期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：2
出版社：S&S Publications
摘要：Sign language is natural media of communication for the hearing and speech impaired all over the world This paper presents vision based static sign gesture recognition system using neural network. This system enables deaf people to interact easily and eff iciently with normal people. The system firstly convert i mages of static gestures of American Sign Language into Lab color space where L for lightness and (a, b) for the color - opponent dimensions, from which skin region i.e. hand is segmented using thresholding technique. The region of interest (hand) is cropped and converted into binary image for feature extraction. Then height, area, centroid, and distance of the centroid from the origin (top - left corner) of the image are used as features. Finally each set of feature vector is used to train a used to tr ain a feed - forward back propagation network. Experimental results showed successful recognition of static sign gestures with an average recognition accuracy of 85 % on a typical set of test images
关键词：American Sign Language; Binary image; Feed ; for ; ward back propagation network; Lab color space; Thresholding technique
