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Title	Abstract	Start	End
Robust Fingerprint Recognition and Classification (details)	The main aim of this project is to apply global models to fingerprint images for robust extraction of local features. These so-called minutiae features are used within classic pattern recognition algorithms for fingerprint matching (recognition, authentication). The direction field of a fingerprint is a crucial parameter for extracting minutiae features. Nevertheless many fingerprint images are of such poor quality, that the direction of the field can not be extracted for certain regions in the image. On the other hand it has been shown that if one can properly "guess" the direction, it is possible to apply enhancement algorithms which adaptively improve the clarity of ridges and furrows of such regions. In order to do this "guess work" computationally, a model for the directional field of a fingerprint must be applied during the extraction process. In another concept the extracted parameters of the directional field model can be employed for fingerprint classification.	2006	2008