Max-min hand cropping method for robust hand region extraction in the image-based hand gesture recognition
- Authors
- Jeong, Jinwoo; Jang, 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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Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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