Wavelet Transform for Face Recognition Based on Improved Fuzzy C-Means

Abstract:

The popular approaches for face recognition are PCA and LDA methods. But PCA could not capture the simplest invariance unless information is explicitly provided in the training data and LDA approach suffers from a small size problem. 2DPCA could reduce high dimensional data to a low-dimensional space.2DLDA could extract the proper features from image matrices based on LDA. Ensemble incomplete wavelet analysis method for face recognition is proposed based on improved fuzzy C-Means in this paper. The method proposed shows that it improves the accuracy and reduces the running time.

• Periodical: Applied Mechanics and Materials (Volumes 602-605)
• Pages: 2170-2173
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.602-605.2170
• Online since: August 2014
• Authors: Xiao Fei Li*
• Keywords: 2DLDA, 2DPCA, Ensemble Subspaces, Face Recognition, Fuzzy C-Means, Wavelet Transform (WT)

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