Sensors 2013, 13(11), 14339-14366; doi:10.3390/s131114339
Article

Robust Finger Vein ROI Localization Based on Flexible Segmentation

1 Division of Electronic and Information Engineering, Chonbuk National University, Jeonju 561-756, Korea 2 Institute of Remote Sensing and Earth Science, Hangzhou Normal University, Hangzhou 311121, China 3 Department of Multimedia Engineering, Mokpo National University, Jeonnam 534-729, Korea 4 College of Computer Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300222, China 5 IT Convergence Research Center, Chonbuk National University, Jeonju 561-756, Korea
* Author to whom correspondence should be addressed.
Received: 30 August 2013; in revised form: 15 October 2013 / Accepted: 17 October 2013 / Published: 24 October 2013
(This article belongs to the Section Physical Sensors)
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Abstract: Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.
Keywords: finger vein; ROI localization; edge operator; segmentation; orientation correction

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MDPI and ACS Style

Lu, Y.; Xie, S.J.; Yoon, S.; Yang, J.; Park, D.S. Robust Finger Vein ROI Localization Based on Flexible Segmentation. Sensors 2013, 13, 14339-14366.

AMA Style

Lu Y, Xie SJ, Yoon S, Yang J, Park DS. Robust Finger Vein ROI Localization Based on Flexible Segmentation. Sensors. 2013; 13(11):14339-14366.

Chicago/Turabian Style

Lu, Yu; Xie, Shan J.; Yoon, Sook; Yang, Jucheng; Park, Dong S. 2013. "Robust Finger Vein ROI Localization Based on Flexible Segmentation." Sensors 13, no. 11: 14339-14366.

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