ANN based Indian Sign Language numerals recognition using the leap motion controller

Abstract

Sign language is the basic medium of communication for the hearing and speech impaired people. It has evolved as one of the major areas of research and study in computer vision. Researchers in sign language recognition used different input devices such as data gloves, web camera, depth camera, color camera, Microsoft's Kinect sensor, etc. to capture hand signs. In this paper we display the importance of Leap Motion Controller and proposed technique for classification and their efficient results. The proposed system contains three stages: Data collection, Feature extraction and Classification. The proposed technique for classification is executed on a dataset of total 200 samples (consisting of 20 samples of each ISL numbers). Indian Sign Language has a total of 26 alphabets and 10 numerals using either one hand or both hands to show the sign. Recognition rate of proposed system is 100%.