Title :
Face Recognition Based on Modified Modular Principal Component Analysis
Author_Institution :
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Abstract :
The technology of face recognition has been widely applied to many fields such as identity authentication. A New Improvement for Face Recognition Using MMPCA is presented in this paper. The proposed algorithm when compared with conventional modular PCA algorithm is different in the computation of image mean value and the recognition process. Comparison of the two algorithms in different face databases proves that the proposed algorithm is more effective and robust than conventional modular PCA algorithm under the large variations in lighting direction and facial expression. The authors also point out that 2DPCA is a special case of improved algorithm, no matter in the process of dimension reduction or recognition.
Keywords :
face recognition; principal component analysis; MMPCA; dimension reduction; face recognition; facial expression; identity authentication; image mean value; modified modular principal component analysis; modular PCA algorithm; Algorithm design and analysis; Computer science; Data preprocessing; Educational institutions; Face recognition; Image recognition; Internet; Machine learning algorithms; Principal component analysis; Robustness; Face Recognition; Modular Principal Component Analysis; Principal Component Analysis;
Conference_Titel :
Internet Computing for Science and Engineering (ICICSE), 2009 Fourth International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-6754-9
DOI :
10.1109/ICICSE.2009.29