Feature extraction for face detection and recognition

We propose a facial feature extraction method for face detection and recognition using image segmentation with adaptive thresholds and real coded genetic algorithm guided shape matching. The shapes template is constructed using the average outer edges of the lips and the eyes. Image segmentation is performed using a region growing method, whose seeds are determined using a hybrid method that combines histogram, random and pixel-by-pixel methods. Adaptive thresholds are calculated using color variance. Color spaces used are the YIQ, XYZ and the HIS. Color variance is worked out using square, star and plus kernels.