Abstract

In the recent years many approaches have been made that uses computer vision algorithms to interpret sign language. This endeavour is yet another approach to accomplish interpretation of human hand gestures. The first step of this work is background subtraction which achieved by the Euclidean distance threshold method. Thinning algorithm is then applied to obtain a thinned image of the human hand for further analysis. The different feature points which include terminating points and curved edges are extracted for the recognition of the different signs. The input for the project is taken from video data of a human hand gesturing all the signs of the American Sign Language.