Hand Posture Recognition Based on PCA

Jing Wen; Nai Zhong Zhang

doi:10.4028/www.scientific.net/AMM.738-739.631

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 738-739Hand Posture Recognition Based on PCA

Hand Posture Recognition Based on PCA

Abstract:

In this paper, we present an algorithm which detects human hand by skin color information in YCbCr and HIS color model. And for confirming special human hand we use circle rate of region to detect hand region because human hand have complex edge than other region, thus circle rate of hand region is usually more greater. For the recognition of detected hand, we use the Hausdorff to tracking the hand region. And we employed a recognition method based on PCA algorithm to recognize the hand gestures. The experimental results show that an algorithm plays an efficient effort for hand gesture recognition.

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Periodical:

Applied Mechanics and Materials (Volumes 738-739)

Pages:

631-634

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.738-739.631

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Online since:

March 2015

Authors:

Jing Wen, Nai Zhong Zhang*

Keywords:

Hand Posture Recognition, Hausdorff Matching Method, PCA

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