Independent component analysis and its application in the fingerprint image preprocessing

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.