Color image segmentation by means of a similarity function

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8 Scopus citations

Abstract

An interactive, semiautomatic image segmentation method is presented which, unlike most of the existing methods in the published literature, processes the color information of each pixel as a unit, thus avoiding color information scattering. The process has two steps: 1) The manual selection of few sample pixels of the color to be segmented, 2) The automatic generation of the so called Color Similarity Image (CSI), which is a gray level image with all the tonalities of the selected color. The color information of every pixel is integrated by a similarity function for direct color comparisons. The color integrating technique is direct, simple, and computationally inexpensive. It is shown that the improvement in quality of our proposed segmentation technique and its quick result is significant with respect to other solutions found in the literature.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010, Proceedings
Pages319-328
Number of pages10
DOIs
StatePublished - 2010
Event15th Iberoamerican Congress on Pattern Recognition, CIARP 2010 - Sao Paulo, Brazil
Duration: 8 Nov 201011 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6419 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Iberoamerican Congress on Pattern Recognition, CIARP 2010
Country/TerritoryBrazil
CitySao Paulo
Period8/11/1011/11/10

Keywords

  • Adaptive color similarity function
  • Color image segmentation
  • HSI parameter distances
  • Morphology in color images

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