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All Journal JURNAL EVALUASI PENDIDIKAN Auladuna SIGMA: Jurnal Pendidikan Matematika AlphaMath: Journal of Mathematics Education JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Jurnal Penjaminan Mutu MATEMATIKA DAN PEMBELAJARAN JURNAL MathEdu (Mathematic Education Journal) GERVASI: Jurnal Pengabdian kepada Masyarakat DIDAKTIKA : Jurnal Kependidikan Jurnal khabar: Komunikasi dan Penyiaran Islam Al-Qalam: Jurnal Kajian Islam dan Pendidikan Jurnal Pendidikan Dasar dan Keguruan Jumat Informatika: Jurnal Pengabdian Masyarakat Jurnal Tadris Matematika (JTMT) Jumat Pendidikan: Jurnal Pengabdian Masyarakat ELIPS: Jurnal Pendidikan Matematika AKM: Aksi Kepada Masyarakat Catimore: Jurnal Pengabdian Kepada Masyarakat Prosiding Seminar Nasional Pendidikan Matematika, Universitas Mulawarman MEGA: Jurnal Pendidikan Matematika Jurnal Penjaminan Mutu Jurnal Masyarakat Madani Indonesia Ar-Riyadhiyyat: Jurnal Pendidikan Matematika Teknovokasi : Jurnal Pengabdian Masyarakat Vokatek : Jurnal Pengabdian Masyarakat PEDAMATH: Journal on Pedagogical Mathematics Mangente: Jurnal Pengabdian kepada Masyarakat Jurnal Tadris Matematika (JTMT) Jurnal Mimbar: Media Intelektual Muslim Dan Bimbingan Rohani Jurnal Pendidikan Dasar dan Keguruan Journal on Mathematics Education Research Pedagogy: Journal of Multidisciplinary Education Mosaic: Jurnal Pengabdian Kepada Masyarakat Indonesian Mathematics Education Journal
Nurjannah Nurjannah
Universitas Islam Ahmad Dahlan
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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Journal : JOIV : International Journal on Informatics Visualization

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Hyperellipsoid Cluster Merging using Hierarchical Analysis of Hyperellipsoid Cluster for Image Segmentation Kaswar, Andi Baso; Nurjannah, Nurjannah; Djawad, Yasser Abd
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.2815

Abstract

Segmentation is one of the critical stages in digital image processing and computer vision. However, conventional clustering-based segmentation methods, such as K-means and Fuzzy C-means (FCM), are still unable to accurately segment images whose pixels form hyperellipsoid clusters in the feature space. In addition, previous clustering methods based on Mahalanobis distance measurement require a long computational time and still have the potential to fall into local optima. Therefore, in this paper, we propose a new method for segmenting images whose pixels form hyperellipsoid clusters in the feature space, utilizing hyperellipsoid clusters merging through hierarchical analysis of hyperellipsoid clusters. The proposed method comprises eight main steps: histogram extraction, peak and valley identification, elimination of low peaks and valleys, peak combination for centroid initialization, initialization of cluster pixel members, elimination of ineffective clusters, hyperellipsoid cluster merging, and finalization of cluster members. This paper presents a novel approach to segmenting color images by employing an initial centroid discovery process and cluster analysis that considers cluster covariance for cluster merging. Based on the tests conducted using various image characteristics, the proposed method can provide 97.42% accuracy, 98.02% precision, 97.15% recall, 2.58 misclassification error, 97.54 F1-score, 95.29% intersection over union, 97.52% dice coefficient, and 15.37 seconds of computation time. The test results are superior to those of conventional methods, such as K-means and FCM. Based on these results, it can be concluded that the proposed method can effectively segment images with high accuracy. The proposed method can serve as an alternative approach to image segmentation.
Co-Authors A. Mutahharah A. Mutahharah A. Mutahharah Mutahharah A. Rezky Pratiwi Alawiyah, Desi Aliyah, Nurul Almi Khaerah AM, Andi Wahdania Amdar, Fetti Fatricia Andi Akram Nur Risal Andi Auliya Ismuna Andi Auliya Ismunandar Andi Auliya Ismunandar Andi Baso Kaswar Andi Baso Kaswar Andi Baso Kaswar Andi Muhammad Fatahillah Anggy Heriyanti Anggy Heriyanti Anis Fuadi Asisah Nur Fariana Astuti, Ninik Danial Danial David Adrian Fachrezi Derek David Adrian Fahrezi Derek David Adrian Fahrezi Derek Dewi Dewi Dewi Dewi Dirawan, Gufran Darma Eka Irmawati Eman Wahyudi Kasim Fachry Abda El Rahman Fahmita Sari Fahmita Sari Fahmita Sari Faridah Faridah Fathahillah Fathahillah Fetti Fatricia Amdar Fhatiah Adiba Fitriani Fitriani Fitriani Fitriani Fitriani Fitriani Haerati Hamka Handayani, Resky Hasmiati, Hasmiati Herdiawal Herdiawal Herianto Herianto Heriyanti, Anggy Husnul Khatimah Husnul Muawiah Husnul Muawiah Irmayanti Irmayanti . Irmayanti Iramaynti Irmayanti Irmayanti, Irmayanti Islamiah, Nurul Ismawati Haris Kurnia Wahyu Prima M. Mailhuddin Maqfirah, Zazirah Megawati Megawati Meysarawati Arsyad Mirna Mirna Mirna Nurlili Mirna, Mirna Mirnawati Muh. Rais Mulkiyan, Mulkiyan Musdalifah Mustamir Mustamir Mytra, Prima Nirmalasari, Nirmalasari Nur Farolai Nur Hikmah Nur Muhlifa Nahli Nur Muhlifa Nahli Nuraziza Rahmah Nuraziza Rahmah Nuraziza Rahmah Nurazizah Nurazizah Amir Nurazizah Nurazizah, Nurazizah Nurbaitul Afyan Nurfadhilah Nurfadhilah Nurfiana Nurfiana Nurhalimah Nurhalimah Nurhalisa Nurhalisa Nurhalizah Nurhalizah Nurlili Nurlili Nurul Fawzani Nurul Islamiah Nurul Islamiah Rahma Melati Amir Resky Handayani Ridwansyah Salmawati Sudirman P Syarifuddin Umar, Firdaniati Wafiq Azizah Yasser Abd Djawad Zazirah Maqfirah Zazirah Maqfirah