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Automatic Translation of Arabic Sign to Arabic Text (ATASAT) System

机译:自动将阿拉伯文符号翻译成阿拉伯文(ATASAT)系统

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Sign language continues to be the preferred tool of communication between the deaf and thehearing-impaired. It is a well-structured code by hand gesture, where every gesture has aspecific meaning, In this paper has goal to develop a system for automatic translation of ArabicSign Language. To Arabic Text (ATASAT) System this system is acts as a translator among deafand dumb with normal people to enhance their communication, the proposed System consists offive main stages Video and Images capture, Video and images processing, Hand SignsConstruction, Classification finally Text transformation and interpretation, this system dependson building a two datasets image features for Arabic sign language gestures alphabets from tworesources: Arabic Sign Language dictionary and gestures from different signer's human, alsousing gesture recognition techniques, which allows the user to interact with the outside world.This system offers a novel technique of hand detection is proposed which detect and extracthand gestures of Arabic Sign from Image or video, in this paper we use a set of appropriatefeatures in step hand sign construction and classification of based on different classificationalgorithms such as KNN, MLP, C4.5, VFI and SMO and compare these results to get betterclassifier.
机译:手语仍然是聋哑人和听力障碍者之间交流的首选工具。它是一种结构良好的手势代码,每个手势都有特定的含义。本文旨在开发一种自动翻译阿拉伯手语的系统。对于阿拉伯文本(ATASAT)系统,该系统充当聋哑人与普通人之间的翻译,以增强他们的沟通,该系统包括主要阶段,包括视频和图像捕获,视频和图像处理,手势构建,分类最终文本转换以及解释上,该系统依赖于构建来自两个资源的阿拉伯手语手势字母表的两个数据集图像特征:阿拉伯手语词典和来自不同签名人的手势,还使用手势识别技术,该功能允许用户与外界交互。提出了一种从图像或视频中检测和提取阿拉伯符号手势的手检测新技术,本文基于KNN,MLP,C4等不同分类算法,在步骤手符号的构建和分类中使用了一组适当的功能。 5,VFI和SMO并比较这些结果以获得更好的分类器。

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