Vision-based Vehicle Type Classification Using Partial Gabor Filter Bank

摘要：

A vision-based vehicle type classification method using partial Gabor filter bank is present in this paper for five vehicles categorization: sedan, van, hatchback sedan, bus and van truck. To reduce the influence caused by the hues of vehicles, we extract the Gabor features from the edge image of vehicle, instead of from the grey image. Partial Gabor filter bank approach, which can save memory and computation cost significantly, is introduced and a new partial sampling method is proposed. The experimental results show that the recognition rate reaches 95.17％ using partial Gabor features, illustrating the effectiveness of the proposed approach.

关键词： Vehicle classification Gabor filter ITS

作者: Peijin Ji Lianwen Jin Xutao Li

作者单位: School of Electronic and Information Engineering South China University of Technology, No.381 Wushan Road, Guangzhou, China. 510640

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）