Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas

Fingerprint-based identification has been known and used for a very long time. The fingerprint image contains narrow ridges separated by narrow background valleys. Most Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching due to its uniqueness. Minutiae are essentially...

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Main Author:	Sulong, Siti Masrina
Format:	Thesis
Language:	English
Published:	2002
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/4391/1/SitiMasrinaSulongMFSKSM2003.pdf
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id	my-utm-ep.4391
record_format	uketd_dc
spelling	my-utm-ep.43912018-01-28T05:29:14Z Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas 2002-10 Sulong, Siti Masrina QA75 Electronic computers. Computer science Fingerprint-based identification has been known and used for a very long time. The fingerprint image contains narrow ridges separated by narrow background valleys. Most Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching due to its uniqueness. Minutiae are essentially terminations and bifurcations of the ridge lines that constitute a fingerprint pattern. According to conventional technique, minutiae detection is applied to a binarized and thmned image. This requires time consuming and lots of information may be lost during the processes. Thus, Maio and Maltoni (1997) proposed a method to detect minutiae in gray scale fingerprint images based on ridge line following algorithm, which is to trail the ridge line according to the fingerprint directional image. Even though, Wse minutiae still detected during the process. Based on these errors, an improved Ridge Line Following Algorithm has developed which consist of five processes; tangent direction computation, sectioning and maximum determination, end point detection, bifurcation point detection, and post-processing. A precise tangent value will contribute to a detection of true minutiae. Sobel operator is applied as other alternative of tangent direction computation. A reversing technique is proposed in order to detect true end point in the fingerprint image. A post-processing technique is also added to minutiae extraction process to determine the true minutiae. Raw fingerprint images and filtered images (noise removal and enhancement) are tested to determine the efficiency of the algorithm developed. The improved algorithm has applied to 350 image samples obtained from National Institute of Standards and Technology (NIST). As a result, techniques proposed in this research gives a higher percentage of 60 percent in true minutiae detection compared to previous techniques, although it still could not detect all the true minutiae correctly. 2002-10 Thesis http://eprints.utm.my/id/eprint/4391/ http://eprints.utm.my/id/eprint/4391/1/SitiMasrinaSulongMFSKSM2003.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Sulong, Siti Masrina Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
description	Fingerprint-based identification has been known and used for a very long time. The fingerprint image contains narrow ridges separated by narrow background valleys. Most Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching due to its uniqueness. Minutiae are essentially terminations and bifurcations of the ridge lines that constitute a fingerprint pattern. According to conventional technique, minutiae detection is applied to a binarized and thmned image. This requires time consuming and lots of information may be lost during the processes. Thus, Maio and Maltoni (1997) proposed a method to detect minutiae in gray scale fingerprint images based on ridge line following algorithm, which is to trail the ridge line according to the fingerprint directional image. Even though, Wse minutiae still detected during the process. Based on these errors, an improved Ridge Line Following Algorithm has developed which consist of five processes; tangent direction computation, sectioning and maximum determination, end point detection, bifurcation point detection, and post-processing. A precise tangent value will contribute to a detection of true minutiae. Sobel operator is applied as other alternative of tangent direction computation. A reversing technique is proposed in order to detect true end point in the fingerprint image. A post-processing technique is also added to minutiae extraction process to determine the true minutiae. Raw fingerprint images and filtered images (noise removal and enhancement) are tested to determine the efficiency of the algorithm developed. The improved algorithm has applied to 350 image samples obtained from National Institute of Standards and Technology (NIST). As a result, techniques proposed in this research gives a higher percentage of 60 percent in true minutiae detection compared to previous techniques, although it still could not detect all the true minutiae correctly.
format	Thesis
qualification_level	Master's degree
author	Sulong, Siti Masrina
author_facet	Sulong, Siti Masrina
author_sort	Sulong, Siti Masrina
title	Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
title_short	Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
title_full	Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
title_fullStr	Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
title_full_unstemmed	Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
title_sort	pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2002
url	http://eprints.utm.my/id/eprint/4391/1/SitiMasrinaSulongMFSKSM2003.pdf
_version_	1747814524093726720

Pengesanan minutiae imej cap jari berskala kelabu menggunakan algoritma susuran batas

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