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Image Segmentation with the Aid of the p-Adic Metrics
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för matematik (MA).ORCID-id: 0000-0002-9857-0938
Institute of System Analysis of Russian Academy of Science, Russia.
2017 (engelsk)Inngår i: New Trends and Advanced Methods in Interdisciplinary Mathematical Sciences / [ed] Bourama Toni, Springer, 2017, s. 143-154Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

We present the results of numerical simulation for image segmentation based on the chain distance clustering algorithm. The key issue is the use of the p-adic metric, where p > 1 is a prime number, at the scale of levels of brightness (pixel wise). In previous studies the p-adic metric was used mainly in combination with spectral methods. In this paper this metric is explored directly, without preparatory transformations of images. The main distinguishing feature of the p-adic metric is that it reflects the hierarchic structure of information presented in an image. Different classes of images match with in general different prime p (although the choice p = 2 works on average). Therefore the presented image segmentation procedure has to be combined with a kind of learning to select the prime p corresponding to the class of images under consideration.

sted, utgiver, år, opplag, sider
Springer, 2017. s. 143-154
Serie
STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health, ISSN 2520-193X
Emneord [en]
Image segmentation; p-adic metric; Clustering; Clustering algorithm
HSV kategori
Forskningsprogram
Matematik, Matematik
Identifikatorer
URN: urn:nbn:se:lnu:diva-72076DOI: 10.1007/978-3-319-55612-3ISBN: 978-3-319-55611-6 (tryckt)ISBN: 978-3-319-55612-3 (digital)OAI: oai:DiVA.org:lnu-72076DiVA, id: diva2:1194667
Tilgjengelig fra: 2018-04-03 Laget: 2018-04-03 Sist oppdatert: 2018-04-05bibliografisk kontrollert

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