{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T13:49:58Z","timestamp":1773236998445,"version":"3.50.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2016,4,18]],"date-time":"2016-04-18T00:00:00Z","timestamp":1460937600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["71331005"],"award-info":[{"award-number":["71331005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["71110107026"],"award-info":[{"award-number":["71110107026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61402429"],"award-info":[{"award-number":["61402429"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1007\/s00521-016-2300-1","type":"journal-article","created":{"date-parts":[[2016,4,18]],"date-time":"2016-04-18T07:27:42Z","timestamp":1460964462000},"page":"29-39","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["A novel clustering-based image segmentation via density peaks algorithm with mid-level feature"],"prefix":"10.1007","volume":"28","author":[{"given":"Yong","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhensong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiquan","family":"Qi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limeng","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,4,18]]},"reference":[{"issue":"1","key":"2300_CR1","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s00521-013-1544-2","volume":"27","author":"X Bai","year":"2016","unstructured":"Bai X, Wang W (2016) Principal pixel analysis and SVM for automatic image segmentation. Neural Comput Appl 27(1):45\u201358","journal-title":"Neural Comput Appl"},{"key":"2300_CR2","doi-asserted-by":"publisher","unstructured":"Nath SK, Palaniappan K (2009) Fast graph partitioning active contours for image segmentation using histograms. \u00a0EURASIP J Image Video process. doi:\n                        10.1155\/2009\/820986","DOI":"10.1155\/2009\/820986"},{"issue":"1","key":"2300_CR3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2008\/417293","volume":"2008","author":"M Hasanzadeh","year":"2008","unstructured":"Hasanzadeh M, Kasaei S (2008) Fuzzy image segmentation using membership connectedness. EURASIP J Adv Signal Process 2008(1):1\u201313","journal-title":"EURASIP J Adv Signal Process"},{"issue":"6","key":"2300_CR4","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1016\/j.patcog.2015.01.008","volume":"48","author":"X Cai","year":"2015","unstructured":"Cai X (2015) Variational image segmentation model coupled with image restoration achievements. Pattern Recogn 48(6):2029\u20132042","journal-title":"Pattern Recogn"},{"issue":"9","key":"2300_CR5","doi-asserted-by":"crossref","first-page":"2633","DOI":"10.1109\/TIP.2015.2419078","volume":"24","author":"B Hell","year":"2015","unstructured":"Hell B, Kassubeck M, Bauszat P, Eisemann M, Magnor M (2015) An approach toward fast gradient-based image segmentation. IEEE Trans Image Process 24(9):2633\u20132645","journal-title":"IEEE Trans Image Process"},{"issue":"9","key":"2300_CR6","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1016\/0031-3203(93)90135-J","volume":"26","author":"NR Pal","year":"1993","unstructured":"Pal NR, Pal SK (1993) A review on image segmentation techniques. Pattern Recogn 26(9):1277\u20131294","journal-title":"Pattern Recogn"},{"issue":"9","key":"2300_CR7","first-page":"72","volume":"3","author":"V Jumb","year":"2014","unstructured":"Jumb V, Sohani M, Shrivas A (2014) Color image segmentation using k-means clustering and otsus adaptive thresholding. Int J Innov Technol Explor Eng 3(9):72\u201376","journal-title":"Int J Innov Technol Explor Eng"},{"key":"2300_CR8","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1109\/AQTR.2006.254652","volume":"2","author":"A Oliver","year":"2006","unstructured":"Oliver A, Munoz X, Batlle J, Pacheco L, Freixenet J (2006) Improving clustering algorithms for image segmentation using contour and region information. IEEE Int Conf Autom Qual Test Robot 2:315\u2013320","journal-title":"IEEE Int Conf Autom Qual Test Robot"},{"issue":"1","key":"2300_CR9","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.compmedimag.2005.10.001","volume":"30","author":"KS Chuang","year":"2006","unstructured":"Chuang KS, Tzeng HL, Chen S, Wu J, Chen T (2006) Fuzzy c-means clustering with spatial information for image segmentation. Comput Med Imaging Gr 30(1):9\u201315","journal-title":"Comput Med Imaging Gr"},{"key":"2300_CR10","doi-asserted-by":"crossref","unstructured":"Kang B, Kim DW, Li Q (2005) Spatial homogeneity-based fuzzy c-means algorithm for image segmentation. In: Fuzzy systems and knowledge discovery. Springer Berlin Heidelberg, pp 462\u2013469","DOI":"10.1007\/11539506_59"},{"issue":"6","key":"2300_CR11","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/j.asoc.2012.02.010","volume":"12","author":"Z Ji","year":"2012","unstructured":"Ji Z, Xia Y, Chen Q, Sun Q, Xia D, Feng DD (2012) Fuzzy c-means clustering with weighted image patch for image segmentation. Appl Soft Comput 12(6):1659\u20131667","journal-title":"Appl Soft