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Real-Time Recognition of Indian Sign Language

机译:实时识别印度手语

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摘要

The real-time sign language recognition system is developed for recognising the gestures of Indian Sign Language (ISL). Generally, sign languages consist of hand gestures and facial expressions. For recognising the signs, the Regions of Interest (ROI) are identified and tracked using the skin segmentation feature of OpenCV. The training and prediction of hand gestures are performed by applying fuzzy c-means clustering machine learning algorithm. The gesture recognition has many applications such as gesture controlled robots and automated homes, game control, Human-Computer Interaction (HCI) and sign language interpretation. The proposed system is used to recognize the real-time signs. Hence it is very much useful for hearing and speech impaired people to communicate with normal people.
机译:开发了实时手语识别系统,用于识别印度手语(ISL)的手势。通常,手语由手势和面部表情组成。为了识别信号,使用OpenCV的皮肤分割功能识别并跟踪感兴趣区域(ROI)。手势的训练和预测是通过应用模糊c均值聚类机器学习算法来执行的。手势识别具有许多应用程序,例如手势控制的机器人和自动化房屋,游戏控制,人机交互(HCI)和手语解释。所提出的系统用于识别实时信号。因此,对于有听力和言语障碍的人与正常人进行交流非常有用。

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