{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T06:41:40Z","timestamp":1762065700505,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T00:00:00Z","timestamp":1661817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This article considers the problem of image segmentation based on its representation as an undirected weighted graph. Image segmentation is equivalent to partitioning a graph into communities. The image segment corresponds to each community. The growing area algorithm search communities on the graph. The average edge weight in the community is a measure of the separation quality. The correlation radius determines the number of next nearest neighbors connected by edges. Edge weight is a function of the difference between color and geometric coordinates of pixels. The exponential law calculates the weights of an edge in a graph. The computer experiment determines the parameters of the algorithm.<\/jats:p>","DOI":"10.3390\/a15090312","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T21:25:18Z","timestamp":1661894718000},"page":"312","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Images Segmentation Based on Cutting the Graph into Communities"],"prefix":"10.3390","volume":"15","author":[{"given":"Sergey V.","family":"Belim","sequence":"first","affiliation":[{"name":"Radio Engineering Department, Omsk State Technical University, 644050 Omsk, Russia"}]},{"given":"Svetlana Yu.","family":"Belim","sequence":"additional","affiliation":[{"name":"Radio Engineering Department, Omsk State Technical University, 644050 Omsk, Russia"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,30]]},"reference":[{"key":"ref_1","first-page":"7536","article-title":"Review: Various Image Segmentation Techniques","volume":"5","author":"Matta","year":"2014","journal-title":"IJCSIT"},{"key":"ref_2","first-page":"1706","article-title":"Computer vision-based color image segmentation with improved kernel clustering","volume":"8","author":"Wang","year":"2015","journal-title":"Int. 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