Title: Sign recognition using key frame selection

Authors: Rajeshree S. Rokade; Dharmpal D. Doye

Addresses: SGGS Institute of Engineering and Technology, Nanded, India ' SGGS Institute of Engineering and Technology, Nanded, India

Abstract: This paper deals with static and dynamic hand gesture (digits) recognition. The method provides a threefold novel contribution: (1) segmentation algorithm gives better results on any skin colour and any size of hand on complex and non-uniform background; (2) key frame finding algorithm and (3) the recognition technique of signs (static digits, alphabets and dynamic digits). We separate out key frames from a sequence of static gestures, which include correct gestures from a video sequence. The recognition efficiency of key frame detection is 93% using the proposed algorithm. The segmentation efficiency is almost 95%. Features are extracted using the proposed feature extraction algorithm, and gestures are recognised. We propose a novel algorithm for static and dynamic gesture recognition. The proposed algorithm shows recognition efficiency of 94.8% for static gestures and 94% for dynamic gestures.

Keywords: hand segmentation; key frame selection; feature extraction; static gestures; dynamic gestures; hand gestures; gesture recognition; sign recognition; image segmentation; skin colour; hand size; video sequences.

DOI: 10.1504/IJSISE.2016.078256

International Journal of Signal and Imaging Systems Engineering, 2016 Vol.9 No.4/5, pp.320 - 332

Received: 17 Jun 2013
Accepted: 22 May 2014
Published online: 10 Aug 2016 *

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