ISSN 3041-1823. Information Extraction and Processing. 2025. Issue 53 (129)
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Object localization in images based on clustering of attention zones
Kosarevych R.Y.
Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine, Lviv
Lviv Polytechnic National University, Lviv
Lutsyk O.A.
Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine, Lviv
Rusyn B.P.
Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine, Lviv
Ivchenko D.V.
Karpenko Physico-Mechanical Institute of the National Academy of Sciences of Ukraine, Lviv

https://doi.org/10.15407/vidbir2025.53.071

Keywords: object detection, point pattern, classification.

Cite as: Kosarevych, R.Y.; Lutsyk, O.A.; Rusyn, B.P.; Ivchenko, D.V. Object localization in images based on clustering of attention zones. Information Extraction and Processing 2025, 53(129), 71-76. DOI:https://doi.org/10.15407/vidbir2025.53.071

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Abstract

A novel methodology for the localization of objects within images is proposed. Contrary to the well-known deep learning approach, which involves the use of samples with matched boxes around similar objects to find their exact position on an image, a method based on object properties as the location of pixels with similar characteristics is developed. The notion of cluster point patterns to detect single parts of an object is used. The concept of an entire object as a composite of proximate, amalgamated clusters is proposed.

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