Facial feature eztraction with weighted modular twodimensional PCA
Feature extraction is a key step in the process of face recognition. Principal Component Analysis (PCA), one of the methods to carry out feature extraction, is widely applied to the field of image recognition. Having studied traditional PCA and several extended measures, a method named weighted modular two-dimensional PCA is proposed in this paper. In this method, a two-dimensional face image is firstly divided into three parts. And then perform feature extraction respectively on these three parts. Finally endow different parts with unequal weights in classification. Experimental results illustrate the feasibility and effectiveness of the proposed algorithm.
face recognition feature eztraction PCA scatter matriz WM-2DPCA
Lijing Zhang Ying Zhang
Network Administration Center North China Electric Power University Baoding, 071003, Hebei Province, Department of Computer Science North China Electric Power University Baoding, 071003, Hebei Province
国际会议
上海
英文
1992-1995
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）