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MULTI-CLASS REGION MERGING FOR INTERACTIVE IMAGE SEGMENTATION USING HIERARCHICAL CLUSTERING ANALYSIS

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 12 No. 2 (2019) · pp. 113–121

DOI
10.21609/jiki.v12i2.757
ISSN
2502-9274, 2088-7051
Published
2019-07-08
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

In interactive image segmentation, distance calculation between regions and sequence of region merging is being an important thing that needs to be considered to obtain accurate segmentation results. Region merging without regard to label in Hierarchical Clustering Analysis causes the possibility of two different labels merged into a cluster and resulting errors in segmentation. This study proposes a new multi-class region merging strategy for interactive image segmentation using the Hierarchical Clustering Analysis. Marking is given to regions that are considered as objects and background, which are then referred as classes. A different label for each class is given to prevent any classes with different label merged into a cluster. Based on experiment, the mean value of ME and RAE for the results of segmentation using the proposed method are 0.035 and 0.083, respectively. Experimental results show that giving the label on each class is effectively used in multi-class region merging.

Keywords

Collaboration network of the authors

40 authors · 93 co-authorship links · 10 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
  • 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
Gulpi Qorik Oktagalu PratamasunuAffiliation unknown3
Anny YuniartiInstitut Teknologi Sepuluh Nopember3
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
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
Andi Baso KaswarInstitut Teknologi Sepuluh Nopember1
Saprina MamaseInstitut Teknologi Sepuluh Nopember1
Saiful Bahri MusaInstitut Teknologi Sepuluh Nopember1
Ahmad Mustofa HadiInstitut Teknologi Sepuluh Nopember1
Christian Sri Kusuma AdityaInstitut Teknologi Sepuluh Nopember1
Mamluatul Hani`ahInstitut Teknologi Sepuluh Nopember1
Aryo HartoInstitut Teknologi Sepuluh Nopember1
Arif FadllullahInstitut Teknologi Sepuluh Nopember1
Dasrit Debora KamudiInstitut Teknologi Sepuluh Nopember1
Muhamad NasirInstitut Teknologi Sepuluh Nopember1

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">MULTI-CLASS REGION MERGING FOR INTERACTIVE IMAGE SEGMENTATION USING HIERARCHICAL CLUSTERING ANALYSIS</dc:title>
	<dc:creator>Aisyah, Khairiyyah Nur</dc:creator>
	<dc:creator>Anggraini, Syadza</dc:creator>
	<dc:creator>Putriwijaya, Novi Nur</dc:creator>
	<dc:creator>Arifin, Agus Zainal</dc:creator>
	<dc:creator>Indraswari, Rarasmaya</dc:creator>
	<dc:creator>Navastara, Dini Adni</dc:creator>
	<dc:subject xml:lang="en-US">Interactive Segmentation</dc:subject>
	<dc:subject xml:lang="en-US">Multi-class Region Merging</dc:subject>
	<dc:subject xml:lang="en-US">Hierarchical Clustering</dc:subject>
	<dc:description xml:lang="en-US">In interactive image segmentation, distance calculation between regions and sequence of region merging is being an important thing that needs to be considered to obtain accurate segmentation results. Region merging without regard to label in Hierarchical Clustering Analysis causes the possibility of two different labels merged into a cluster and resulting errors in segmentation. This study proposes a new multi-class region merging strategy for interactive image segmentation using the Hierarchical Clustering Analysis. Marking is given to regions that are considered as objects and background, which are then referred as classes. A different label for each class is given to prevent any classes with different label merged into a cluster. Based on experiment, the mean value of ME and RAE for the results of segmentation using the proposed method are 0.035 and 0.083, respectively. Experimental results show that giving the label on each class is effectively used in multi-class region merging.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2019-07-08</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/757</dc:identifier>
	<dc:identifier>10.21609/jiki.v12i2.757</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 12 No. 2 (2019): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 113-121</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v12i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/757/418</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2019 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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