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Jurnal SINTA 2

LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 8 No. 2 (2015) · pp. 111–118

DOI
10.21609/jiki.v8i2.309
ISSN
2502-9274, 2088-7051
Published
2015-08-27
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

In recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris). Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP) method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP), a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI) detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is needed

Keywords

Collaboration network of the authors

40 authors · 74 co-authorship links · 14 across different organisations · showing the 40 most connected

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

  • Institut Teknologi Sepuluh Nopember
  • Hasanuddin University
  • Universitas Airlangga
  • University of Brawijaya
  • University of Indonesia
  • North Sumatra Islamic University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Diana PurwitasariInstitut Teknologi Sepuluh Nopember10
Handayani TjandrasaInstitut Teknologi Sepuluh Nopember9
Anny YuniartiInstitut Teknologi Sepuluh Nopember5
Siti RochimahInstitut Teknologi Sepuluh Nopember4
Mutmainnah MuchtarInstitut Teknologi Sepuluh Nopember3
Yuna SugianelaInstitut Teknologi Sepuluh Nopember2
Imam KuswardayanInstitut Teknologi Sepuluh Nopember2
Hari GinardiInstitut Teknologi Sepuluh Nopember2
Isye ArieshantiInstitut Teknologi Sepuluh Nopember2
Ahmad SaikhuInstitut Teknologi Sepuluh Nopember2
Syavira Tiara ZulkarnainInstitut Teknologi Sepuluh Nopember2
Hilya TsaniyaInstitut Teknologi Sepuluh Nopember2
Hendra MesraHasanuddin University2
Riyanarto SarnoInstitut Teknologi Sepuluh Nopember2
Eha Renwi AstutiUniversitas Airlangga2
Ramadhan Hardani PutraUniversitas Airlangga2
Faida RoyaniAffiliation unknown2
Dewi RosidaAffiliation unknown2
Bilqis AmaliahInstitut Teknologi Sepuluh Nopember1
M. Rahmat WidyantoUniversity of Indonesia1
Agus Zainal ArifinInstitut Teknologi Sepuluh Nopember1
Mohammad ZarkasiInstitut Teknologi Sepuluh Nopember1
Fransisca Joanet PontohHasanuddin University1
Amil Ahmad IlhamHasanuddin University1
Ingrid NurtanioHasanuddin University1
Evan TanuwijayaInstitut Teknologi Sepuluh Nopember1
Bernardinus ArisandiAffiliation unknown1
Arya Yudhi WijayaInstitut Teknologi Sepuluh Nopember1
Yuita Arum SariUniversity of Brawijaya1
Ratih Kartika DewiUniversity of Brawijaya1
Lim Yohanes StefanusAffiliation unknown1
Yudhi PurwanantoInstitut Teknologi Sepuluh Nopember1
Junaidi JunaidiNorth Sumatra Islamic University1
Tri Anggraeny FettyAffiliation unknown1
Lalu Muhammad DzakiAffiliation unknown1
Rosdiana RahmawatiAffiliation unknown1
Rizky Yuniar HakkunAffiliation 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">LOCAL LINE BINARY PATTERN FOR FEATURE EXTRACTION ON PALM VEIN RECOGNITION</dc:title>
	<dc:creator>Sari, Jayanti Yusmah</dc:creator>
	<dc:creator>Fatichah, Chastine</dc:creator>
	<dc:creator>Suciati, Nanik</dc:creator>
	<dc:subject xml:lang="en-US">Fuzzy k-NN</dc:subject>
	<dc:subject xml:lang="en-US">LLBP</dc:subject>
	<dc:subject xml:lang="en-US">Local Line Binary Pattern</dc:subject>
	<dc:subject xml:lang="en-US">palm vein</dc:subject>
	<dc:description xml:lang="en-US">In recent years, palm vein recognition has been studied to overcome problems in conventional systems in biometrics technology (finger print, face, and iris). Those problems in biometrics includes convenience and performance. However, due to the clarity of the palm vein image, the veins could not be segmented properly. To overcome this problem, we propose a palm vein recognition system using Local Line Binary Pattern (LLBP) method that can extract robust features from the palm vein images that has unclear veins. LLBP is an advanced method of Local Binary Pattern (LBP), a texture descriptor based on the gray level comparison of a neighborhood of pixels. There are four major steps in this paper, Region of Interest (ROI) detection, image preprocessing, features extraction using LLBP method, and matching using Fuzzy k-NN classifier. The proposed method was applied on the CASIA Multi-Spectral Image Database. Experimental results showed that the proposed method using LLBP has a good performance with recognition accuracy of 97.3%. In the future, experiments will be conducted to observe which parameter that could affect processing time and recognition accuracy of LLBP is needed</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2015-08-27</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/309</dc:identifier>
	<dc:identifier>10.21609/jiki.v8i2.309</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 8 No. 2 (2015): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 111 - 118</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v8i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/309/344</dc:relation>
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