I.J. Image, Graphics and Signal Processing, 2017, 9, 18-27 Published Online September 2017 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijigsp.2017.09.03 Copyright © 2017 MECS I.J. Image, Graphics and Signal Processing, 2017, 9, 18-27 Curvilinear Tracing Approach for Extracting Kannada Word Sign Symbol from Sign Video Ramesh M. Kagalkar 1 1 Research Scholar and Asst. Professor, Computer Engineering. Department, Dr. D Y Patil School of Engineering and Technology, Pune, Maharashtra, India Email: rameshvtu10@gmail.com Dr. S.V Gumaste 2 2 Professor & Head, Computer Engineering, R. H. Sapat College of Engineering, Nashik, Maharashtra, India Email: svgumaste@gmail.com Received: 18 March 2017; Accepted: 13 April 2017; Published: 08 September 2017 Abstract—Gesture based communications are utilized as a primary method of correspondence, however, the differing qualities in the sign image portrayal limit its use to district bound. There is a tremendous assorted quality in the sign image portrayal from one nation to another, one state to another. In India, there is distinctive gesture- based communication watched for each state locale. It is henceforth exceptionally troublesome for one area individual to convey to other utilizing a signature image. This paper proposes a curvilinear tracing approach for the shape portrayal of Kannada communication via gestures acknowledgment. To build up this approach, a dataset is consequently made with all Swaragalu, Vyanjanagalu, Materials and Numbers in Kannada dialect. The arrangement of the dataset is framed by characterizing a vocabulary dataset for various sign images utilized as a part of regular interfacing. In the portrayal of gesture- based communication for acknowledgment, edge elements of hand areas are thought to be an ideal element portrayal of communication through signing. In the preparing of gesture-based communication, the agent includes assumes a critical part in arrangement execution. For the developed approach of sign language detection, where a single significant transformation is carried out, a word level detection is then performed. To represent the processing efficiency, a set of cue symbols is used for formulating a word. This word symbols are then processed to evaluate the performance for sign language detection. Word processing is carried out as a recursive process of a single cue symbol representation, where each frame data are processed for a curvilinear shape feature. The frame data are extracted based on the frame reading rate and multiple frames are processed in successive format to extract the region of interest. A system outline to process the video data and to give an optimal frame processing for sign recognition a word level process is performed. Index Terms—Curvilinear feature; leap forward tracing; support vector machine, kannada sign language. I. INTRODUCTION Sign language is the only mode of communication for vocally disabled people to communicate with the external world. The mode of sign language generated is dependent on the way of its representation, where only hand gesture or hand and lip movement are combined together to communicate. Wherein sign language is the only mode of communication in this domain, people need to be trained for this sign language to understand to communicate. The vocally disabled personals are given courses in this language towards sign language generation to communicate with each other. However, for a normal individual it is hard to understand this sign language, as no exposure or courses in this reference is given. It is then become a limited mode of communication for a vocally disabled individual with a common individual. This raise the need of a converter system, which is need for interfacing the captured sign language to automatically transform to an understanding character, to eradicate the interfacing issue. This paper is organized as follows. In the section to follow, we have provided a brief overview of related work. In section 3 describes the system outline overviews of system, where the detailed description of approach used for shape representation. In section 4 provides experimental results and analysis on our self-built data set. Lastly conclusion of the work is outlined. II. RELATED WORK Towards the development of such system, various systems were proposed in past. In [1] survey that specializes in computerized speech consciousness for sign language is presented. The definition of sign languages and the objective associated to them are first defined. The contributions made in automatic sign recognition are proposed. Examples of past initiatives and future trends when coping with sign languages are