Image structure analysis by 3-stages clustering

dc.contributor.authorMelnyk, Roman
dc.contributor.authorTushnytskyy, Ruslan
dc.date.accessioned2018-12-10T11:37:17Z
dc.date.available2018-12-10T11:37:17Z
dc.date.issued2009
dc.description.abstractAn approach for decomposition of visual images by clustering and breaking them down into geometric figures is considered. Multilevel hierarchical clustering algorithm to form three emphasized levels of clusters such as rectangles, closed regions and integrated areas is proposed. Advantages of such decomposition in three stages are as follows: images covered by rectangles are planned to be formatted and compressed, image fragments could be taken for the preliminary pattern recognition or could easily be corrected, hierarchically constructed fragments are good material to form pattern features for searching procedures. The algorithm complexity, the proposed approach of scanning searching area to reduce it, the rolling up criteria and key parameters for its control are investigated. The results of pattern analysis by structure features for some practical problems are presented in the article.uk_UA
dc.identifier.citationMelnyk, R. Image structure analysis by 3-stages clustering [Text] / Roman Melnyk, Ruslan Tushnytskyy // Computing = Комп’ютинг. - 2009. - Vol. 8, is. 2. - P. 86-94.uk_UA
dc.identifier.urihttp://dspace.tneu.edu.ua/handle/316497/32137
dc.publisherТНЕУuk_UA
dc.subjectclusteruk_UA
dc.subjectclusteringuk_UA
dc.subjectvisual patternuk_UA
dc.subjecthierarchical treeuk_UA
dc.subjectrolling-up algorithmuk_UA
dc.subjectscanning areauk_UA
dc.subjectrectanglesuk_UA
dc.subjectintegrated areasuk_UA
dc.subjectstructured imagesuk_UA
dc.subjectstructural featuresuk_UA
dc.titleImage structure analysis by 3-stages clusteringuk_UA
dc.typeArticleuk_UA

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