An Image Quality Assessment Algorithm for Palm-Dorsa Vein Based on Multi-Feature Fusion

Jian Jiang Cui; Qi Li; Xu Jia

doi:10.4028/www.scientific.net/AMR.508.96

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 508An Image Quality Assessment Algorithm for...

An Image Quality Assessment Algorithm for Palm-Dorsa Vein Based on Multi-Feature Fusion

Abstract:

In order to acquire more feature information in captured vein image with high-quality, an image quality assessment algorithm for palm-dorsa vein is presented based on multi-feature fusion. According to the statistical and structure properties of image, we can acquire the good vein image by adjusting near-infrared LED light exposure duty cycle combined with computing the four characteristic parameters of gray variance, information entropy, cross point and area of effect and then fusing those according to weights. In the end, an experimental case is given and the assessment results prove that this algorithm is efficient.

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Periodical:

Advanced Materials Research (Volume 508)

Pages:

96-99

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.508.96

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Online since:

April 2012

Authors:

Jian Jiang Cui, Qi Li, Xu Jia

Keywords:

Duty Cycle, Multi-Feature Fusion, Quality Assessment, Vein Recognition

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References

[1] J. Hashimoto, Finger vein authentication technology and its future, 2006 Symposium on VLSI Circuits, Kawasaki, 2006, pp.5-8.

DOI: 10.1109/vlsic.2006.1705285

Google Scholar

[2] J. G. Wang, W. Y. Yau, Suwandy A, et al, Person recognition by fusing palm print and palm vein images based on"Laplacian palm" representation, Pattern Recognition, 2008, vol. 41, no. 5, pp.1514-1527.

DOI: 10.1016/j.patcog.2007.10.021

Google Scholar

[3] S. Crisan, I. G. Tarnovan, T. E. Crisan, A low cost vein detection system using near infrared radiation, IEEE Sensors Applications Symposium. San Diego, IEEE, 2007, pp.51-56.

DOI: 10.1109/sas.2007.374359

Google Scholar

[4] L. Y. Wang, C. G. Leedham. A thermal hand vein pattern verification system, Lecture Notes in Computer Science, 2005, vol. 3687, pp.58-65.

DOI: 10.1007/11552499_7

Google Scholar

[5] Y. G. Dai, B. N. Huang, W. X. Li, et al, A method for capturing the finger-vein image using nonuniform intensity infrared light, 1st International Congress on Image and Signal Processing. Tianjin: Tianjin University of Technology, 2008, pp.501-505.

DOI: 10.1109/cisp.2008.654

Google Scholar

[6] A. Benoit, P. Le Callet, P. Campisi, et al, Quality assessment of stereoscopic images, Journal on Image and Video Processing, 2008, pp.1-13.

DOI: 10.1155/2008/659024

Google Scholar

[7] L. X. Zhang, X. S. Zhan, X. R. Zhang, Fingerprint Image Binarization Algorithm Based on Information Entropy, Computer Systems & Applications, 2010, vol. 19, no. 6, pp.148-152.

Google Scholar

[8] K. Y. Liao, X. D. Zhang, M. Z. Zhang, et al, Method for binarizing and post-processing fingerprint image based on orientation information. Journal of Computer Applications, 2008, vol. 28, no. 4, pp.1001-1005.

Google Scholar