Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin

Fingerprint verification has drawn a lot of attention on its approach in biometric since it is one of the most important biometric technologies nowadays and it is widely used in several different applications and areas. It is applied in the forensic science area in order to identify the people that...

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Main Author:	Shamsudin, Farah Syadiyah
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Electronic Computers Computer Science Computer software Application software Configuration management Software protection Software measurement Algorithms Database management
Online Access:	https://ir.uitm.edu.my/id/eprint/69418/1/69418.pdf
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id	my-uitm-ir.69418
record_format	uketd_dc
spelling	my-uitm-ir.694182022-10-31T03:34:23Z Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin 2017-01 Shamsudin, Farah Syadiyah Electronic Computers. Computer Science Evolutionary programming (Computer science). Genetic algorithms Computer software Application software Configuration management Development. UML (Computer science) Software protection Software measurement Cryptography. Access control. Computer security Algorithms Database management Fingerprint verification has drawn a lot of attention on its approach in biometric since it is one of the most important biometric technologies nowadays and it is widely used in several different applications and areas. It is applied in the forensic science area in order to identify the people that are involved in the criminal scenes such as the victims and the suspects. A human’s fingerprint is unique and usually has its own patterns and ridges, which differs them from others’ fingerprints. However, there are some drawbacks that can cause low accuracy and low performance of the verification when the fingerprint images used are of low-quality causing some of the important details to be missing or hard to trace. Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. There will be two processes involved, which are feature extraction using minutiae-based method and also the implementation of the proposed algorithm, CSA. The results of False Matching Ratio (FMR) was 16.67% whilst the False Non-Matching Ratio (FNMR) was 33.33%. However, different number of generations applied in CSA will give different result of the verification process. Further studies can be made by using the same algorithm, but focusing more on the image enhancement and the feature extraction methods to improve the quality of the extraction of fingerprints. 2017-01 Thesis https://ir.uitm.edu.my/id/eprint/69418/ https://ir.uitm.edu.my/id/eprint/69418/1/69418.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Sa’dan, Siti ‘Aisyah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Sa’dan, Siti ‘Aisyah
topic	Electronic Computers Computer Science Electronic Computers Computer Science Computer software Application software Configuration management Electronic Computers Computer Science Software protection Software measurement Electronic Computers Computer Science Algorithms Database management
spellingShingle	Electronic Computers Computer Science Electronic Computers Computer Science Computer software Application software Configuration management Electronic Computers Computer Science Software protection Software measurement Electronic Computers Computer Science Algorithms Database management Shamsudin, Farah Syadiyah Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
description	Fingerprint verification has drawn a lot of attention on its approach in biometric since it is one of the most important biometric technologies nowadays and it is widely used in several different applications and areas. It is applied in the forensic science area in order to identify the people that are involved in the criminal scenes such as the victims and the suspects. A human’s fingerprint is unique and usually has its own patterns and ridges, which differs them from others’ fingerprints. However, there are some drawbacks that can cause low accuracy and low performance of the verification when the fingerprint images used are of low-quality causing some of the important details to be missing or hard to trace. Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. There will be two processes involved, which are feature extraction using minutiae-based method and also the implementation of the proposed algorithm, CSA. The results of False Matching Ratio (FMR) was 16.67% whilst the False Non-Matching Ratio (FNMR) was 33.33%. However, different number of generations applied in CSA will give different result of the verification process. Further studies can be made by using the same algorithm, but focusing more on the image enhancement and the feature extraction methods to improve the quality of the extraction of fingerprints.
format	Thesis
qualification_level	Bachelor degree
author	Shamsudin, Farah Syadiyah
author_facet	Shamsudin, Farah Syadiyah
author_sort	Shamsudin, Farah Syadiyah
title	Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
title_short	Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
title_full	Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
title_fullStr	Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
title_full_unstemmed	Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
title_sort	fingerprint verification using clonal selection algorithm / farah syadiyah shamsudin
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2017
url	https://ir.uitm.edu.my/id/eprint/69418/1/69418.pdf
_version_	1783735877080449024

Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin

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