Welcome to the InfoSci Platform
Reference Hub2
Shape-Based Features for Optimized Hand Gesture Recognition

Shape-Based Features for Optimized Hand Gesture Recognition

Priyanka R., Prahanya Sriram, Jayasree L. N., Angelin Gladston
Copyright: © 2021 |Volume: 11 |Issue: 1 |Pages: 16
ISSN: 2642-1577|EISSN: 2642-1585|EISBN13: 9781799864103|DOI: 10.4018/IJAIML.2021010103
Cite Article Cite Article

MLA

Priyanka R., et al. "Shape-Based Features for Optimized Hand Gesture Recognition." IJAIML vol.11, no.1 2021: pp.23-38. http://doi.org/10.4018/IJAIML.2021010103

APA

Priyanka R., Sriram, P., Jayasree L. N., & Gladston, A. (2021). Shape-Based Features for Optimized Hand Gesture Recognition. International Journal of Artificial Intelligence and Machine Learning (IJAIML), 11(1), 23-38. http://doi.org/10.4018/IJAIML.2021010103

Chicago

Priyanka R., et al. "Shape-Based Features for Optimized Hand Gesture Recognition," International Journal of Artificial Intelligence and Machine Learning (IJAIML) 11, no.1: 23-38. http://doi.org/10.4018/IJAIML.2021010103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Gesture recognition is the most intuitive form of human-computer interface. Hand gestures provide a natural way for humans to interact with computers to perform a variety of different applications. However, factors such as complexity of hand gesture structures, differences in hand size, hand posture, and environmental illumination can influence the performance of hand gesture recognition algorithms. Considering the above factors, this paper aims to present a real time system for hand gesture recognition on the basis of detection of some meaningful shape-based features like orientation, center of mass, status of fingers, thumb in terms of raised or folded fingers of hand and their respective location in image. The internet is growing at a very fast pace. The use of web browser is also growing. Everyone has at least two or three most frequently visited website. Thus, in this paper, effectiveness of the gesture recognition and its ability to control the browser via the recognized hand gestures are experimented and the results are analyzed.