Title: Discriminant Feature Extraction Based on Modular Local Binary Pattern and Face Recognition
Abstract: This paper presents a new discriminant feature extraction method based bases on modular local binary pattern(LBP).According to the proposed method,the original face images are firstly divided into smaller sub-images.Then,the LBP operator is applied to each of these sub-images and the effective texture feature is extracted.A new training set is formed by the LBP feature vector of each sub-image.The lower dimensional PCA-based features can be computed by applying PCA on the new training set.Finally,LDA is performed on the reduced PCA-based feature vectors.The experimental results on both ORL face database and YALE face database show that the proposed method is more effective than traditional PCA and LDA methods.
Publication Year: 2009
Publication Date: 2009-01-01
Language: en
Type: article
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