2018年手势识别外文翻译--光照不变的实时鲁棒手势识别

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1、4100 英文单词， 20500 英文字符 ， 中文 6600 字 文献出处： Chaudhary A, Raheja J L. Light invariant real-time robust hand gesture recognitionJ. Optik, 2018, 159: 283-294. Light invariant real-time robust hand gesture recognition Ankit Chaudhary, J.L. Raheja Abstract Computer vision has spread over different domains to

2、 facilitate difcult operations. It works as the articial eye for many industrial applications to observe elements, process, automation and to nd defects. Vision-based systems can also be applied to normal human life operations but changing light conditions is a big problem for these systems. Hand ge

3、sture recognition can be embedded with many existing interactive applications/games to make interaction natural and easy but changing illumination and non-uniform backgrounds make it very difcult to perform operations with good image segmentation. If a vision based system is installed in public doma

4、in, different people are supposed to work on the application. This paper demonstrates a light intensity invariant technique for hand gesture recognition which can be easily applied to other vision-based applications also. The technique has been tested on different people in different light condition

5、s with the extreme change in intensity. This was done as one skin color looks different in changed light intensity and different skin colors may look same in changed light intensity. The orientation histogram was used to identify unique features of a hand gesture and it was compared using super- vis

6、ed ANN. The overall accuracy of 92.86% is achieved in extreme light intensity changing environments. Keywords: Gesture recognition ； Orientation histogram； Light intensity invariant systems ；Extreme change in light intensity ； Natural computing； Robust skin detection 1. Introduction Computer vision applications have been part of industry operations for more than four decades. They are helpful in fasting the industrial process, automated many difcult tasks and also help in nding minor de