Abstract
There have been many developments and applications based on hand posture recognition to make human–computer interaction/interfaces more convenient and effective. And, many of these applications are based on the image-processing technique since it can guarantee more information and more flexibility for processing. To develop a hand posture recognition system, the proper extraction of pure hand region is a very important step since it is much related with the final performance and recognition rate. But, by the noisy data due to the illumination, image resolution, and non-uniform distribution of skin colors which could be easily found in real environments, it is not easy to extract the pure hand region exactly. In this research, a simple and effective algorithm for hand cropping, named as max–min hand cropping, is proposed and compared with some of the previous research. Finally, the effectiveness of the proposed method is verified with 152 different hand images from 8 persons and 19 hand postures.
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This work was supported by the research program of Dongguk University, 2014.
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Communicated by J.-W. Jung.
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Jeong, J., Jang, Y. Max–min hand cropping method for robust hand region extraction in the image-based hand gesture recognition. Soft Comput 19, 815–818 (2015). https://doi.org/10.1007/s00500-014-1391-9
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DOI: https://doi.org/10.1007/s00500-014-1391-9