Numbers Sign Language Recognition (ArANSLR). It facilitates the communication between the deaf and normal people by recognizing the alphabet and numbers signs of Arabic sign language to text or speech. To achieve this target, the system able to visually recognize gestures from hand image input. The proposed algorithm uses hand geometry and the different shape of a hand in each sign for classifying letters shape by using Hidden Markov Model (HMM). Experiments on real-world datasets showed that the proposed algorithm for Arabic alphabet and numbers sign language recognition is suitability and reliability compared with other competitive algorithms. The experiment results show that the increasing of the gesture recognition rate depends on the increasing of the number of zones by dividing the rectangle surrounding the hand.
The proposed system has reached an accuracy of 63.5% for Arab Alphabet signs Hidden Markov Model (HMM) technique successfully recognizes the alphabet and numbers signs of Arabic sign language to text or speech REF .
Arabic Alphabet and Numbers Sign Language Recognition
International Journal of Advanced Computer Science and Applications
Computer Science