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Real-Time Recognition of Indian Sign Language

机译:印度手语的实时识别

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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:开发了实时标志语言识别系统,用于识别印度手语(ISL)的手势。通常,标志语言由手势和面部表达组成。为了识别标志,使用OpenCV的皮肤分割特征来识别和跟踪感兴趣区域(ROI)。通过应用模糊C型聚类机学习算法来执行手势的训练和预测。手势识别有许多应用,例如手势控制机器人和自动家庭,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标志。因此,听证会和言语受损人民与正常人沟通非常有用。

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