This paper proposes a new face recognition approach by using Independent Component Analysis (ICA) and Ensemble Classifiers based on Support Vector Machine (SVM). Firstly, to improve the quality of the face images, a series of image pre-processing techniques are used. Then the ICA based on Kernel Principal Component Analysis (KPCA) and FastICA is employed to extract features. At last, appropriate classifiers based on SVM are selected to construct the classification committee using Binary Particle Swarm Optimization (BPSO). The experimental results show that the proposed framework is efficient for face recognition.
Ensemble Classification Based on ICA for Face Recognition
2008 Congress on Image and Signal Processing ; 3 ; 144-148
2008-05-01
366261 byte
Conference paper
Electronic Resource
English
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