Color image simplification by morphological hierarchical segmentation and color clustering

Franklin Cesar Flores, Adrian N. Evans

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Morphological hierarchical segmentation of color images may be achieved in a straightforward way by measuring the persistence of regional minima from color gradients and using these measurements as a criterion to select markers for the watershed from markers framework. Since color has an implicit role in the selection of markers, the segmentation process may provide a bad combination of distinct colored regions, and this may lead to a distorted image simplification. This paper proposes a new method to color image simplification in which the importance of color is raised because color information is added to the marker selection process. Such method provides finer control over the final number of regions (n) and the resulting number of colors (c). A color clustering method splits the regional minima in to c minima sets, each of which has a representative color. The most prominent regional minima from each minima set are selected to form the markers for the segmentation framework. In the final segmentation, the color assigned to a region is given by the representative color bound to the marker that points to the region. It leads to an image whose segmented regions are quantized to fewer distinct colors.

Original languageEnglish
Title of host publicationProceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016
PublisherIEEE
Number of pages6
ISBN (Electronic)9781509033393
ISBN (Print)978-1-5090-3340-9
DOIs
Publication statusPublished - 27 Jan 2017
Event35th International Conference of the Chilean Computer Science Society, SCCC 2016 - Valparaiso, Chile
Duration: 10 Oct 201614 Oct 2016

Conference

Conference35th International Conference of the Chilean Computer Science Society, SCCC 2016
CountryChile
CityValparaiso
Period10/10/1614/10/16

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Color
Watersheds

Keywords

  • color clustering
  • color image segmentation
  • morphological hierarchical segmentation

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

Cite this

Flores, F. C., & Evans, A. N. (2017). Color image simplification by morphological hierarchical segmentation and color clustering. In Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016 [7836049] IEEE. https://doi.org/10.1109/SCCC.2016.7836049

Color image simplification by morphological hierarchical segmentation and color clustering. / Flores, Franklin Cesar; Evans, Adrian N.

Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016. IEEE, 2017. 7836049.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Flores, FC & Evans, AN 2017, Color image simplification by morphological hierarchical segmentation and color clustering. in Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016., 7836049, IEEE, 35th International Conference of the Chilean Computer Science Society, SCCC 2016, Valparaiso, Chile, 10/10/16. https://doi.org/10.1109/SCCC.2016.7836049
Flores FC, Evans AN. Color image simplification by morphological hierarchical segmentation and color clustering. In Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016. IEEE. 2017. 7836049 https://doi.org/10.1109/SCCC.2016.7836049
Flores, Franklin Cesar ; Evans, Adrian N. / Color image simplification by morphological hierarchical segmentation and color clustering. Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016. IEEE, 2017.
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