Comparative study of segmentation technique for hand gesture recognition system

Hand gesture recognition system brings a lot of benefits to people in various industries. it consists of three main modules,which are the detection module,segmentation module and feature extraction module. the selection of appropriate segmentation method depends on the application and system environments. this paper concentrates on the following points: 1) the input images are converted to the hsv and ycbcr model by using threshold values,which satisfy the skin color segmentation based on skin color region; 2) different edges operator are then applied on both color model images,namely canny with fixed threshold,canny with otsu threshold and sobel with fixed threshold. while there is no conclusion,which color space is best fit for skin color detection,canny edge detector using otsu threshold proves the best in creating contour of hand image since it is able to detect true weak edges compared to the other types of edge segmentation technique.