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- W2891561635 abstract "The minutia descriptor which describes characteristics of minutia, plays a major role in fingerprint recognition. Typically, fingerprint recognition systems employ minutia descriptors to find potential correspondence between minutiae, and they use similarity between two minutia descriptors to calculate overall similarity between two fingerprint images. A good minutia descriptor can improve recognition accuracy of fingerprint recognition system and largely reduce comparing time. A good minutia descriptor should have high ability to distinguish between different minutiae and at the same time should be robust in difficult conditions including poor quality image and small size image. It also should be effective in computational cost of similarity among descriptors. In this paper, a robust minutia descriptor is constructed using Gabor wavelet and linear discriminant analysis. This minutia descriptor has high distinguishing ability, stability and simple comparing method. Experimental results on FVC2004 and FVC2006 databases show that the proposed minutia descriptor is very effective in fingerprint recognition." @default.
- W2891561635 created "2018-09-27" @default.
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- W2891561635 date "2018-09-06" @default.
- W2891561635 modified "2023-10-14" @default.
- W2891561635 title "A Stable Minutia Descriptor based on Gabor Wavelet and Linear Discriminant Analysis" @default.
- W2891561635 cites W2014470493 @default.
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- W2891561635 doi "https://doi.org/10.48550/arxiv.1809.03326" @default.
- W2891561635 hasPublicationYear "2018" @default.
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