REAL-TIME TRAFFIC LIGHT RECOGNITION BASED ON C-HOG FEATURES

被引:4
|
作者
Zhou, Xuanru [1 ]
Yuan, Jiazheng [2 ]
Liu, Hongzhe [1 ]
机构
[1] Beijing Union Univ, Beijing Key Lab Informat Serv, Beijing 100101, Peoples R China
[2] Beijing Open Univ, Sci Res Off, Beijing 100081, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
C-HOG features; SVM; traffic light recognition; intelligent vehicles;
D O I
10.4149/cai_2017_4_793
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a real-time traffic light detection and recognition algorithm that would allow for the recognition of traffic signals in intelligent vehicles. This algorithm is based on C-HOG features (Color and HOG features) and Support Vector Machine (SVM). The algorithm extracted red and green areas in the video accurately, and then screened the eligible area. Thereafter, the C-HOG features of all kinds of lights could be extracted. Finally, this work used SVM to build a classifier of corresponding category lights. This algorithm obtained accurate real-time information based on the judgment of the decision function. Furthermore, experimental results show that this algorithm demonstrated accuracy and good real-time performance.
引用
收藏
页码:793 / 814
页数:22
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