Comput"},{"issue":"3","key":"2300_CR12","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/42.996338","volume":"21","author":"MN Ahmed","year":"2002","unstructured":"Ahmed MN, Yamany SM, Mohamed N, Farag AA, Moriarty T (2002) A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans Med Imaging 21(3):193\u2013199","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"2300_CR13","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.1016\/j.patcog.2009.11.015","volume":"43","author":"Z Yu","year":"2010","unstructured":"Yu Z, Au OC, Zou R, Yu W, Tian J (2010) An adaptive unsupervised approach toward pixel clustering and color image segmentation. Pattern Recogn 43(5):1889\u20131906","journal-title":"Pattern Recogn"},{"issue":"4","key":"2300_CR14","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.1016\/j.asoc.2012.11.038","volume":"13","author":"KS Tan","year":"2013","unstructured":"Tan KS, Isa NAM, Lim WH (2013) Color image segmentation using adaptive unsupervised clustering approach. Appl Soft Comput 13(4):2017\u20132036","journal-title":"Appl Soft Comput"},{"key":"2300_CR15","first-page":"1766","volume":"4","author":"CJ Tilton","year":"1998","unstructured":"Tilton CJ (1998) Image segmentation by region growing and spectral clustering with natural convergence criterion. Int Geosci Remote Sens Symp 4:1766\u20131768","journal-title":"Int Geosci Remote Sens Symp"},{"issue":"5","key":"2300_CR16","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1007\/s00521-012-1101-4","volume":"23","author":"W Kong","year":"2013","unstructured":"Kong W, Hu S, Zhang J, Dai G (2013) Robust and smart spectral clustering from normalized cut. Neural Comput Appl 23(5):1503\u20131512","journal-title":"Neural Comput Appl"},{"issue":"7\u20138","key":"2300_CR17","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1007\/s00521-012-0959-5","volume":"22","author":"YK Lam","year":"2013","unstructured":"Lam YK, Tsang PWM, Leung CS (2013) PSO-based K-Means clustering with enhanced cluster matching for gene expression data. Neural Comput Appl 22(7\u20138):1349\u20131355","journal-title":"Neural Comput Appl"},{"issue":"6191","key":"2300_CR18","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1126\/science.1242072","volume":"344","author":"A Rodriguez","year":"2014","unstructured":"Rodriguez A, Laio A (2014) Clustering by fast search and find of density peaks. Science 344(6191):1492\u20131496","journal-title":"Science"},{"issue":"1","key":"2300_CR19","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s00521-012-1207-8","volume":"24","author":"S Ding","year":"2014","unstructured":"Ding S, Jia H, Zhang L, Jin F (2014) Research of semi-supervised spectral clustering algorithm based on pairwise constraints. Neural Comput Appl 24(1):211\u2013219","journal-title":"Neural Comput Appl"},{"key":"2300_CR20","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1016\/j.procs.2015.07.096","volume":"55","author":"Z Chen","year":"2015","unstructured":"Chen Z, Qi Z, Meng F, Cui L, Shi Y (2015) Image segmentation via improving clustering algorithms with density and distance. Proc Comput Sci 55:1015\u20131022","journal-title":"Proc Comput Sci"},{"issue":"1","key":"2300_CR21","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1146\/annurev.bioeng.2.1.315","volume":"2","author":"DL Pham","year":"2000","unstructured":"Pham DL, Xu C, Prince JL (2000) Current methods in medical image segmentation. Annu Rev Biomed Eng 2(1):315\u2013337","journal-title":"Annu Rev Biomed Eng"},{"issue":"2","key":"2300_CR22","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1080\/10255840903131878","volume":"13","author":"Z Ma","year":"2010","unstructured":"Ma Z, Tavares JM, Jorge RN, Mascarenhas T (2010) A review of algorithms for medical image segmentation and their applications to the female pelvic cavity. Comput Methods Biomech Biomed Eng 13(2):235\u2013246","journal-title":"Comput Methods Biomech Biomed Eng"},{"issue":"7\u20138","key":"2300_CR23","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1007\/s00521-013-1437-4","volume":"24","author":"HM Moftah","year":"2014","unstructured":"Moftah HM, Azar AT, Al-Shammari ET, Ghali NI, Hassanien AE, Shoman M (2014) Adaptive k-means clustering algorithm for MR breast image segmentation. Neural Comput Appl 24(7\u20138):1917\u20131928","journal-title":"Neural Comput Appl"},{"issue":"1","key":"2300_CR24","first-page":"11","volume":"1","author":"C Chandhok","year":"2012","unstructured":"Chandhok C, Chaturvedi S, Khurshid AA (2012) An approach to image segmentation using K-means clustering algorithm. Int J Inf Technol 1(1):11\u201317","journal-title":"Int J Inf Technol"},{"issue":"5","key":"2300_CR25","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1007\/s00521-011-0792-2","volume":"22","author":"DJ Hemanth","year":"2013","unstructured":"Hemanth DJ, Vijila CKS, Selvakumar AI, Anitha J (2013) Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation. Neural Comput Appl 22(5):1013\u20131022","journal-title":"Neural Comput Appl"},{"issue":"5","key":"2300_CR26","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1007\/s00521-012-1102-3","volume":"23","author":"BS