Face Representation Using Combined Method of Gabor Filters, Wavelet Transformation and DCV and Recognition Using RBF

• 作者: Jebakumari Beulah Vasanthi Jeyasingh Kathirvalavakumar Thangairulappan
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 工学
• 关键词: Feature Extraction GABOR WAVELET WAVELET Transformation Discriminative Common Vector RADIAL BASIS Function Neural Network
• 年，卷（期）: 2012,（4）
• 页码范围: 266-273
• 页数: 8页
• 分类号: TP39

摘要

An efficient face representation is a vital step for a successful face recognition system. Gabor features are known to be effective for face recognition. The Gabor features extracted by Gabor filters have large dimensionality. The feature of wavelet transformation is feature reduction. Hence, the large dimensional Gabor features are reduced by wavelet transformation. The discriminative common vectors are obtained using the within-class scatter matrix method to get a feature representation of face images with enhanced discrimination and are classified using radial basis function network. The proposed system is validated using three face databases such as ORL, The Japanese Female Facial Expression (JAFFE) and Essex Face database. Experimental results show that the proposed method reduces the number of features, minimizes the computational complexity and yielded the better recognition rates.