Communication is the process of exchanging information, views and expressions between two or more persons, in both verbal and non-verbal manner. The sign language is a visual language used by the people with the speech and hearing disabilities for communication in their daily conversation activities. Myanmar Sign Language (MSL) is the language of choice for most deaf people in this country. In this research paper, Real-time Myanmar Sign Language Recognition System (RMSLRS) is proposed. The major objective is to accomplish the translation of 30 static sign gestures into Myanmar alphabets. The input video stream is captured by webcam and is inputed to computer vision. The incoming frames are converted into YCbCr color space and skin like region is detected by YCbCr threshold technique. The hand region is also segmented and converted into grayscale image and morphological operation is applied for feature extraction. In order to translate the signs of ASL into the corresponding alphabets, PCA is used for feature extraction and SVM is used for recognition of MSL signs. Experimental results show that the proposed system gives the successful recognition accuracy of static sign gestures of MSL alphabets with 89%.
YCbCr Color Space, Threshold, Computer Vision, Feature Extraction, PCA, Real-time, SVM, Sign Language
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