{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T17:02:43Z","timestamp":1793120563032,"version":"4.5.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2015,12,9]],"date-time":"2015-12-09T00:00:00Z","timestamp":1449619200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2017,4]]},"DOI":"10.1007\/s13042-015-0471-1","type":"journal-article","created":{"date-parts":[[2015,12,9]],"date-time":"2015-12-09T18:58:35Z","timestamp":1449687515000},"page":"699-710","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Hybrid ABC-ANN for pavement surface distress detection and classification"],"prefix":"10.1007","volume":"8","author":[{"given":"Anan","family":"Banharnsakun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2015,12,9]]},"reference":[{"key":"471_CR1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1061\/(ASCE)1076-0342(2000)6:1(24)","volume":"6","author":"KCP Wang","year":"2000","unstructured":"Wang KCP (2000) Designs and implementations of automated systems for pavement surface distress survey. Journal of Infrastruct Syst 6:24\u201332","journal-title":"Journal of Infrastruct Syst"},{"key":"471_CR2","first-page":"20","volume":"989354","author":"S Chambon","year":"2011","unstructured":"Chambon S, Moliard J-M (2011) Automatic road pavement assessment with image processing: review and comparison. Int J Geophys 989354:20","journal-title":"Int J Geophys"},{"key":"471_CR3","doi-asserted-by":"crossref","unstructured":"Jing L, Aiqin Z (2010) Pavement crack distress detection based on image analysis. In: Proceedings of the international conference on machine vision and human-machine interface, pp 576\u2013579","DOI":"10.1109\/MVHI.2010.10"},{"key":"471_CR4","first-page":"368","volume-title":"CCTA 2010, Part IV, IFIP AICT 347","author":"A Ouyang","year":"2011","unstructured":"Ouyang A, Luo C, Zhou C (2011) Surface distresses detection of pavement based on digital image processing. In: Li D, Liu Y, Chen Y (eds) CCTA 2010, Part IV, IFIP AICT 347. Springer, Berlin, pp 368\u2013375"},{"key":"471_CR5","doi-asserted-by":"crossref","first-page":"398","DOI":"10.4103\/0256-4602.62225","volume":"27","author":"Y Hu","year":"2010","unstructured":"Hu Y, Zhao C-X, Wang H-N (2010) Automatic pavement crack detection using texture and shape descriptors. IETE Tech Rev 27:398\u2013405","journal-title":"IETE Tech Rev"},{"key":"471_CR6","doi-asserted-by":"crossref","unstructured":"Salari E, Ouyang D (2012) An image-based pavement distress detection and classification. In: Proceedings of the IEEE international conference on electro\/information technology, pp 1\u20136","DOI":"10.1109\/EIT.2012.6220706"},{"key":"471_CR7","first-page":"298","volume-title":"ICIC 2011, LNCS 6838","author":"S Wang","year":"2011","unstructured":"Wang S, Tang W (2011) Pavement crack segmentation algorithm based on local optimal threshold of cracks density distribution. In: Huang D-S et al (eds) ICIC 2011, LNCS 6838. Springer, Heidelberg, pp 298\u2013302"},{"key":"471_CR8","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)CP.1943-5487.0000488","author":"L Sun","year":"2015","unstructured":"Sun L, Kamaliardakani M, Zhang Y (2015) Weighted neighborhood pixels segmentation method for automated detection of cracks on pavement surface images. J Comput Civ Eng. doi: 10.1061\/(ASCE)CP.1943-5487.0000488","journal-title":"J Comput Civ Eng"},{"key":"471_CR9","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.aei.2011.01.002","volume":"25","author":"C Koch","year":"2011","unstructured":"Koch C, Brilakis I (2011) Pothole detection in asphalt pavement images. Adv Eng Inform 25:507\u2013515","journal-title":"Adv Eng Inform"},{"key":"471_CR10","first-page":"027007.1","volume":"45","author":"J Zhou","year":"2006","unstructured":"Zhou J, Huang PS, Chiang F-P (2006) Wavelet-based pavement distress detection and evaluation. Opt Eng 45:027007.1","journal-title":"Opt Eng"},{"key":"471_CR11","doi-asserted-by":"crossref","first-page":"013017.1","DOI":"10.1117\/1.2177650","volume":"15","author":"Y Huang","year":"2006","unstructured":"Huang Y, Xu B (2006) Automatic inspection of pavement cracking distress. J Electron Imaging 15:013017.1\u2013013017.6","journal-title":"J Electron Imaging"},{"key":"471_CR12","doi-asserted-by":"crossref","unstructured":"Li Q, Liu X (2008) Novel approach to pavement image segmentation based on neighboring difference histogram method. In: Proceedings of the congress on image and signal processing, pp 792\u2013796","DOI":"10.1109\/CISP.2008.13"},{"key":"471_CR13","doi-asserted-by":"crossref","unstructured":"Salari E, Yu X (2011) Pavement distress detection and classification using a genetic algorithm. In: Proceedings of the IEEE applied imagery pattern recognition workshop: imaging for decision making, pp 1\u20135","DOI":"10.1109\/AIPR.2011.6176378"},{"key":"471_CR14","doi-asserted-by":"crossref","unstructured":"Omran MGH, Engelbrecht AP, Salman A (2005) Differential evolution methods for unsupervised image classification. In: Proceedings of the IEEE congress on evolutionary computation, pp 966\u2013973","DOI":"10.1109\/CEC.2005.1554795"},{"key":"471_CR15","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.amc.2006.06.057","volume":"184","author":"P-Y Yin","year":"2007","unstructured":"Yin P-Y (2007) Multilevel minimum cross entropy threshold selection based on particle swarm optimization. Appl Math Comput 184:503\u2013513","journal-title":"Appl Math Comput"},{"key":"471_CR16","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1016\/j.patrec.2009.11.018","volume":"31","author":"C Xu","year":"2010","unstructured":"Xu C, Duan H (2010) Artificial bee colony (ABC) optimized edge potential function (EPF) approach to target recognition for low-altitude aircraft. Pattern Recogn