基于迭代上下文滤波的指纹匹配增强

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI:10.1109/ICoICT52021.2021.9527482

Brama Yoga Satria, Agus Bejo, Risanuri Hidayat

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引用次数: 1

摘要

指纹匹配取决于指纹图像的质量。当指纹图像质量较低时，会严重降低指纹匹配的性能。指纹图像经常受到噪声的污染。因此，图像质量对指纹匹配至关重要。提出了一种将上下文滤波迭代应用于指纹图像的图像增强算法。该算法的主要思想是对Gabor滤波器的输出进行迭代，以获得更好的增强和匹配性能。该算法经过5次迭代，得到5张滤波后的图像。结果表明，基于等错误率(EER)的Gabor滤波方法与改进的Gabor滤波方法相比，具有明显的优越性。该方法优于Gabor滤波器3.08%，优于改进的Gabor滤波器2.95%。

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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Fingerprint Enhancement using Iterative Contextual Filtering for Fingerprint Matching

Fingerprint matching depends on the quality of the fingerprint images. When fingerprint image quality is low, it can degrade the performance of fingerprint matching significantly. Fingerprint images are often contaminated by noise. Therefore, image quality is crucial for fingerprint matching. In this paper, an image enhancement algorithm in which contextual filtering is applied iteratively to a fingerprint image has been proposed. The main idea of the algorithm is to iterate the output of the Gabor filter to get better enhancement and matching performance. The result of the algorithm has five filtered images due to five times iteration. It showed that the proposed method is significantly better based on Equal Error Rate (EER) compared to the Gabor filter and the modified Gabor filter. The proposed method surpassed the Gabor filter by 3.08 % and the modified Gabor filter by 2.95 %.

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2021 9th International Conference on Information and Communication Technology (ICoICT)

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