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The Suggestion of LINF Algorithm for a Real-time Face Recognition System  

Jang Hye-Kyoung (Dept. of Electronic Eng., Dong-A University)
Kang Dae-Seong (Dept. of Electronic Eng., Dong-A University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.42, no.4, 2005 , pp. 79-86 More about this Journal
Abstract
In this paper, we propose a new LINF(Linear Independent Non-negative Factorization) algorithm for real-time face recognition systea This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction Part we applied subtraction image, the detection of eye and mouth region , and normalization method, and then in the face recognition Part we used LINF in extracted face candidate region images. The existing recognition system using only PCA(Principal Component Analysis) showed low recognition rates, and it was hard in the recognition system using only LDA(Linear Discriminants Analysis) to apply LDA directly when the training set is small. To overcome these shortcomings, we reduced dimension as the matrix that had non-negative value to be different from former eigenfaces and then applied LDA to the matrix in the proposed system We have experimented using self-organized DAIJFace database and ORL database offered by AT(')T laboratory in Cambridge, U.K. to evaluate the performance of the proposed system. The experimental results showed that the proposed method outperformed PCA, LDA, ICA(Independent Component Analysis) and PLMA(PCA-based LDA mixture algorithm) method within the framework of recognition accuracy.
Keywords
Face recognition; PCA(Principal Component Analysis); LDA(Linear Discriminants Analysis); NMF(Non-negative Matrix Factorization); ICA(Independent Component Analysis);
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