Lett 31:1759\u20131772","journal-title":"Pattern Recogn Lett"},{"key":"471_CR17","first-page":"1","volume":"2012","author":"LS Bartolome","year":"2012","unstructured":"Bartolome LS, Bandala AA, Llorente C, Dadios EP (2012) Vehicle parking inventory system utilizing image recognition through artificial neural networks. Proc IEEE TENCON 2012:1\u20135","journal-title":"Proc IEEE TENCON"},{"key":"471_CR18","volume-title":"Digital image processing","author":"RC Gonzalez","year":"2006","unstructured":"Gonzalez RC, Woods RE (2006) Digital image processing, 3rd edn. Prentice-Hall, New York","edition":"3"},{"key":"471_CR19","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9:62\u201366","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"471_CR20","doi-asserted-by":"crossref","first-page":"2345","DOI":"10.1016\/S0167-8655(03)00060-6","volume":"24","author":"PL Rosin","year":"2003","unstructured":"Rosin PL, Ioannidis E (2003) Evaluation of global image thresholding for change detection. Pattern Recogn Lett 24:2345\u20132356","journal-title":"Pattern Recogn Lett"},{"key":"471_CR21","unstructured":"Oliveira H, Correia PL (2009) Automatic road crack segmentation using entropy and image dynamic thresholding. In: Proceedings of the 17th European signal processing conference, pp 622\u2013626"},{"key":"471_CR22","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","volume":"29","author":"JN Kapur","year":"1985","unstructured":"Kapur JN, Sahoo PK, Wong AKC (1985) A new method for grey-level picture thresholding using the entropy of the histogram. Comput Vis Graph Image Process 29:273\u2013285","journal-title":"Comput Vis Graph Image Process"},{"key":"471_CR23","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10462-012-9328-0","volume":"42","author":"D Karaboga","year":"2014","unstructured":"Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intell Rev 42:21\u201357","journal-title":"Artif Intell Rev"},{"key":"471_CR24","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural networks for pattern recognition","author":"CM Bishop","year":"1995","unstructured":"Bishop CM (1995) Neural networks for pattern recognition. Clarendon Press, Oxford"},{"key":"471_CR25","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/0734-189X(86)90002-2","volume":"35","author":"J Serra","year":"1986","unstructured":"Serra J (1986) Introduction to mathematical morphology. Comput Vis Graph Image Process 35:283\u2013305","journal-title":"Comput Vis Graph Image Process"},{"key":"471_CR26","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0165-1684(98)00167-4","volume":"72","author":"P-Y Yin","year":"1999","unstructured":"Yin P-Y (1999) A fast scheme for optimal thresholding using genetic algorithms. Sig Process 72:85\u201395","journal-title":"Sig Process"},{"key":"471_CR27","doi-asserted-by":"crossref","unstructured":"Zhang R, Liu J (2006) Underwater image segmentation with maximum entropy based on particle swarm optimization (PSO). In: Proceedings of the first international multi-symposiums on computer and computational sciences (IMSCCS\u201906), pp 360\u2013362","DOI":"10.1109\/IMSCCS.2006.280"},{"key":"471_CR28","unstructured":"Pei Z, Zhao Y, Liu Z (2009) Image segmentation based on differential evolution algorithm. In: Proceedings of the international conference on image analysis and signal processing (IASP 2009), pp 48\u201351"},{"key":"471_CR29","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1117\/1.1631315","volume":"13","author":"M Sezgin","year":"2004","unstructured":"Sezgin M, Sankur B (2004) Survey over image thresholding techniques and quantitative performance evaluation. J Electron Imaging 13:146\u2013165","journal-title":"J Electron Imaging"},{"key":"471_CR30","unstructured":"Banharnsakun A (2015) Data set of pavement surface distress. http:\/\/www.cirlab.org\/dataset\/distress_feature.data"},{"key":"471_CR31","doi-asserted-by":"crossref","unstructured":"Li NN, Hou XD, Yang XY, Dong YF (2009) Automation recognition of pavement surface distress based on support vector machine. In: Proceedings of the 2nd international conference on intelligent networks and intelligent systems, pp 346\u2013349","DOI":"10.1109\/ICINIS.2009.95"},{"key":"471_CR32","doi-asserted-by":"crossref","unstructured":"Shi L, Gao C, Zhang J (2012) Pavement distress image recognition based on multilayer autoencoders. In: Proceedings of 4th international conference on artificial intelligence and computational intelligence, pp 666\u2013673","DOI":"10.1007\/978-3-642-33478-8_82"},{"key":"471_CR33","doi-asserted-by":"crossref","first-page":"11","DOI":"10.7307\/ptt.v26i1.1477","volume":"26","author":"L Li","year":"2014","unstructured":"Li L, Sun L, Ning G, Tan S (2014) Automatic pavement crack recognition based on bp neural network. PROMET-Traffic & Transp 26:11\u201322","journal-title":"PROMET-Traffic & Transp"},{"key":"471_CR34","unstructured":"Chang C-C, Lin C-J (2015) LIBSVM\u2013a library for support vector machines. https:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvm"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-015-0471-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-015-0471-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-015-0471-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-015-0471-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,12]],"date-time":"2024-06-12T23:13:25Z","timestamp":1718234005000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-015-0471-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,9]]},"references-count":34,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,4]]}},"alternative-id":["471"],"URL":"https:\/\/doi.org\/10.1007\/s13042-015-0471-1","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,9]]}}}