Abstract
Hand gestures enabling deaf people to communication during their daily lives rather than by speaking. A sign language is a language which, instead of using sound, uses visually transmitted gesture signs which simultaneously combine hand shapes, orientation and movement of the hands, arms, lip-patterns, body movements and facial expressions to express the speaker's thoughts. Recognizing and documenting Arabic sign language has only been paid attention to recently. There have been few attempts to develop recognition systems to allow deaf people to interact with the rest of society. This paper introduces an automatic Arabic sign language (ArSL) recognition system based on the Hidden Markov Models (HMMs). A large set of samples has been used to recognize 20 isolated words from the Standard Arabic sign language. The proposed system is signer-independent. Experiments are conducted using real ArSL videos taken for deaf people in different clothes and with different skin colors. Our system achieves an overall recognition rate reaching up to 82.22%.
Highlights
IntroductionDeaf people have created and used signs among themselves
Singing has always been part of human communications [1]
Deaf people have created and used signs among themselves. These signs were the only form of communication available for many deaf people.Within the variety of cultures of deaf people all over the world, signing evolved to form complete and sophisticated languages
Summary
Deaf people have created and used signs among themselves These signs were the only form of communication available for many deaf people.Within the variety of cultures of deaf people all over the world, signing evolved to form complete and sophisticated languages. These languages have been learned and elaborated by succeeding generations of deaf children. The problem arises when a deaf person wants to communicate with a nondeaf person. Both will be dissatisfaction in a very short time
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