Isomap algorithm based on 2D Gabor wavelets and 2DPCA

摘要：

Compared with gray feature, the Gabor feature is more effective for facial image representation. But in practice, the dimension of a Gabor feature is so high that the computation is prohibitively large. In this paper, We use the two-dimensional principal component analysis (2DPCA) to reduce the dimension and then replace the original gray feature with the Gabor feature vector of reduced dimension as the front-end input of traditional Isometric Mapping(lsomap) algorithm. The validity of this method can be verified by experimental results.

关键词： 2D Gabor wavelets 2D principal component analysis Isomap algorithm

作者: Chanchan Qin Hongbo Xu Lihua Wang Huijuan Zhang Guoqing Li

作者单位: College of Physical Science & Technology HuaZhong Nonnal University Wuhan, China Information Management Center Bijie University Bijie, China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 773-776

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）