Hand Gesture Recognition via Covariance Method
Ginu Thomas1, Rahul Vivek Purohit2
1Ginu Thomas, Pursuing MTech., Department of Electronic & Communication, Ajay Kumar Garg Engineering College, Ghaziabad (U.P.), India.
2Rahul Vivek Purohit, Asst. Professor, Department of Electronic & Communication, Ajay Kumar Garg Engineering College, Ghaziabad (U.P.), India.
Manuscript received on May 15, 2013. | Revised Manuscript received on June 03, 2013. | Manuscript published on June 30, 2013. | PP: 26-29 | Volume-2, Issue-5, June 2013. | Retrieval Number: E1637062513/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Gesture is a powerful form of communication among humans. This paper presents simple as well as effective method of realizing hand gesture recognition using Covariance Method. First an image database is created which constitutes various static hand gesture images. These images are a subset of American Sign Language (ASL). Preprocessing of the image is done so as to reduce the amount of noise present in the image. Eigen values of the Eigen vectors are calculated. A pattern recognition system is used to transform an image into feature vector i.e. Eigen image, which will then be compared with the trained set of gestures. The method used was successful to retrieve the correct match.
Keywords: Covariance, Pattern Recognition.