Mexican Sign Language Recognition Using Jacobi-Fourier Moments
Mexican Sign Language Recognition Using Jacobi-Fourier Moments作者机构：University Center UAEM Teotihucan Valley Autonomous University of Mexico State Mé xico Polytechnic University of Tulancingo Tulancingo Mé xico
出 版 物：《Engineering（科研）》 (工程（英文）（1947-3931）)
年 卷 期：2015年第7卷第10期
页 面：700-705页
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Mexican Sign Language Jacobi-Fourier Moments Digital Image Processing
摘 要：The present work introduces a system for recognizing static signs in Mexican Sign Language (MSL) using Jacobi-Fourier Moments (JFMs) and Artificial Neural Networks (ANN). The original color images of static signs are cropped, segmented and converted to grayscale. Then to reduce computational costs 64 JFMs were calculated to represent each image. The JFMs are sorted to select a subset that improves recognition according to a metric proposed by us based on a ratio between dispersion measures. Using WEKA software to test a Multilayer-Perceptron with this subset of JFMs reached 95% of recognition rate.
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