A novel approach towards detecting faces and gender using skin segmentation and template matching

Human face detection has become a major field of interest in current research due to the lack of deterministic algorithm to find face(s) in a given image. Further the algorithms that exist are very specific to the kind of images they would take as input and detect faces. The approach we take is a mixture of heuristic and novel algorithms. To detect faces we can put a number of simple rejection blocks in series, until we get the faces. Deeper the rejection block, more specifically it can be trained to eliminate non-faces. Various methods like template matching, maximal rejection and Eigen faces have been tried. Finally, a combination of skin colour segmentation, morphological operations, and Template Matching with Eigen faces has been used. The same technique is further expanded and used to classify genders.