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dc.contributor.authorUkrit Marungen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.description.abstractClustering method has been applied in many fields, including data mining, machine learning, information retrieval, and image analysis. In this paper, we propose a visual clustering method based on the genetic algorithm (GA) and image manipulation. The proposed method automatically determines the number of clusters in a binary image without using distance measures. There are three processes of the proposed method, i.e., creating the object table, mapping the object table into a binary image, and clustering objects in the binary image by using the GA and image manipulation. The effectiveness of the proposed method is tested on both synthetic data sets and a real data set. The experimental results show that the proposed method can effectively construct the clusters in both synthetic and real data sets. © 2011 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleVisual clustering method using genetic algorithm and image manipulationen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2011 International Symposium on Intelligent Signal Processing and Communications Systems: "The Decade of Intelligent and Green Signal Processing and Communications", ISPACS 2011en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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