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Iris Segmentation using Adaptive Histogram Equalization and median filtering

机译:使用自适应直方图均衡和中值滤波的虹膜分割

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摘要

The personal identification based on Iris biometric is one of the most suitable and reliable methods with respect to performance and accuracy. However, the reliability and accuracy of the method depends on the proper segmentation of an iris from an eye image. In this paper, Adaptive Histogram Equalization (AHE) and median filtering are employed to segment the iris region from an eye image. Segmented iris patterns are classified using ANN. The experiments are performed over CASIA iris V3 interval database obtained from public domain digital repository. The experimental results demonstrate that the proposed approach outperforms the existing approaches, viz. Daugman's approach, Masek's approach and Abdullah's approach in terms of running time and image classification accuracy for the considered dataset.
机译:就性能和准确性而言,基于虹膜生物特征的个人识别是最合适和最可靠的方法之一。但是,该方法的可靠性和准确性取决于从眼睛图像中适当分割虹膜。在本文中,采用自适应直方图均衡(AHE)和中值滤波从眼睛图像中分割虹膜区域。使用ANN对分段的虹膜图案进行分类。在从公共领域数字资源库获得的CASIA iris V3间隔数据库上执行实验。实验结果表明,提出的方法优于现有方法,即。就所考虑的数据集的运行时间和图像分类精度而言,Daugman方法,Masek方法和Abdullah方法。

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