SIGN LANGUAGE TRANSLATION SYSTEM

Normal individuals can readily engage and communicate with one another, but those with hearing and speech impairments have difficulty conversing with other hearing people without the assistance of a translator. For deaf and dumb individuals, the Indian sign language is a communication obstacle. People with hearing and speech impairments rely heavily on nonverbal communication, which includes hand gestures. This is why implementing a system that recognizes Indian sign language would have a tremendous positive influence on the deaf and dumb. In this, a method for automatically recognizing finger printing in Indian Indian sign language is proposed. In this case, the system is provided the sign in the form of gestures. On the input sign picture, multiple stages are conducted. To determine the shape of the sign, the first segmentation step is done based on skin color. After that, the discovered region is converted to a binary image. The binary image is then transformed using the Euclidean distance transformation. On the distance modified picture, row and column projection is used. Central moments, as well as HU’s moments, are done to extract features. SVM and GREYSCALE are used for classification.