Abstract
Human face is an important object in an image database due to its unique features (eyes, mouth, nose etc.) in every human being. The detection & recognition of a face in an image using template matching is one of the profound research interest in the field of image processing. Various approaches have been proposed in the literature to extract the visual facial features based on texture, color, shape, sketch & pose variance etc. for face detection in color images. This paper describes an approach of face detection technique that includes major characteristics such as lightening compensation based on luminance (Y) & chrominance (Cr), Color segmentation, skin-tone statistics & eye-mouth region computation. A template matching algorithm using cross correlation method for locating & recognizing a face has been applied on various face candidates to match the template with right face candidate. Thus, the presented work is divided into three steps: Face detection, Computation of template matching & Face recognition. The performance of given approach has been evaluated on the basis of run time & accuracy. The simulation result shows that the defined model is efficient in terms of accuracy which is 81% and the false alarms are reduced.
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