自动化学报2009，Vol.35Issue(4)：350-355,6.DOI:10.3724/SP.J.1004.2009.00350
采用精选Gabor小波和SVM分类的物体识别
Gabor Wavelet Selection and SVM Classification for Object Recognition
摘要
Abstract
This paper proposes a Gabor wavelets and support vector machine (SVM)-based framework for object recognition. When discriminative features are extracted at optimized locations using selected Gabor wavelets, classifications are done via SVM. Compared to conventional Gabor feature based object recognition system, the system developed in this paper is both robust and efficient. The proposed framework has been successfully applied to two object recognition applications, i.e., object/non-object classification and face recognition. Experimental results clearly show advantages of the proposed method over other approaches.关键词
Gabor feature/support vector machine (SVM)/object recognitionKey words
Gabor feature/support vector machine (SVM)/object recognition分类
信息技术与安全科学引用本文复制引用
沈琳琳,纪震..采用精选Gabor小波和SVM分类的物体识别[J].自动化学报,2009,35(4):350-355,6.基金项目
Supported by National Natural Science Foundation of China(60572100, 60673122), Royal Society (U.K.) International Joint Projects 2006/R3-Cost Share with NSFC (60711130233), ScienceFoundation of Shenzhen City (CXQ2008019, 200706), and Scientific Research Foundation for the Returned Overseas Chinese Scholars,State Education Ministry (2008[890]) （60572100, 60673122）
