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Jurnal SINTA 2

MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 7 No. 2 (2014) · pp. 83–89

DOI
10.21609/jiki.v7i2.261
ISSN
2502-9274, 2088-7051
Published
2014-08-21
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Abstract Image segmentation is typically used to distinguish objects that exist in an image. However, it remains difficult to accommodate favourable thresholding in multimodal image histogram problem with specifically desired number of thresholds. This research proposes a novel approach to find thresholds in multimodal grayscale image histogram. This method consists of histogram smoothing, identification of peak(s) and valley(s), and merging process using hierarchical cluster analysis. Using five images that consisted of grayscale and converted-to-grayscale images. This method yields maximum value of accuracy, precision, and recall of 99.93%, 99.75%, and 99.75% respectively. These results are better than the similar peak finding method in multimodal grayscale image segmentation.

Keywords

Collaboration network of the authors

5 authors · 7 co-authorship links

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  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
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  • Same organisation
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Co-authorOrganisationJoint articles
Aris TjahyantoInstitut 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">MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS</dc:title>
	<dc:creator>Cahyono, Cahyono</dc:creator>
	<dc:creator>Prasetyo, Gigih</dc:creator>
	<dc:creator>Yoza, Adrianus</dc:creator>
	<dc:creator>Hani, Ramadhan</dc:creator>
	<dc:subject xml:lang="en-US">segmentation</dc:subject>
	<dc:subject xml:lang="en-US">multithresholding</dc:subject>
	<dc:subject xml:lang="en-US">peak finding</dc:subject>
	<dc:subject xml:lang="en-US">merging</dc:subject>
	<dc:subject xml:lang="en-US">cluster analysis</dc:subject>
	<dc:description xml:lang="en-US">Abstract

Image segmentation is typically used to distinguish objects that exist in an image. However, it remains difficult to accommodate favourable thresholding in multimodal image histogram problem with specifically desired number of thresholds. This research proposes a novel approach to find thresholds in multimodal grayscale image histogram. This method consists of histogram smoothing, identification of peak(s) and valley(s), and merging process using hierarchical cluster analysis. Using five images that consisted of grayscale and converted-to-grayscale images. This method yields maximum value of accuracy, precision, and recall of 99.93%, 99.75%, and 99.75% respectively. These results are better than the similar peak finding method in multimodal grayscale image segmentation.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2014-08-21</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/261</dc:identifier>
	<dc:identifier>10.21609/jiki.v7i2.261</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 7 No. 2 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 83-89</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v7i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/261/319</dc:relation>
</oai_dc:dc>