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Gabor Filter-based Multiple Enrollment Fingerprint Recognition

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Fred Kaggwa, John Ngubiri, Florence Tushabe
10.5120/ijca2016909210

Fred Kaggwa, John Ngubiri and Florence Tushabe. Article: Gabor Filter-based Multiple Enrollment Fingerprint Recognition. International Journal of Computer Applications 139(7):32-38, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Fred Kaggwa and John Ngubiri and Florence Tushabe},
	title = {Article: Gabor Filter-based Multiple Enrollment Fingerprint Recognition},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {7},
	pages = {32-38},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Minutiae-based matching techniques have been widely used in the implementation of multiple enrollment fingerprint recognition systems. However, these techniques suffer the difficulty of automatically extracting all minutiae points due to failure to detect the complete ridge structures of a fingerprint. With poor quality fingerprint images, detection of minutiae points as well as describing all the local ridge structures is difficult. It is also difficult to quickly match two fingerprints that have a difference in the number of unregistered minutiae. Non-minutiae based techniques such as Gabor filtering are rich in terms of distinguishing features and can be used as an alternative since they capture both the local and global details in a fingerprint. This paper presents a Gabor filter-based approach; the first of the kind to implement a verification multiple enrollment based fingerprint recognition system. The Gabor filter-based multiple enrollment fingerprint recognition method was compared with a spectral minutiae-based method using two fingerprint databases; FVC 2000-DB2-A and FVC 2006-DB2-A. Although the minutiae-based method outperformed the Gabor filter-based method, the results attained from the later are promising and can be a good basis for implementing Gabor filter-based techniques in designing multiple enrollment based fingerprint systems.

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Keywords

Multiple enrollment, Gabor Filter-based matching, Spectral Minutiae-based matching, Recognition performance, memory consumption, matching speed.