A New Sclera Segmentation and Vessels Extraction Method for Sclera Recognition

Wei Dong, Han Zhou, Dong Xu
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Abstract

As a unique biometric trait, the research of sclera blood vessels have becomes active recently, because the sclera vessels can be captured under visible-wavelength light condition rather than near infrared light condition. However, the performance of sclera identification system degrades a lot due to unsatisfactory sclera segmentation and tedious extraction process. In this paper, we propose a novel sclera segmentation algorithm and an improved sclera vessels extraction method. The accurate and efficient sclera segmentation method is proposed based on improved OSTU algorithm. Besides, the vessels extraction method is put forward by adaptive histogram equalization method and Gabor filters. The experimental results on UBIRIS.vl database prove that the proposed sclera vessels extraction algorithm performs well and the sclera segmentation method has an obvious improvement in terms of efficiency and accuracy over than other segmentation algorithms.
一种新的巩膜分割和血管提取方法用于巩膜识别
巩膜血管作为一种独特的生物特征,由于在可见光条件下而不是近红外光条件下可以捕获巩膜血管,近年来对其的研究变得活跃起来。然而,由于巩膜分割不理想和提取过程繁琐,使得巩膜识别系统的性能大大降低。本文提出了一种新的巩膜分割算法和一种改进的巩膜血管提取方法。基于改进的OSTU算法,提出了准确高效的巩膜分割方法。此外,提出了基于自适应直方图均衡化和Gabor滤波器的血管提取方法。UBIRIS的实验结果。Vl数据库证明,本文提出的巩膜血管提取算法性能良好,巩膜分割方法在效率和准确率上均较其他分割算法有明显提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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