Sign Language Recognition System is one of the important researches today in engineering field. Number of methods are been developed recently in the field of Sign Language Recognition for deaf and dumb people. It is very useful to the deaf and dumb people to convey their message to other people. In this paper we proposed some methods, through which the recognition of the signs becomes easy for peoples while communication. We use the different symbols of signs to convey the meanings. And the result of those symbols signs will be converted into the text. In this project, we are capturing hand gestures through webcam and convert this image into gray scale image. The segmentation of gray scale image of a hand gesture is performed using Otsu thresholding algorithm.. Total image level is divided into two classes one is hand and other is background. The optimal threshold value is determined by computing the ratio between class variance and total class variance. To find the boundary of hand gesture in image Canny edge detection technique is used. Keywords: Indian Sign Language, Feature Extraction, Edge Detection, Sign recognition, Color, Texture