EMCC: Enhancement of Motion Chain Code for Arabic Sign Language Recognition
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 12
Abstract
In this paper, an algorithm for Arabic sign language recognition is proposed. The proposed algorithm facilitates the communication between deaf and non-deaf people. A possible way to achieve this goal is to enable computer systems to visually recognize hand gestures from images. In this context, a proposed criterion which is called Enhancement Motion Chain Code (EMCC) that uses Hidden Markov Model (HMM) on word level for Arabic sign language recognition (ArSLR) is introduced. This paper focuses on recognizing Arabic sign language at word level used by the community of deaf people. Experiments on real-world datasets showed that the reliability and suitability of the proposed algorithm for Arabic sign language recognition. The experiment results introduce the gesture recognition error rate for a different sign is 1.2% compared to that of the competitive method.
Authors and Affiliations
Mahmoud Abdo, Alaa Hamdy, Sameh Salem, Elsayed Saad
Keywords
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- EP ID EP90418
- DOI 10.14569/IJACSA.2015.061215
- Views 97
- Downloads 0
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