基于图像处理的语音和听力障碍手语识别

Parama Sridevi, Tahmida Islam, Urmi Debnath, Noor A Nazia, Rajat Chakraborty, C. Shahnaz
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引用次数: 7

摘要

本文提出了一种能够实现美国手语语言化的手语翻译模型。这个健壮的模型基于仅使用用户手势创建人机界面(HCI)。硬件和软件接口的结合-网络摄像头和MATLAB 2016a-执行从实时视频中捕获的手势图像的特征提取过程。将这些特征与数据库图像的特征进行比较,在MATLAB中经过一些图像处理技术,系统根据预测的最高相似度产生输出。由于该模型不含任何其他设备或配件,因此非常实用且易于使用。该模型在我们的测试中提供了令人满意的精度,而不需要任何恒定或单色背景。所提出的技术,加上一个庞大的源数据库,肯定会对减轻有听力和说能力的人与没有听力和说能力的人之间的沟通差距非常有益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sign Language Recognition for Speech and Hearing Impaired by Image Processing in MATLAB
The paper presents the model of a sign language interpreter that can verbalize American Sign Language (ASL). This robust model is based on creating a human-computer interface (HCI) using the user's hand gesture only. The combination of Hardware and software interfaces-webcam and MATLAB 2016a-performs the feature extraction process from the image captured from real-time video of hand signs. These features are compared with the features of the database images and after some image processing techniques in MATLAB, the system generates outputs depending on the prediction of highest resemblance. As the model is free from any other apparatus or accessories, it is solely practical and easy to use. This model provided satisfactory accuracy in our tests without any need of any constant or unicolor background. The proposed technique, together with a vast source database, will definitely be highly beneficial for mitigating the communication gap between the people with speaking and hearing abilities and those without them.
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