Lower Order Krawtchouk Moment-Based Feature-Set for Hand Gesture Recognition. (13th March 2016)

• Record Type: Journal Article
• Authors: Kaur, Bineet; Joshi, Garima
• Other Names: Mamei Marco Academic Editor.
• Is Part Of: Advances in human-computer interaction. Volume 2016(2016)
• Publication Date: 2016-03-13
• Subjects: Human-computer interaction -- Periodicals; Human-computer interaction; Periodicals; Electronic journals; 004.019
• DOI: 10.1155/2016/6727806
• Languages: English
• ISSNs: 1687-5893

Abstract

Abstract : The capability of lower order Krawtchouk moment-based shape features has been analyzed. The behaviour of 1D and 2D Krawtchouk polynomials at lower orders is observed by varying Region of Interest (ROI). The paper measures the effectiveness of shape recognition capability of 2D Krawtchouk features at lower orders on the basis of Jochen-Triesch's database and hand gesture database of 10 Indian Sign Language (ISL) alphabets. Comparison of original and reduced feature-set is also done. Experimental results demonstrate that the reduced feature dimensionality gives competent accuracy as compared to the original feature-set for all the proposed classifiers. Thus, the Krawtchouk moment-based features prove to be effective in terms of shape recognition capability at lower orders.