Independent component analysis and its application in the fingerprint image preprocessing

Fenglan Long, Bin Kong
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引用次数: 7

Abstract

Independent component analysis (ICA) is a new method of signal separation developed in recent years. In this paper, the fundamental theory and algorithm of ICA are introduced, and the implementation of ICA method in fingerprint image preprocessing is discussed to separate the fingerprint from background texture. ICA requires the number of observations should be no less than that of independent sources. So it is impossible to apply ICA to a single image directly. The paper presents a technique to generate three input signals from one single image, and then, process it by ICA. The experiment results illustrate that ICA has better performance than traditional methods.
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独立分量分析及其在指纹图像预处理中的应用
独立分量分析(ICA)是近年来发展起来的一种新的信号分离方法。本文介绍了ICA的基本理论和算法,讨论了ICA方法在指纹图像预处理中的实现,实现了指纹与背景纹理的分离。ICA要求观测的数量不少于独立来源的观测数量。因此,直接将ICA应用于单个图像是不可能的。本文提出了一种从单幅图像中生成三个输入信号,然后进行ICA处理的方法。实验结果表明,ICA比传统方法具有更好的性能。
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