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Metodologia para extração de características invariantes à rotação em Imagens de Impressões Digitais

Cristina Mônica Dornelas MazettiAdilson Gonzaga

The objective of this research is to present algorithms that can be applied on images containingfingerprints in order to extract certain features, which are invariant to an eventual rotation in the given image. In the preprocessing stage, the "Canny" Border Detector is used, resulting in a binary, fine tuned image. For the minutiae extraction, the Crossing Number method is used, which extracts local aspects such as minutiae endings and bifurcations. The direction of local ridges is ignored because, in rotated images, the permanence conditions of the biometric attributes are not fulfilled. The process of matching fingerprints uses two arrays (one for ridge endings and the other for bifurcations), which are generated by the extraction of the minutiae, considering the (x,y) coordinate of the given minutiae stored in the arrays, and calculating its Euclidean Distance relating to the Center of Mass of the minutiae distribution, for each of its types (ending or bifurcation). Thus, both images are similar when the Euclidean Distance between the arrays of each image, distinct by the type of each minutiae, is minimal. The problems found in the initial experimental results are also mentioned, along with suggestions for solutions to be presented in this masters degree research.

http://www.lbd.dcc.ufmg.br/colecoes/wvc/2005/0010.pdf

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