Abstract

Sign language is used by deaf and hard hearing people to exchange information between their own community and other people. Computer recognition of Sign language deals from Sign gesture acquisition and continues till text/speech generation. Sign gestures can be classified as static and dynamic. However static gesture recognition is simpler than dynamic gesture recognition but both recognition systems are important to the human community. However, most people do not know the sign language. In this project, we aim to automatically recognize sign language Alphabet / Numbers / Words in image- based methodology using MATLAB. The problem addressed is based on Digital Image Processing using Skin Detection, Image Segmentation, Image Filtering, and cross- correlation method. This system expects to achieve recognizing gestures of ISL (Indian Sign Language) by special people and converting into speech/text. The statistic of the result of the implementation, it is therefore concluded that the method is used for cross-correlation and color segmentation work with hand gesture recognition. The results obtained are applicable and can be implemented in a mobile device smart phone having a frontal camera. The vision of an efficient system to translate sign language to text is quite achievable, but the challenges lie in optimization. Key Words: Computer recognition, Skin Detection, ISL (Indian Sign Language)

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