International Journal on Computational Sciences & Applications (IJCSA) Vol.4, No.2, April 2014 DOI:10.5121/ijcsa.2014.4207 57 Segmentation, Tracking And Feature Extraction For Indian Sign Language Recognition Divya S , Kiruthika ,S Nivin Anton A L and Padmavathi S Student, Department of Computer Science & Engineering, Amrita University ABSTRACT Sign Language is a means of communication between audibly challenged people. To provide an interface between the audibly challenged community and the rest of the world we need Sign Language translators. A sign language recognition system computerizes the work of a sign language translator. Every Sign Language Recognition (SLR) System is trained to recognize specific sets of signs and they correspondingly output the sign in the required format. These SLR systems are built with powerful image processing techniques. The sign language recognition systems are capable of recognizing a specific set of signing gestures and output the corresponding text/audio. Most of these systems involve the techniques of detection, segmentation, tracking, gesture recognition and classification. This paper proposes a design for a SLR System. KEYWORDS Indian Sign Language (ISL), Sign Language Recognition Systems (SLR Systems), Skin Based Segmentation, RGB, HSV, YCbCr, Kalman Filter, SIFT. 1. INTRODUCTION Sign Language Translators act an interface of communication between the audibly challenged and the rest of the world. Providing an interface between the communities in Indian Sign Language (ISL) is very challenging issue because of the following reasons (1) The ISL Signs have not been standardized as of date. (2) The ISL Signs vary from region to region and hence we have various dialects of ISL. (3) Every Signer does the same gesture in a different ways. (4) Information regarding the signs and gestures are multichannel. The Central Institute ISL Society is currently working in collaboration with Ramakrishna Mission to standardize the ISL Signs. ISL words are categorized into 4 types as- (1) Feelings (2) Descriptions (3) Actions and (4) Non- Manual Actions. ISL grammar omits the usage of articles such as (a, an, the) and also does not include tense forms. The sentence structure of an ISL sentence (SOV) – Subject Object Verb- very much different from the sentence structure of English Language (SVO) – Subject Verb Object and hence ISL and English Language aren’t verbatim convertible. The term sign and gesture are used interchangeably throughout the paper. The Signs are represented by the HamNoSys* System of Notation for Sign Language. Most of the signs in ISL involve dynamic movement of both the hands and non-manual gestures. SLR systems are simple yet trained intelligent systems used for converting sign language into text by recognizing the head and hand gestures. SLR systems have been classified into two types based on the approach- (1) Data Glove