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Biometric System for Person Authentication Using Retinal Vascular Branching Pattern

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 16 No. 2 (2023) · pp. 141–149

DOI
10.21609/jiki.v16i2.1156
ISSN
2502-9274, 2088-7051
Published
2023-07-03
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

The person’s retina has its uniqueness that can be used as biometric recognition. The use of the retina as a marking feature in biometrics is more accurate in making calls, verification, and authentication. Retinal biometric characteristics are unique and difficult to manipulate, thus making the retinal biometric system one of the most reliable biometrics compared to other biometric characteristics. The retinal biometric system can be formed using extracted retinal vessels. The difficulty in extracting retinal vessels is a characteristic of retinal vessels. itself includes (central artery, central branch artery, central vein and central branch vein), the ratio of the thickness ratio between the different retinal arteries and veins (2:3), the location of the retinal artery and vein and the color. This complexity often results in errors in the retinal blood vessel extraction process, where not all blood vessel objects can be extracted properly which can reduce the accuracy of the retinal biometric system. This study will address the problem of extracting retinal vessels by proposing the use of an extraction method to produce truly unique retinal features to be included in the retinal biometric system by tracing all branches of the retinal vessels (consisting of: bifurcation, trifurcation and crossover). ). The accuracy results show that 99.81% of the images were correctly detected. The blood pattern is obtained by doing extraction which includes the preprocessing stage and is continued by doing the blood extraction stage. This pattern extraction result is used as a unique pattern to be included in the feature vector of the biometric system in identifying person based on the retina.

Collaboration network of the authors

25 authors · 64 co-authorship links · 11 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Gunadarma University
  • Universitas Putra Indonesia "YPTK"
  • University of Indonesia
  • Universitas Baiturrahmah
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Eka PatriyaGunadarma University10
Ernastuti ErnastutiGunadarma University4
Achmad FahruroziGunadarma University2
Djati KeramiUniversity of Indonesia2
Rodiah RodiahGunadarma University2
Ety SutantyGunadarma University2
MaukarGunadarma University1
Esti SetiyaningsihGunadarma University1
HandayaniAffiliation unknown1
Dina Kusuma AstutiGunadarma University1
Andriansyah LatifAffiliation unknown1
Suryarini WidodoGunadarma University1
Fitrianingsih FitrianingsihGunadarma University1
Dewi Putrie LestariGunadarma University1
Eri Prasetyo WibowoGunadarma University1
Jufriadif Na’amUniversitas Putra Indonesia "YPTK"1
Johan HarlanGunadarma University1
Julius SantonyUniversitas Putra Indonesia "YPTK"1
Catur SuharintoUniversitas Baiturrahmah1
Dewi Agushinta RGunadarma University1
Diana Tri SusetianigtiasAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc)
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	<dc:title xml:lang="en-US">Biometric System for Person Authentication Using Retinal Vascular Branching Pattern</dc:title>
	<dc:creator>Susetianingtias, Diana Tri</dc:creator>
	<dc:creator>Madenda, Sarifuddin</dc:creator>
	<dc:creator>Rodiah</dc:creator>
	<dc:creator>Arianty, Rini</dc:creator>
	<dc:description xml:lang="en-US">The person’s retina has its uniqueness that can be used as biometric recognition. The use of the retina as a marking feature in biometrics is more accurate in making calls, verification, and authentication. Retinal biometric characteristics are unique and difficult to manipulate, thus making the retinal biometric system one of the most reliable biometrics compared to other biometric characteristics. The retinal biometric system can be formed using extracted retinal vessels. The difficulty in extracting retinal vessels is a characteristic of retinal vessels. itself includes (central artery, central branch artery, central vein and central branch vein), the ratio of the thickness ratio between the different retinal arteries and veins (2:3), the location of the retinal artery and vein and the color. This complexity often results in errors in the retinal blood vessel extraction process, where not all blood vessel objects can be extracted properly which can reduce the accuracy of the retinal biometric system. This study will address the problem of extracting retinal vessels by proposing the use of an extraction method to produce truly unique retinal features to be included in the retinal biometric system by tracing all branches of the retinal vessels (consisting of: bifurcation, trifurcation and crossover). ). The accuracy results show that 99.81% of the images were correctly detected. The blood pattern is obtained by doing extraction which includes the preprocessing stage and is continued by doing the blood extraction stage. This pattern extraction result is used as a unique pattern to be included in the feature vector of the biometric system in identifying person based on the retina.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2023-07-03</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1156</dc:identifier>
	<dc:identifier>10.21609/jiki.v16i2.1156</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 16 No. 2 (2023): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 141-149</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v16i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1156/495</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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