印度手语的实时识别

H. Muthu Mariappan, V. Gomathi
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引用次数: 49

摘要

实时手语识别系统是为识别印度手语(ISL)的手势而开发的。一般来说,手语包括手势和面部表情。为了识别标志,使用OpenCV的皮肤分割特征识别和跟踪感兴趣区域(ROI)。采用模糊c均值聚类机器学习算法对手势进行训练和预测。手势识别在手势控制机器人和自动化家庭、游戏控制、人机交互(HCI)和手语翻译等领域有着广泛的应用。该系统用于实时标识识别。因此,听力和语言障碍的人与正常人交流是非常有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Recognition of Indian Sign Language
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.
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