Sign Language Recognition

被引：0

作者：

Karayilan, Tulay ^{[1
]}

Kilic, Ozkan ^{[1
]}

机构：

[1] Yildirim Beyazit Univ, Dept Comp Engn, Ankara, Turkey

来源：

2017 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2017年

关键词：

human-computer interaction; hand gesture recognition; artificial neural network; multilayer perceptron; hack-propagation; Static Hand Gesture Translator; American Sign Language (ASL); finger spelling;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Millions of people around the world suffer from hearing disability. This large number demonstrates the importance of developing a sign language recognition system converting sign language to text for sign language to become clearer to understand without a translator. In this paper, a sign language recognition system using Backpropagation Neural Network Algorithm is proposed based on American Sign Language. The neural network of this system used extracted image features as input and it was trained using back propagation algorithm to recognize which letter was the given letter with accuracy of respectively 70% and 85% with two proposed classifiers.

引用

页码：1122 / 1126

页数：5

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