Static hand gesture recognition of Persian sign numbers using thinning method
Alaa Barkoky, Nasrollah Moghadam Charkari · 2011
Sign language is the most natural way of communication for the people with hearing problems. One of its most appealing applications is developing interfacing of human machine interaction with more effective. A hand gesture recognition system can provide an opportunity for deaf persons to communicate with normal people without the need of an interpreter or Intermediate. In this article, we propose a method to recognize the image-based numbers of Persian sign language (PSL) using thinning method on segmented image. In this approach, after cleaning thinned image, the real endpoints have been used for recognition. The method is qualified to provide real time recognition and is not affected by hand rotation and scaling. Experimental results on 300 images show that our approach recognition rate is 96.6% as average.