An Adaptive Threshold Segmentation Algorithm for Gesture Segmentation

The key step for gesture recognition is hand gesture segmentation. A new dynamic thresholding segmentation approach named Adaptive Threshold Segmentation Algorithm (ATSA) was developed. The segmentation effect evaluation was conducted based on the construction of a new color space model of skin mode...

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Veröffentlicht in:Applied Mechanics and Materials Jg. 513-517; H. Applied Science, Materials Science and Information Technologies in Industry; S. 457 - 460
Hauptverfasser: Fu, Zhou Xing, Wang, Mei, Meng, Guo Qing, Lin, Jzau Sheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 06.02.2014
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ISBN:9783038350125, 3038350125
ISSN:1660-9336, 1662-7482, 1662-7482
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Zusammenfassung:The key step for gesture recognition is hand gesture segmentation. A new dynamic thresholding segmentation approach named Adaptive Threshold Segmentation Algorithm (ATSA) was developed. The segmentation effect evaluation was conducted based on the construction of a new color space model of skin model. The images of hand gesture were processed by using the proposed ATSA and the Fixed Threshold Segmentation (FTS) algorithm. Comparing with FTS, the ATSA is experimentally demonstrated that the segmented result has a less brightness impact, a lower redundancy rate, a lower rate of false alarm and missing, and a higher integrity rate.
Bibliographie:Selected, peer reviewed papers from the 2014 International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI 2014), January 11-12, 2014, Xi’an, China
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ISBN:9783038350125
3038350125
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.513-517.457