Feature Extraction using DCT fusion based on facial symmetry for enhanced face recognition

Feature Extraction plays a very important role in Face Recognition technology. This paper proposes a novel Discrete Cosine Transform (DCT) fusion technique based on facial symmetry. Also proposed are DCT subset matrix selection based on aspect ratio of the image and pre-processing concepts, namely Local Histogram Equalization to remove illumination variation and Scale normalization using skin detection for colored images. The performance of proposed techniques is evaluated by computing the recognition rate and number of features selected for ORL, Extended Yale B and Color FERET databases.