期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2011
卷号：2
期号：11
DOI：10.14569/IJACSA.2011.021108
出版社：Science and Information Society (SAI)
摘要：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%.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Hand Gesture; Hand Tracking; Arabic Sign Language (ArSL); HMM; Hand Features; Hand Contours.
