A new color image segmentation algorithm based on watershed transformation

Marat Kazanov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

A new color segmentation method is presented in this paper. The method is specified for color images that have both large and small objects, and objects with both step and ramp edges. Scanned pages of color magazines and newspapers are the examples of this kind of images. Watershed transformation algorithm is the basis of the proposed method. Our method incorporates the original multi-scale analysis that allows to segment edges of different slope. This analysis uses fine-to-coarse strategy and prevents the already detected sharp edges from smoothing while moving to coarser scales. In the same time the introduced algorithm allows to detect ramp edges successfully at coarse scales. For fine scales we propose a special gradient operator and a modification of watershed transformation for small objects segmentation.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages590-593
Number of pages4
DOIs
Publication statusPublished - 2004
Externally publishedYes
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: 23 Aug 200426 Aug 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2
ISSN (Print)1051-4651

Conference

ConferenceProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
Country/TerritoryUnited Kingdom
CityCambridge
Period23/08/0426/08/04

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