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The minutia descriptor which describes characteristics of minutia, plays amajor role in fingerprint recognition. Typically, fingerprint recognitionsystems employ minutia descriptors to find potential correspondence betweenminutiae, and they use similarity between two minutia descriptors to calculateoverall similarity between two fingerprint images. A good minutia descriptorcan improve recognition accuracy of fingerprint recognition system and largelyreduce comparing time. A good minutia descriptor should have high ability todistinguish between different minutiae and at the same time should be robust indifficult conditions including poor quality image and small size image. It alsoshould be effective in computational cost of similarity among descriptors. Inthis paper, a robust minutia descriptor is constructed using Gabor wavelet andlinear discriminant analysis. This minutia descriptor has high distinguishingability, stability and simple comparing method. Experimental results on FVC2004and FVC2006 databases show that the proposed minutia descriptor is veryeffective in fingerprint recognition.

A Stable Minutia Descriptor based on Gabor Wavelet and Linear Discriminant Analysis