Abstract
In this paper, we present a new hand shape recognition algorithm based on Delaunay triangulation. When collecting hand shape images by a non-contact acquisition equipment, the degree of stretching of fingers may cause finger root contour deformation, which leads to unstable central axis and width features. Thus, we propose to form a more robust and non-parametric finger central axis extraction algorithm, by using a Delaunay triangulation algorithm. We show that our robust algorithm achieves the recognition rate of 99.89% on our database, while the mean time of feature extraction is 0.09 s.
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Acknowledgments
This study is supported by National Natural Science Foundation of China (NO. 61503151), Natural Science Foundation of Jilin Province (NO. 20160520100JH), Industrial Innovation Special Fund Project of Jilin Province (NO. 2017C032-4, NO. 2017C045-4).
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Liu, F., Jiang, S., Kang, B., Hou, T. (2018). A New Hand Shape Recognition Algorithm Based on Delaunay Triangulation. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_3
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DOI: https://doi.org/10.1007/978-3-319-97909-0_3
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