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Jurnal SINTA 2

PARAMETER SIGMOID TRANSFORM CONTRAST ENHANCEMENT FOR DENTAL RADIOGRAPH CLASSIFICATION AND NUMBERING SYSTEM

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 8 No. 2 (2015) · pp. 60–67

DOI
10.21609/jiki.v8i2.303
ISSN
2502-9274, 2088-7051
Published
2015-08-27
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Dental record is a method that is used to identify a person. The identification process needs a system that could recognize each individual tooth automatically. The similar intensity level between the teeth and the gums is one of the main problem in tooth identification in a dental radiograph. The intensity problem could influence the segmentation process of the system. In this paper, we proposed a new contrast enhancement by using parameter sigmoid transform to increase the segmentation accuracy. There are five main steps in this method. The first step is to fix the contrast of the image with the proposed method. The next steps are to segment the teeth using horizontal and vertical integral projection, feature extraction, and classification using Support Vector Machine (SVM). The last step is teeth numbering. The experiment result using the proposed method have an accuracy rate of 88% for classification and 73% for teeth numbering.

Keywords

Collaboration network of the authors

40 authors · 94 co-authorship links · 13 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
  • Lampung University
  • University of Brawijaya
  • State University of Makassar
  • Institut Teknologi dan Sains Mandala
  • Universitas Islam Negeri Raden Intan Lampung
  • 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 Nopember6
Dini Adni NavastaraInstitut Teknologi Sepuluh Nopember5
Rarasmaya IndraswariInstitut Teknologi Sepuluh Nopember3
Chastine FatichahInstitut Teknologi Sepuluh Nopember3
Gulpi Qorik Oktagalu PratamasunuAffiliation unknown3
Munjiah Nur SaadahInstitut Teknologi Sepuluh Nopember2
Rigga Widar AtmagiInstitut Teknologi Sepuluh Nopember2
Dyah S. RahayuInstitut Teknologi Sepuluh Nopember2
Khoirul UmamInstitut Teknologi Sepuluh Nopember2
Darlis HerumurtiInstitut Teknologi Sepuluh Nopember2
Safri AdamInstitut Teknologi Sepuluh Nopember2
Nanik SuciatiInstitut Teknologi Sepuluh Nopember2
Dyah Darma AndayaniState University of Makassar2
Wawan GunawanUniversitas Islam Negeri Raden Intan Lampung1
⁠Undang RosidinLampung University1
Nina KadaritnaLampung University1
Naser JawasInstitut Teknologi Sepuluh Nopember1
Randy Cahya WihandikaUniversity of Brawijaya1
Go Frendi GunawanInstitut Teknologi Sepuluh Nopember1
Sonny Christiano GosariaInstitut Teknologi Sepuluh Nopember1
Yuita Arum SariUniversity of Brawijaya1
Evy Kamilah RatnasariInstitut Teknologi Sepuluh Nopember1
Siti MutrofinInstitut Teknologi Sepuluh Nopember1
Mutmainnah MuchtarInstitut Teknologi Sepuluh Nopember1
Jayanti Yusmah SariInstitut Teknologi Sepuluh Nopember1
Mohammad ZarkasiInstitut Teknologi Sepuluh Nopember1
Fidi Wincoko PutroInstitut Teknologi Sepuluh Nopember1
Khadijah Fahmi Hayati HolleInstitut Teknologi Sepuluh Nopember1
Mamluatul Hani`ahInstitut Teknologi Sepuluh Nopember1
Abdul WahidInstitut Teknologi dan Sains Mandala1
Sardar Faroq Ahmad KhanAffiliation unknown1
Fitria Nur Dina SalamAffiliation unknown1
Magfirah AuliaAffiliation unknown1
Rezki Nurul Jariah S.IntamAffiliation 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">PARAMETER SIGMOID TRANSFORM CONTRAST ENHANCEMENT FOR DENTAL RADIOGRAPH CLASSIFICATION AND NUMBERING SYSTEM</dc:title>
	<dc:creator>Kaswar, Andi Baso</dc:creator>
	<dc:creator>Mamase, Saprina</dc:creator>
	<dc:creator>Musa, Saiful Bahri</dc:creator>
	<dc:creator>Hadi, Ahmad Mustofa</dc:creator>
	<dc:creator>Yuniarti, Anny</dc:creator>
	<dc:creator>Arifin, Agus Zainal</dc:creator>
	<dc:subject xml:lang="en-US">contrast enhancement</dc:subject>
	<dc:subject xml:lang="en-US">dental radiograph</dc:subject>
	<dc:subject xml:lang="en-US">parameter sigmoid transform.</dc:subject>
	<dc:description xml:lang="en-US">Dental record is a method that is used to identify a person. The identification process needs a system that could recognize each individual tooth automatically. The similar intensity level between the teeth and the gums is one of the main problem in tooth identification in a dental radiograph. The intensity problem could influence the segmentation process of the system. In this paper, we proposed a new contrast enhancement by using parameter sigmoid transform to increase the segmentation accuracy. There are five main steps in this method. The first step is to fix the contrast of the image with the proposed method. The next steps are to segment the teeth using horizontal and vertical integral projection, feature extraction, and classification using Support Vector Machine (SVM). The last step is teeth numbering. The experiment result using the proposed method have an accuracy rate of 88% for classification and 73% for teeth numbering.</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>
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	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/303</dc:identifier>
	<dc:identifier>10.21609/jiki.v8i2.303</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); 60 - 67</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/303/338</dc:relation>
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