Discrete cosine transform (DCT) based face recognition in hexagonal images

In this paper a new approach to face recognition is presented which is based on processing of face images in hexagonal lattice. The importance of the hexagonal representation is that it possesses special computational features that are pertinent to the Human Vision process. Few advantages of processing images on hexagonal lattice are higher degree of circular symmetry, uniform connectivity, greater angular resolution, and a reduced need of storage and computation in image processing operations. Proposed methodology is a hybrid approach to face recognition. DCT is being applied to hexagonally converted images for dimensionality reduction and feature extraction. These features are stored in a database for recognition purpose. Artificial Neural Network (ANN) is being used for recognition. Experiments and testing were conducted over ORL, Yale and FERET databases. The proposed methodology has given better results in recognition over square pixel based approaches.