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4-D pattern structure features by three stages clustering algorithm for image analysis and classification

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Abstract

An approach for decomposition of visual image by clustering, pattern analysis and classification by structure features is considered. Hierarchical clusters such as rectangles, closed regions and integrated areas are objects of investigation. By hierarchically constructed fragments, the 4-D pattern structure features are formulated. To reduce the clustering algorithm complexity, the scanning area approach is proposed. The results of pattern analysis and classification by structure features for some images are presented.

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Authors and Affiliations

  1. Computer Sciences and Information Technologies Institute, Lviv Polytechnic National University, S.Bandery Str 12, Lviv, 79013, Ukraine

    Roman Melnyk & Ruslan Tushnytskyy

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  1. Roman Melnyk
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  2. Ruslan Tushnytskyy
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Correspondence to Roman Melnyk.

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Melnyk, R., Tushnytskyy, R. 4-D pattern structure features by three stages clustering algorithm for image analysis and classification. Pattern Anal Applic 16, 201–211 (2013). https://doi.org/10.1007/s10044-013-0326-x

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  • DOI: https://doi.org/10.1007/s10044-013-0326-x

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