An Adaptive Threshold Segmentation Algorithm for Gesture Segmentation

Mei Wang; Jzau Sheng Lin; Zhou Xing Fu; Guo Qing Meng

doi:10.4028/www.scientific.net/AMM.513-517.457

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517An Adaptive Threshold Segmentation Algorithm for...

An Adaptive Threshold Segmentation Algorithm for Gesture Segmentation

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

457-460

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.457

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Online since:

February 2014

Authors:

Mei Wang*, Jzau Sheng Lin, Zhou Xing Fu, Guo Qing Meng

Keywords:

Adaptive Threshold, Hand Gesture, Image Segmentation

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* - Corresponding Author

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