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Examination of Various Approaches to Possibly Improve the Existing Algorithms Applied in Fingerprint Recognition Systems
Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
2007 (English)Independent thesis Basic level (degree of Bachelor)Student thesis
Abstract [en]

In human fingerprints there are plenty of small details which are the discontinuities in the ridges, denoted minutiae. Minutiae-based matching is a wellknown method applied in fingerprint recognition. Minutiae defines a representative feature vector of a fingerprint. Due to quality variations in fingerprint images a preprocessing in form of binarization and skeltonization is applied, before obtaining the feature vector. Once the features of each fingerprint are obtained, a matching algorithm carries out the comparison task between those features vectors to determine if they match. In the new binarization function, quality at the same time that speed are essential requirements. In order to sort out this subject, areas of an adaptive size are analyzed instead of a pixel by pixel examination. The binarization algorithm is implemented in the frequency domain with the concept of ridges and their orientations. Skeletonization is needed as a preprocessing step with the aim of obtaining the minutiae from the fingerprint. It is a matter of fact that the high quality skeleton is an emphatic factor in the fingerprint recognition. A robust skeletoned image will ensure a reliable extraction of features. Several strategies relating to the application of filters will be discussing in order to speed-up the iteractive thinning algorithms. The proposed minutiae matching algorithms explore though several variations of the geometric hashing method. Based on minutiae features, new approaches are presented to obtain an effectiveness function.

Place, publisher, year, edition, pages
2007. , 78 p.
Keyword [en]
Fingerprint Recognition
National Category
Signal Processing
URN: urn:nbn:se:bth-5529Local ID: diva2:832914
Available from: 2015-04-22 Created: 2007-06-27 Last updated: 2015-06-30Bibliographically approved

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