Parallel structure system employing PCA and VQ in the transform domain for facial recognition

Recently, due to emerging critical applications such as biomedical, and security applications, the area of intelligent signal processing has been receiving considerable attention. In this contribution, we present an intelligent signal processing system applied to signal recognition and classification. The system employs different structures, multicriteria and multitransform techniques. In addition, principal component analysis in the transform domain in conjunction with vector quantization is developed which result in further improvement in the recognition accuracy and dimensionality reduction. Experimental results are given which confirm the excellent properties of the proposed approaches.