An approach based on simulated annealing to optimize the performance of extraction of the flower region using mean-shift segmentation

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dc.authoridKarasulu, Bahadir/0000-0001-8524-874X
dc.contributor.authorKarasulu, Bahadir
dc.date.accessioned2025-01-27T20:12:10Z
dc.date.available2025-01-27T20:12:10Z
dc.date.issued2013
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractFlower identification and recognition are tedious and difficult tasks even for humans. Image segmentation based on automatic flower extraction is an essential step for computer-aided flower image recognition and retrieval processes. Furthermore, there is a challenge for segmentation of the object(s) s) from natural complex background in color images. In this study, a novel performance optimization approach for image segmentation, i.e. simulated annealing-based mean-shift segmentation (SAMS), is proposed and implemented. It is based on the simulated annealing solution of quadratic assignment problem model treated as an image segmentation process using feature-based mean-shift (MS) clustering on color images. The proposed approach is designed to realize a global and unsupervised (i.e., fully automatic) segmentation. It is a modified and optimized version of Backprojection-based mean-shift segmentation (BackMS) method. In conducted segmentation experiments, the performance results of SAMS approach are compared with the ones of BackMS method. Comparison of overall performance results and statistical analysis (i.e., Wilcoxon signed rank median test) show that SAMS approach improves the performance of BackMS method. It is measured as 49.33% when using object bounding boxes and as 51.33% when using object pixel regions. (C) 2013 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.asoc.2013.07.019
dc.identifier.endpage4785
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.issue12
dc.identifier.scopus2-s2.0-84886728363
dc.identifier.scopusqualityQ1
dc.identifier.startpage4763
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2013.07.019
dc.identifier.urihttps://hdl.handle.net/20.500.12428/20869
dc.identifier.volume13
dc.identifier.wosWOS:000325759200024
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Bv
dc.relation.ispartofApplied Soft Computing
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectSimulated annealing
dc.subjectFlower extraction
dc.subjectMean shift segmentation
dc.subjectQuadratic assignment problem
dc.subjectPerformance optimization
dc.titleAn approach based on simulated annealing to optimize the performance of extraction of the flower region using mean-shift segmentation
dc.typeArticle

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