The fast iris image clarity evaluation based on Brenner

2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA) Pub Date : 2013-12-01 DOI:10.1109/IMSNA.2013.6743274

Liling Chen, Min Han, H. Wan

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引用次数: 9

Abstract

In iris biometric system, iris images with poor quality possibly lead to poor performance in personal identification or recognition. To address the issue we propose the fast evaluation method for iris quality by sharpness in this paper. In our method, ROI (Region of Interests) is located firstly and then Brenner operator is utilized to evaluate quality of iris images. Experimental results reveal that our proposal has less computation load and high processing speed than compared methods. So it is necessary to evaluate the iris image quality before recognition, and sharpness evaluation is one important part of it. As some previous algorithms used the method of locating first then extracting the region of interest takes more time, this paper proposes a faster approach to evaluate the definition of iris image. First extract the region of interest (ROI) based on experience, then use brenner operator to evaluate the iris image's definition. Experimental results reveal that our proposal has the characteristics of less calculation, high velocity and more effectiveness.

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基于Brenner的快速虹膜图像清晰度评价

在虹膜生物识别系统中，虹膜图像质量不佳可能导致个人识别性能不佳。针对这一问题，本文提出了基于清晰度的虹膜质量快速评价方法。该方法首先定位感兴趣区域(ROI)，然后利用Brenner算子对虹膜图像进行质量评价。实验结果表明，该方法计算量小，处理速度快。因此，在识别前对虹膜图像质量进行评估是必要的，而清晰度评估是其中的重要组成部分。针对以往一些算法采用先定位后提取感兴趣区域耗时较长的问题，本文提出了一种快速评估虹膜图像清晰度的方法。首先根据经验提取感兴趣区域(ROI)，然后利用brenner算子对虹膜图像的清晰度进行评估。实验结果表明，该方法具有计算量少、速度快、效率高的特点。

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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来源期刊

2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA)

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