Abstract
Sign language recognition (SLR) system is helpful for individuals who can't talk or hear. One can easily communicate with this kind of people using SLR system. In this paper we are focusing on SLR approach where we have apply our proposed algorithm to recognize hand gestures of routine words like Morning, Night, Monday, Tuesday and so forth. Total 10 routine words we have recognize using our proposed technique. For recognize hand pose we have utilized skin color detection algorithm. Further we have applied correlation-coefficient algorithm to distinguish closeness features which are further continue in Neuro-fuzzy(NF) classification algorithm to recognize words. Presented algorithm tried on Matlab. With taken of 10 routine words our proposed framework of techniques got 92% correction rate.
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