Abstract
The objective of this study is to create an effective way on communication between two deaf people and the others. The Computer-Vision based hand gesture recognition was developed. We apply Background Subtraction method to show a targeted gesture motion images. The images were transformed to YCbCr color space and binaries to locate the skin region. We used Morphological and Connected Component method to remove the noises produced in image process. Further, we also eliminated problems with recognizing process like a slanted hand gesture. Finally, we used Artificial Neural Network for recognizing the sign language and transmitted the out-come to handheld device such as Iphone.
Experimental results show that the accuracy of 89% in average and the processing time of 55ms in each gesture were archived in the motion hand gesture recognition. While the accuracy of 94.6% in average and the processing time of 39ms in each gesture was archived in the static hand gesture recognition.
Our results demonstrated the Computer-Vision based hand gesture recognition can be applied to next generation of Iphone.
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Lee, HC., Shih, CY., Lin, TM. (2013). Computer-Vision Based Hand Gesture Recognition and Its Application in Iphone. In: Pan, JS., Yang, CN., Lin, CC. (eds) Advances in Intelligent Systems and Applications - Volume 2. Smart Innovation, Systems and Technologies, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35473-1_49
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DOI: https://doi.org/10.1007/978-3-642-35473-1_49
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