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<p><b>Abstract</b>—In this work, we introduce a new approach to automatic fingerprint classification. The directional image is partitioned into "homogeneous" connected regions according to the fingerprint topology, thus giving a synthetic representation which can be exploited as a basis for the classification. A set of dynamic masks, together with an optimization criterion, are used to guide the partitioning. The adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point, which can be conceived as a continuous classification. Different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification. Experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature: As to fingerprint retrieval based on continuous classification, our method gives the best performance and exhibits a very high robustness.</p>
Fingerprint classification, directional image, partitioning algorithms, continuous classification, biometric systems.

A. Lumini, R. Cappelli, D. Maio and D. Maltoni, "Fingerprint Classification by Directional Image Partitioning," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 21, no. , pp. 402-421, 1999.
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