期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2015
卷号：10
期号：9
页码：281-290
DOI：10.14257/ijmue.2015.10.9.29
出版社：SERSC
摘要：A hand gesture recognition system for American sign language (ASL) using hierarchical features based on an infrared image is proposed. To reduce the error rate and illumination chage, the infrared image is used in this article. Hierarchical features consist of object extern, Hu-moment invariants, and direction features. First, circularity and eccentricity can be computed from the object extern feature. And then, ASL is classified by K-means using them. Next, the moment invariants features are used to recognize hand gestures by back-propagation (BP). Finally, the direction feature can accurately classify similar gestures like G and Z, I and J, U and H. The goal of this article is to achieve an efficient and effective hand gesture recognition system that meets the high recognition rate of gestures. Through experiments, the recognition rate for the proposed method is 97.15% and it takes 0.046 s to process one frame.
关键词：ASL; BP; Hand gesture recognition; Hierarchical features; Infrared image
