Human face extraction using genetic algorithm with similarity of subspace method as a fitness value

A subspace method that can express facial images efficiently by linear translation into lower dimensional subspace has wide application for face recognition, e.g., identification, facial pose detection etc. In the preprocessing of this method, the accurate extraction of the human face area is required, but it is influenced by light condition, varying background, individual variation and so on, so it has not been put into practical use yet. In this paper, we examine the subspace method by comparison of the search space, and apply a genetic algorithm to face extraction and show that effective results were obtained