Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/7473
Title: A new algorithm for minutiae extraction and matching in fingerprint
Authors: Noor, Azad
Advisors: Balachandran, W
Keywords: Fingerprint biometrics;Image processing in fingerprints;Fingerprint template;Minutiae based matching;Fingerprint image enhancement
Issue Date: 2012
Publisher: Brunel University School of Engineering and Design PhD Theses
Abstract: A novel algorithm for fingerprint template formation and matching in automatic fingerprint recognition has been developed. At present, fingerprint is being considered as the dominant biometric trait among all other biometrics due to its wide range of applications in security and access control. Most of the commercially established systems use singularity point (SP) or ‘core’ point for fingerprint indexing and template formation. The efficiency of these systems heavily relies on the detection of the core and the quality of the image itself. The number of multiple SPs or absence of ‘core’ on the image can cause some anomalies in the formation of the template and may result in high False Acceptance Rate (FAR) or False Rejection Rate (FRR). Also the loss of actual minutiae or appearance of new or spurious minutiae in the scanned image can contribute to the error in the matching process. A more sophisticated algorithm is therefore necessary in the formation and matching of templates in order to achieve low FAR and FRR and to make the identification more accurate. The novel algorithm presented here does not rely on any ‘core’ or SP thus makes the structure invariant with respect to global rotation and translation. Moreover, it does not need orientation of the minutiae points on which most of the established algorithm are based. The matching methodology is based on the local features of each minutiae point such as distances to its nearest neighbours and their internal angle. Using a publicly available fingerprint database, the algorithm has been evaluated and compared with other benchmark algorithms. It has been found that the algorithm has performed better compared to others and has been able to achieve an error equal rate of 3.5%.
Description: This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.
URI: http://bura.brunel.ac.uk/handle/2438/7473
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Theses

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