Real time Sign Language Recognition using PCA

Shreyas Sawant, M. S. Kumbhar
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引用次数: 48

Abstract

The Sign Language is a method of communication for deaf-dumb people. This paper presents the Sign Language Recognition system capable of recognizing 26 gestures from the Indian Sign Language by using MATLAB. The proposed system having four modules such as: pre-processing and hand segmentation, feature extraction, sign recognition and sign to text and voice conversion. Segmentation is done by using image processing. Different features are extracted such as Eigen values and Eigen vectors which are used in recognition. The Principle Component Analysis (PCA) algorithm was used for gesture recognition and recognized gesture is converted into text and voice format. The proposed system helps to minimize communication barrier between deaf-dumb people and normal people.
使用PCA的实时手语识别
手语是聋哑人交流的一种方式。本文介绍了一种基于MATLAB的手语识别系统,该系统能够识别印度手语中的26种手势。该系统分为预处理与手势分割、特征提取、手势识别和手势到文本和语音的转换四个模块。分割是通过图像处理完成的。提取不同的特征,如特征值和特征向量,用于识别。采用主成分分析(PCA)算法对手势进行识别,并将识别出的手势转换为文本和语音格式。该系统有助于减少聋哑人与正常人之间的沟通障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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