Segmentation of color images using mean curvature flow and parametric curves

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F21%3A00341283" target="_blank" >RIV/68407700:21240/21:00341283 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21340/21:00341283
Result on the web
<a href="https://doi.org/10.3934/dcdss.2020389" target="_blank" >https://doi.org/10.3934/dcdss.2020389</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3934/dcdss.2020389" target="_blank" >10.3934/dcdss.2020389</a>

Result language
angličtina
Original language name
Segmentation of color images using mean curvature flow and parametric curves
Original language description
Automatic detection of objects in photos and images is beneficial in various scientific and industrial fields. This contribution suggests an algorithm for segmentation of color images by the means of the parametric mean curvature flow equation and CIE94 color distance function. The parametric approach is enriched by the enhanced algorithm for topological changes where the intersection of curves is computed instead of unreliable curve distance. The result is a set of parametric curves enclosing the object. The algorithm is presented on a test image and also on real photos.
Czech name
—
Czech description
—

Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10102 - Applied mathematics

Project
<a href="/en/project/NV15-27178A" target="_blank" >NV15-27178A: Quantitative mapping of the myocardium and flow dynamics using MRI in patients with non-ischemic cardiac disease - methodology improvement</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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