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Real-time fingerprint image enhancement with a two-stage algorithm and block–local normalization

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Fingerprint enhancement is a key step in the Automated Fingerprint Identification System. Because of poor quality of a fingerprint the algorithm for feature extraction may extract features incorrectly, which affects incorrect fingerprint match and consequently inefficient fingerprint-based identity verification. Fingerprint image enhancement techniques are based on enhancement in spatial domain or in frequency domain or in a combination of both. This article presents a block–local normalization algorithm and a technique for speeding up a two-stage algorithm for low-quality fingerprint image enhancement with image learning, which first enhances a fingerprint image in the spatial domain and then in the frequency domain. The normalization technique includes an algorithm with block–local normalization with different block sizes. Experimental results obtained on a public database FVC2004 showed that the presented normalization technique speeds up and improves a state-of-the-art two-stage algorithm, provides better results in comparison with global and local normalization, and positively affects fingerprint image enhancement, and consequently improves the efficiency of the automated fingerprint identification system.

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This operation was partly financed by the European Union, European Social Fund. This operation was implemented in the framework of the Operational Programme for Human Resources Development for the Period 2007–2013, Priority axis 1: Promoting entrepreneurship and adaptability, Main type of activity 1.1.: Experts and researchers for competitive enterprises.

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Correspondence to Marko Kočevar.

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Kočevar, M., Kotnik, B., Chowdhury, A. et al. Real-time fingerprint image enhancement with a two-stage algorithm and block–local normalization. J Real-Time Image Proc 13, 773–782 (2017).

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