IMAGE STRUCTURE ANALYSIS BY 3-STAGES CLUSTERING

Authors

  • Roman Roman
  • Ruslan Tushnytskyy

DOI:

https://doi.org/10.47839/ijc.8.2.670

Keywords:

Cluster, clustering, visual pattern, hierarchical tree, rolling-up algorithm, scanning area, rectangles, integrated areas, structured images, structural features.

Abstract

An 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.

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Published

2014-08-01

How to Cite

Roman, R., & Tushnytskyy, R. (2014). IMAGE STRUCTURE ANALYSIS BY 3-STAGES CLUSTERING. International Journal of Computing, 8(2), 86-94. https://doi.org/10.47839/ijc.8.2.670

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Articles