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Artificial neural network based method for Indian sign language recognition

机译:基于人工神经网络的印度手语识别方法

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Sign Language is a language which uses hand gestures, facial expressions and body movements for communication. A sign language consists of either word level signs or fingerspelling. It is the only communication mean for the deaf-dumb community. But the hearing people never try to learn the sign language. So the deaf people cannot interact with the normal people without a sign language interpreter. This causes the isolation of deaf people in the society. So a system that automatically recognizes the sign language is necessary. The implementation of such a system provides a platform for the interaction of hearing disabled people with the rest of the world without an interpreter. In this paper, we propose a method for the automatic recognition of fingerspelling in Indian sign language. The proposed method uses digital image processing techniques and artificial neural network for recognizing different signs.
机译:手语是一种使用手势,面部表情和身体动作进行交流的语言。手语由字级标志或手指拼写组成。这是聋哑社区唯一的交流手段。但是听觉的人从不尝试学习手语。因此,如果没有手语翻译人员,聋哑人将无法与普通人互动。这导致社会上聋人的孤立。因此,需要一种自动识别手语的系统。这种系统的实施提供了一个平台,用于在没有口译员的情况下使听力障碍人士与世界其他地方进行交互。在本文中,我们提出了一种自动识别印度手语中的手指拼写的方法。所提出的方法使用数字图像处理技术和人工神经网络来识别不同的符号。

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