Interact With Computer System Using Real-Time Static Hand Gesture Recognition
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 4
Abstract
Hand gestures are powerful approach of communication among humans and the sign language is the most effective and natural communication for the peoples. In this work, the hand gesture system is developed. The setup of the proposed system needs fixed position webcam with 20 mega pixel resolution. It captures snapshot using RGB colour space from static distance. This work is divided in different stages, which are image pre-processing, the region extraction after that feature extraction & last feature matching. First stage converts captured input image into binary image using gray threshold, followed by morphological operations. At Second stage, blob extracts hand region and crop is applied for getting extracted region and then “Sobel” edge detection is applied on the above extracted region. Third stage gives feature vectors as area of edge, which will be compared with feature vectors of a dataset by using Euclidian distance in the further stage. Minimum Euclidian distance gives accurate recognition of perfect matching gesture for performing corresponding activity. This paper have experiments for static hand gestures related to all 26 alphabets. The Training dataset having number of samples of each symbol in different shapes, different positions and conditions of environment. It can reliably recognize single hand gestures in real time. It can achieve upto 82.88% of recognition rate in static background with least Euclidian distance.
Authors and Affiliations
Ajit R. Waingankar, Sanket S. Gurav, Abhishek A. Naik, Rohit S. Gangan
Keywords
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