dc.contributor.advisor |
Chefranov, Alexander |
|
dc.contributor.author |
Mriheel, Abdurahman Ibrahim |
|
dc.date.accessioned |
2021-11-05T06:15:49Z |
|
dc.date.available |
2021-11-05T06:15:49Z |
|
dc.date.issued |
2020 |
|
dc.date.submitted |
2020-02 |
|
dc.identifier.citation |
Mriheel, Abdurahman Ibrahim. (2020). Real Fingerprint Detection System (RFDS) Based on Image Quality Measures and Six Classifiers. Thesis (M.S.), Eastern Mediterranean University, Institute of Graduate Studies and Research, Dept. of Computer Engineering, Famagusta: North Cyprus. |
en_US |
dc.identifier.uri |
http://hdl.handle.net/11129/5158 |
|
dc.description |
Master of Science in Computer Engineering. Thesis (M.S.)--Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering, 2020. Supervisor: Assoc. Prof. Dr. Alexander Chefranov. |
en_US |
dc.description.abstract |
Fingerprint detection in biometrics is an important field of study in our new modern
world, many forensic departments around the world use fingerprints as the key to
detect criminals and bring them justice. To improve the accuracy of fingerprint
detection system we implemented a Real Fingerprint Detection System (RFDS) that
has high performance level of detecting real and fake fingerprint images. In this thesis,
we present an RFDS system based on image quality measures (IQM’s) to detect real
fingerprint images and fake fingerprint images. We performed different RFDS
experiments with 25, 10, 15, and 5 IQM’s; they showed sufficient quality of real and
fake fingerprint images detection. We compared our RFDS using 25, 15, 10, and 5
IQM’s with RFDS that has used 25 IQMs. Based on the comparison in this thesis we
can conclude that the best result from all these RFDS is the one with 25 IQMs, because
it’s HTER score is the minimum one with 0.3%, and the worst RFDS is the one with
the 15 IQMs which has the maximum HTER score with 14.8%.
Keywords: Biometrics, Image Quality Measure, Real and Fake Fingerprint Image,
Classifier. |
en_US |
dc.description.abstract |
ÖZ:
Biyometride parmak izi tespiti, yeni modern dünyamızda önemli bir çalışma alanıdır,
dünyadaki birçok adli departman, suçluları tespit etmek ve adalet getirmek için parmak
izi kullanmaktadır. Parmak izi algılama sisteminin doğruluğunu artırmak için, gerçek
ve sahte parmak izi görüntülerini algılamada yüksek performans seviyesine sahip bir
Gerçek Parmak İzi Algılama sistemi (RFDS) uyguladık. Bu tezde, gerçek parmak izi
görüntülerini ve sahte parmak izi görüntülerini tespit etmek için görüntü kalitesi
ölçümlerine (IQM'ler) dayanan bir RFDS sistemi sunuyoruz. 25, 15, 10 ve 5 IQM'lerle
farklı RFDS deneyleri gerçekleştirdik; yeterli kalitede gerçek ve sahte parmak izi
görüntüleri algılama özelliği gösterdiler. 25, 15, 10 ve 5 IQM kullanarak RFDS'imizi
25 IQM kullanan RFDS ile karşılaştırdık. Bu tezdeki karşılaştırmaya dayanarak, tüm
bu RFDS'lerden en iyi sonucun 25 IQM'ye sahip olduğu sonucuna varabiliriz, çünkü
HTER puanı % 0.3 ile en düşük olanıdır ve en kötü RFDS ise %14.8 HTER puanı ile
15 IQM'ye sahip olanıdır.
Anahtar Kelimeler: Biyometri, Görüntü Kalitesi Ölçüsü, Gerçek Ve Sahte Parmak
Izi Görüntüsü, Sınıflandırıcı. |
en_US |
dc.language.iso |
eng |
en_US |
dc.publisher |
Eastern Mediterranean University (EMU) - Doğu Akdeniz Üniversitesi (DAÜ) |
en_US |
dc.rights |
info:eu-repo/semantics/openAccess |
en_US |
dc.subject |
Computer Engineering |
en_US |
dc.subject |
Computer Vision |
en_US |
dc.subject |
Image Processing |
en_US |
dc.subject |
Biometrics |
en_US |
dc.subject |
Image Quality Measure |
en_US |
dc.subject |
Real and Fake Fingerprint Image |
en_US |
dc.subject |
Classifier |
en_US |
dc.title |
Real Fingerprint Detection System (RFDS) Based on Image Quality Measures and Six Classifiers |
en_US |
dc.type |
masterThesis |
en_US |
dc.contributor.department |
Eastern Mediterranean University, Faculty of Engineering, Dept. of Computer Engineering |
en_US |