Computer vision based approach for Indian Sign Language character recognition

R. K. Shangeetha, V. Valliammai, S. Padmavathi
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引用次数: 30

Abstract

Deaf and dumb people communicate among themselves using sign languages, but they find it difficult to expose themselves to the outside world. This paper proposes a method to convert the Indian Sign Language (ISL) hand gestures into appropriate text message. In this paper the hand gestures corresponding to ISL English alphabets are captured through a webcam. In the captured frames the hand is segmented and the state of fingers is used to recognize the alphabet. The features such as angle made between fingers, number of fingers that are fully opened, fully closed or semi closed and identification of each finger are used for recognition. Experimentation done for single hand alphabets and the results are summarised.
基于计算机视觉的印度手语字符识别方法
聋哑人之间用手语交流,但他们发现很难将自己暴露在外面的世界。本文提出了一种将印度手语(ISL)手势转换成合适的文本信息的方法。本文通过网络摄像头捕获与ISL英语字母相对应的手势。在捕获的帧中,手被分割,手指的状态被用来识别字母表。利用手指之间的夹角、全开、全闭或半闭的手指数量以及每个手指的身份等特征进行识别。对单手字母的实验结果进行了总结。
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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