Point Pattern Matching Algorithm for Recognition of 36 ASL Gestures
Deval G. Patel
Deval G. Patel, Computer Engineering, B.V.M. Engineering College, India.
Manuscript received on June 05, 2013. | Revised Manuscript received on June 11, 2013. | Manuscript published on June 15, 2013. | PP: 24-28 | Volume-1 Issue-7, June 2013. | Retrieval Number: G0336061713/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Hand gesture recognition is a way to create a useful, highly adaptive interface between machines and their users. The recognition of gestures is difficult because gestures exhibit human variability. Sign languages are used for communication and interface . There are various types of systems and methods available for sign languages recognition. Our approach is robust and efficient for static hand gesture recognition. The main objective of this paper is to propose a system which is able to recognize 36 static hand gestures of American Sign Language (ASL) for letter A- Z and digits 0-9 successfully and also it is able to perform the classification on static images correctly in real time. We proposed a novel method of pattern recognition to recognize symbols of the ASL based on the features extracted by SIFT algorithm and its performance is compared it with widely used methods such as PCA and Template Matching.
Keywords: ASL, Hand Gesture Recognition System, PCA, Point Pattern Matching Algorithm.