Mousavi","year":"2013","unstructured":"Mousavi BS, Soleymani F, Razmjooy N (2013) Color image segmentation using neuro-fuzzy system in a novel optimized color space. Neural Comput Appl 23(5):1513\u20131520","journal-title":"Neural Comput Appl"},{"issue":"5","key":"2300_CR27","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.1109\/TSMCB.2007.902249","volume":"37","author":"W Tao","year":"2007","unstructured":"Tao W, Jin H, Zhang Y (2007) Color image segmentation based on mean shift and normalized cuts. IEEE Trans Syst Man Cybern Part B Cybern 37(5):1382\u20131389","journal-title":"IEEE Trans Syst Man Cybern Part B Cybern"},{"key":"2300_CR28","first-page":"1","volume":"2013","author":"MH Rahman","year":"2013","unstructured":"Rahman MH, Islam MR (2013) Segmentation of color image using adaptive thresholding and masking with watershed algorithm. Int Conf Inf Electron Vis 2013:1\u20136","journal-title":"Int Conf Inf Electron Vis"},{"key":"2300_CR29","doi-asserted-by":"publisher","unstructured":"Doll\u00e1r P, Tu Z, Perona P, Belongie S (2009) Integral Channel Features. In Cavallaro A, Prince S, Alexander D (eds) Proceedings of the British Machine Conference, pages 91.1-91.11. BMVA Press. doi:\n                        10.5244\/C.23.91","DOI":"10.5244\/C.23.91"},{"key":"2300_CR30","doi-asserted-by":"crossref","unstructured":"Porikli F (2005) Integral histogram: a fast way to extract histograms in cartesian spaces. In: IEEE computer society conference on computer vision and pattern recognition, 2005, vol 1. pp 829\u2013836","DOI":"10.1109\/CVPR.2005.188"},{"key":"2300_CR31","first-page":"34","volume":"4","author":"P Viola","year":"2004","unstructured":"Viola P, Jones M (2004) Robust real-time object detection. Int J Comput Vis 4:34\u201347","journal-title":"Int J Comput Vis"},{"key":"2300_CR32","doi-asserted-by":"crossref","unstructured":"Doll\u00e1r, P, Tu Z, Tao H and Belongie S (2007) Feature mining for image classification. In: IEEE conference on computer vision and pattern recognition, 2007. pp 1\u20138","DOI":"10.1109\/CVPR.2007.383046"},{"key":"2300_CR33","first-page":"949","volume":"6","author":"I Laptev","year":"2006","unstructured":"Laptev I (2006) Improvements of object detection using boosted histograms. BMVC 6:949\u2013958","journal-title":"BMVC"},{"key":"2300_CR34","unstructured":"Tu Z (2005) Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering. In: IEEE international conference on computer vision, 2005. pp 1589\u20131596"},{"key":"2300_CR35","doi-asserted-by":"crossref","unstructured":"Tuzel O, Porikli F, Meer P (2007) Human detection via classification on riemannian manifolds. In: IEEE conference on computer vision and pattern recognition, 2007. pp 1\u20138","DOI":"10.1109\/CVPR.2007.383197"},{"key":"2300_CR36","unstructured":"Zhu Q, Yeh MC, Cheng KT, Avidan S (2006) Fast human detection using a cascade of histograms of oriented gradients. In: IEEE computer society conference on computer vision and pattern recognition, vol 2. pp 1491\u20131498"},{"key":"2300_CR37","doi-asserted-by":"crossref","unstructured":"Lim JJ, Zitnick CL, Doll\u00e1r P (2013) Sketch tokens: a learned mid-level representation for contour and object detection. In: IEEE conference on computer vision and pattern recognition 2013. pp 3158\u20133165","DOI":"10.1109\/CVPR.2013.406"},{"key":"2300_CR38","volume-title":"The EM algorithm and extensions","author":"G McLachlan","year":"2007","unstructured":"McLachlan G, Krishnan T (2007) The EM algorithm and extensions. Wiley, Hoboken"},{"key":"2300_CR39","unstructured":"Martin D, Fowlkes C (2001) The Berkeley segmentation database and benchmark. Computer Science Department, Berkeley University. \n                        http:\/\/www.eecs.berkeley.edu\/Research\/Projects\/CS\/vision\/bsds"},{"issue":"20","key":"2300_CR40","first-page":"21","volume":"41","author":"C Mythili","year":"2012","unstructured":"Mythili C, Kavitha V (2012) Color image segmentation using ERKFCM. Int J Comput Appl 41(20):21\u201328","journal-title":"Int J Comput Appl"},{"issue":"8","key":"2300_CR41","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1167\/7.8.2","volume":"7","author":"CC Fowlkes","year":"2007","unstructured":"Fowlkes CC, Martin DR, Malik J (2007) Local figure-ground cues are valid for natural images. J Vis 7(8):2\u20132","journal-title":"J Vis"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-016-2300-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2300-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2300-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2300-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T22:21:32Z","timestamp":1559082092000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-016-2300-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,18]]},"references-count":41,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["2300"],"URL":"https:\/\/doi.org\/10.1007\/s00521-016-2300-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,4,18]]}}}