes to roughly locate the front face of the car, and then accurately locate the face of the car on the basis of the rough positioning. Based on the horizontal gradient horizontal projection and the horizontal gradient vertical projection of the accurately located front face, Histogram of Oriented Gradients (HOG) feature of the vehicle logo is extracted. Thus, a car face feature point extraction method based on the HOG feature description is proposed, and the vehicle logo feature vector is classified and recognized by Support Vector Machine (SVM). Experimental results show that only by selecting proper HOG feature parameters can the vehicle recognition rate be improved. |
| Keywords: car face recognition; video recognition; HOG; SVM |
