{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T23:32:35Z","timestamp":1780356755527,"version":"3.54.1"},"reference-count":53,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T00:00:00Z","timestamp":1668729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Clustering using fuzzy C-means (FCM) is a soft segmentation method that has been extensively investigated and successfully implemented in image segmentation. FCM is useful in various aspects, such as the segmentation of grayscale images. However, FCM has some limitations in terms of its selection of the initial cluster center. It can be easily trapped into local optima and is sensitive to noise, which is considered the most challenging issue in the FCM clustering algorithm. This paper proposes an approach to solve FCM problems in two phases. Firstly, to improve the balance between the exploration and exploitation of improved global best-guided artificial bee colony algorithm (IABC). This is achieved using a new search probability model called PIABC that improves the exploration process by choosing the best source of food which directly affects the exploitation process in IABC. Secondly, the fuzzy clustering algorithm based on PIABC, abbreviated as PIABC-FCM, uses the balancing of PIABC to avoid getting stuck into local optima while searching for the best solution having a set of cluster center locations of FCM. The proposed method was evaluated using grayscale images. The performance of the proposed approach shows promising outcomes when compared with other related works.<\/jats:p>","DOI":"10.3390\/s22228956","type":"journal-article","created":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T04:39:59Z","timestamp":1669005599000},"page":"8956","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Fuzzy Clustering Algorithm Based on Improved Global Best-Guided Artificial Bee Colony with New Search Probability Model for Image Segmentation"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2937-4327","authenticated-orcid":false,"given":"Waleed","family":"Alomoush","sequence":"first","affiliation":[{"name":"School of Information Technology, Skyline University College, Sharjah P.O. Box 1797, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1965-1869","authenticated-orcid":false,"given":"Osama A.","family":"Khashan","sequence":"additional","affiliation":[{"name":"Research and Innovation Centers, Rabdan Academy, Abu Dhabi P.O. Box 114646, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ayat","family":"Alrosan","sequence":"additional","affiliation":[{"name":"School of Information Technology, Skyline University College, Sharjah P.O. Box 1797, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8127-7233","authenticated-orcid":false,"given":"Essam H.","family":"Houssein","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Information, Minia University, Minia 61519, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8028-7918","authenticated-orcid":false,"given":"Hani","family":"Attar","sequence":"additional","affiliation":[{"name":"Department of Energy Engineering, Zarqa University, Zarqa 13132, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Alweshah","sequence":"additional","affiliation":[{"name":"Prince Abdullah Bin Ghazi Faculty of Information and Communication Technology, Al-Balqa Applied University, Al-Salt 19117, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1139-0705","authenticated-orcid":false,"given":"Fuad","family":"Alhosban","sequence":"additional","affiliation":[{"name":"CIS Department, Faculty of Computer Information Systems, Higher Colleges of Technology, Dubai P.O. 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