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- W45752882 abstract "Automatic Fingerprint Identification is a difficult and multidimensional problem. For this reason, the number of papers and techniques regarding this issue is numerous. The hardness of the problem lies with the fact that there is a large percentage of corrupted and partial fingerprint images. Throughout this Thesis, two methods were proposed for the Automatic Fingerprint Identification: a) the Automatic Fingerprint Identification based on registration techniques and b) the Automatic Fingerprint Identification based on the theory of Self Organizing Maps of Kohonen, setting the minutiae of the fingerprint images as input neurons of the Map. Furthermore, an important step prior to the application of the proposed automatic fingerprint identification methods is the pre-processing of these images by the development and implementation of a series of image processing techniques in order to enhance the image quality and to extract the minutiae which are then used for the fingerprint identification.In this Thesis, a substantial number of fingerprint images were used from the database VeriFingerSample_DB kai from the database DB3 of the competition FVC2004. The quantitative evaluation of both proposed automatic fingerprint identification methods were based on the Equal Error Rate (EER) criterion. According to this, the Automatic Fingerprint Identification based on the Self Organizing Maps outperformed against any other method based on registration techniques." @default.
- W45752882 created "2016-06-24" @default.
- W45752882 creator A5073600688 @default.
- W45752882 date "2011-07-14" @default.
- W45752882 modified "2023-09-27" @default.
- W45752882 title "Αυτόματη ταυτοποίηση βιομετρικών χαρακτηριστικών: εφαρμογή στα δακτυλικά αποτυπώματα" @default.
- W45752882 hasPublicationYear "2011" @default.
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