Sign recognition using key frame selection. (2016)

• Record Type: Journal Article
• Authors: Rokade, Rajeshree S.; Doye, Dharmpal D.
• Is Part Of: International journal of signal and imaging systems engineering. Volume 9:Number 4/5(2016)
• Page Start: 320
• Page End: 332
• Publication Date: 2016
• Subjects: 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; Signal processing -- Periodicals; Imaging systems -- Periodicals; Information theory -- Periodicals; 621.3822
• Languages: English
• ISSNs: 1748-0698

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.