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Proceedings Paper

An improved vein image segmentation algorithm based on SLIC and Niblack threshold method
Author(s): Muqing Zhou; Zhaoguo Wu; Difan Chen; Ya Zhou
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Paper Abstract

Subcutaneous vein images are often obtained by using the absorbency difference of near-infrared (NIR) light between vein and its surrounding tissue under NIR light illumination. Vein images with high quality are critical to biometric identification, which requires segmenting the vein skeleton from the original images accurately. To address this issue, we proposed a vein image segmentation method which based on simple linear iterative clustering (SLIC) method and Niblack threshold method. The SLIC method was used to pre-segment the original images into superpixels and all the information in superpixels were transferred into a matrix (Block Matrix). Subsequently, Niblack thresholding method is adopted to binarize Block Matrix. Finally, we obtained segmented vein images from binarized Block Matrix. According to several experiments, most part of vein skeleton is revealed compared to traditional Niblack segmentation algorithm.

Paper Details

Date Published: 19 December 2013
PDF: 10 pages
Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90450D (19 December 2013); doi: 10.1117/12.2037345
Show Author Affiliations
Muqing Zhou, Beijing Institute of Technology (China)
Zhaoguo Wu, Beijing Institute of Technology (China)
Difan Chen, Beijing Institute of Technology (China)
Ya Zhou, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 9045:
2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Xinggang Lin; Jesse Zheng, Editor(s)

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