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Cited 8 time in webofscience Cited 10 time in scopus
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Max-min hand cropping method for robust hand region extraction in the image-based hand gesture recognition

Authors
Jeong, JinwooJang, Yoonhee
Issue Date
Apr-2015
Publisher
SPRINGER
Keywords
Max-min hand cropping; Hand region extraction; Hand posture recognition; Human-computer interaction
Citation
SOFT COMPUTING, v.19, no.4, pp 815 - 818
Pages
4
Indexed
SCIE
SCOPUS
Journal Title
SOFT COMPUTING
Volume
19
Number
4
Start Page
815
End Page
818
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/25385
DOI
10.1007/s00500-014-1391-9
ISSN
1432-7643
1433-7479
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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