Vision based hand gesture recognition using eccentric approach for human computer interaction

There has been growing interest in the development of new approaches and technologies for bridging the human-computer barrier. Hand gesture recognition is considered as an interaction technique having potential to communicate with machines. Human computer interaction (HCI) was never an easy task and lots of approaches are available to build such systems. Hand gesture recognition (HGR) using wearable data glove provides a solution to build a HCI system, but lags in terms of its computational time and poor interface. Pattern matching is one more solution which uses vision based techniques and provides strong interface to build HCI systems. But again, it requires complex algorithms which takes lots of computational time and hence limits its use in real time HCI applications. In this paper, we presented an eccentric approach for hand gesture recognition which is simple, fast and user independent and can be used to develop real time HCI applications. Based on proposed algorithm we built a system for Indian Sign Language recognition which converts Indian Sign numbers into text. The algorithm first captures the image of single handed gesture of speech/hearing impaired person using simple webcam and then using our proposed algorithm it classifies the gesture into its appropriate class. It uses simple logical conditions for gesture classification which make its use in real time HCI applications.