计算机工程Issue(2)：203-207,5.DOI:10.3969/j.issn.1000-3428.2014.02.044
基于多特征融合的前向车辆检测方法
Forward Vehicle Detection Method Based on Multi-feature Fusion
李星 1郭晓松 1郭君斌1
作者信息
- 1. 第二炮兵工程大学兵器发射理论与技术国家重点学科实验室，西安 710025
- 折叠
摘要
Abstract
A forward vehicle detection method based on multi-feature fusion is proposed in order to improve the accuracy of vehicle detection. The shadow and edge features of vehicle are segmented accurately by using histogram analysis method and adaptive dual-threshold method respectively. The initial candidates are generated by combining edge and shadow features and these initial candidates are further verified by using an integrated feature based on the fusion of symmetry, texture and shape matching degree features. A threshold is used to remove the non-vehicle initial candidates. Experimental results show that this method can adapt to different light conditions robustly with a detection rate over 92%. The proposed method is better than traditional methods based on learning with a higher detection rate and lower error rate.关键词
自适应双阈值/特征提取/多特征融合/Fisher 准则/前向车辆检测Key words
adaptive dual-threshold/feature extraction/multi-feature fusion/Fisher criterion/forward vehicle detection分类
信息技术与安全科学引用本文复制引用
李星,郭晓松,郭君斌..基于多特征融合的前向车辆检测方法[J].计算机工程,2014,(2):203-207,5.
