{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T14:24:01Z","timestamp":1781533441040,"version":"3.54.5"},"reference-count":37,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2016,8,5]],"date-time":"2016-08-05T00:00:00Z","timestamp":1470355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2017,1,13]]},"abstract":"<jats:p>Although how to deal well with images corrupted with noise is a commonly encountered task in image segmentation, the design of efficient and robust segmentation algorithms still keeps a challenging research topic. In this paper, a robust fuzzy-clustering-based image segmentation algorithm is presented to effectively segment noisy images. The proposed algorithm is derived from both the conventional fuzzy c-means (FCM) clustering algorithm and the hidden Markov random field (HMRF) model with the capability of incorporating spatial information. The performance of the proposed algorithm is experimentally evaluated with the comparison algorithms. Experimental results on synthetic and real images demonstrate the effectiveness of the proposed algorithm.<\/jats:p>","DOI":"10.3233\/jifs-151345","type":"journal-article","created":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T14:34:42Z","timestamp":1471358082000},"page":"177-188","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["A robust fuzzy clustering algorithm using mean-field-approximation based hidden Markov random field model for image segmentation"],"prefix":"10.1177","volume":"32","author":[{"given":"Aiguo","family":"Chen","sequence":"first","affiliation":[{"name":"School of Digital Media, Jiangnan University, Wuxi, Jiangsu, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shitong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Digital Media, Jiangnan University, Wuxi, Jiangsu, P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2016,8,5]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(98)00019-X"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2012.09.015"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-0450-1"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2004.831165"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/42.712135"},{"key":"e_1_3_2_7_2","first-page":"416","article-title":"A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics","author":"Martin D.","year":"2001","unstructured":"MartinD., FowlkesC., TalD., and MalikJ., A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, In Proc 8th IEEE Int Conf Comput Vis, Vancouver, BC, Canada, 2 2001, pp. 416\u2013423.","journal-title":"Proc 8th IEEE Int Conf Comput Vis, Vancouver"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(02)00027-4"},{"key":"e_1_3_2_9_2","first-page":"86","article-title":"Fuzzy c-means clustering with regularization by K-L information","author":"Ichihashi H.","year":"1997","unstructured":"IchihashiH., MiyagishiK., and HondaK., Fuzzy c-means clustering with regularization by K-L information, IEEE International Conference on Fuzzy System (1997), 86\u201392.","journal-title":"IEEE International Conference on Fuzzy System"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1986.tb01412.x"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.2307\/2987782"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"e_1_3_2_13_2","volume-title":"Clustering Algorithms","author":"Hartigan J.","year":"1975","unstructured":"HartiganJ., Clustering Algorithms, John Wiley & Sons, New York, NY, 1975."},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(02)00372-X"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2009.12.007"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2013.05.029"},{"key":"e_1_3_2_17_2","first-page":"237","article-title":"Color image processing and applications","author":"Plataniotis K.","year":"2013","unstructured":"PlataniotisK., and VenetsanopoulosA.N., Color image processing and applications, Springer Science & Business Media (2013), 237\u2013278.","journal-title":"Springer Science & Business Media"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICNC.2007.226"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(03)00067-9"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2003.12.008"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/42.996338"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1979.4310076"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2004.840099"},{"key":"e_1_3_2_24_2","volume-title":"GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation","author":"Wang Q.","year":"2012","unstructured":"WangQ., GMM-Based Hidden Markov Random Field for Color Image and 3D Volume Segmentation, Computer Science, 2012."},{"key":"e_1_3_2_25_2","first-page":"24","article-title":"A measure for objective evaluation of image segmentation algorithms","author":"Unnikrishnan R.","year":"2005","unstructured":"UnnikrishnanR., PantofaruC., and HebertM., A measure for objective evaluation of image segmentation algorithms, IEEE International Conference on Computer Vision 2005, pp. 24\u201341.","journal-title":"IEEE International Conference on Computer Vision"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2004.831165"},{"key":"e_1_3_2_27_2","first-page":"1498","article-title":"Markov random field image models and their applications to computer vision","author":"Geman S.","year":"1987","unstructured":"GemanS., and GraffigneC., Markov random field image models and their applications to computer vision, Proceeding of the International Congress of Mathematicians Berkeley, 1987, pp. 1498\u20131517.","journal-title":"Proceeding of the International Congress of Mathematicians Berkeley"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1984.4767596"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2040763"},{"key":"e_1_3_2_30_2","first-page":"181","article-title":"Image segmentation using fuzzy clustering: A survey, pp","author":"Naz S.","year":"2010","unstructured":"NazS., MajeedH., and IrshadH., Image segmentation using fuzzy clustering: A survey, pp, International Conference on Emerging Technologies (2010), 181\u2013186.","journal-title":"International Conference on Emerging Technologies"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2008.924317"},{"issue":"5","key":"e_1_3_2_32_2","first-page":"83","article-title":"Image Segmentation by using threshold techniques","volume":"2","author":"Al-amri S.S.","year":"2010","unstructured":"Al-amriS.S., and KalyankarN.V., Image Segmentation by using threshold techniques, Journal of Computing 2(5) (2010), 83\u201386.","journal-title":"Journal of Computing"},{"key":"e_1_3_2_33_2","unstructured":"TheodoridisS. and KoutroumbasK. Pattern Recognition Academic Press Technology & Engineering 2008."},{"issue":"4","key":"e_1_3_2_34_2","first-page":"166","article-title":"Image Segmentation Techniques: A Survey","volume":"1","author":"Khan W.","year":"2013","unstructured":"KhanW., Image Segmentation Techniques: A Survey, Journal of Image and Graphics 1(4) (2013), 166\u2013170.","journal-title":"Journal of Image and Graphics"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.1991.0132"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2014.2334595"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.3233\/IFS-141130"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35286-7_9"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-151345","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-151345","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-151345","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:38:33Z","timestamp":1777455513000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-151345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,5]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,1,13]]}},"alternative-id":["10.3233\/JIFS-151345"],"URL":"https:\/\/doi.org\/10.3233\/jifs-151345","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,5]]}}}