Color image segmentation based on blocks clustering and region growing

Haifeng Sima, Lixiong Liu*, Ping Guo

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

In order to overcome the discontinuity in clustering segmentation, a novel color image segmentation algorithm is proposed, which is based on seeds clustering and can locate the seeds of regions quickly. Firstly, the image is divided into a series of non-overlapping blocks with the size of n(n pixels in HSI color space. For each block, the centroid pixel of salient homogeneous region is selected as a feature point of the block. Secondly, based on the principles of color similarity centroids are clustered to obtain the clustered centroids as seeds for region growing. Finally, invalid and noisy regions are merged to get the complete segmentation results. Comparing with other segmentation algorithms, the experimental results demonstrate that the proposed method can accurately segment regions and objects, it outperforms other methods in terms of human visual perception.

Original languageEnglish
Title of host publicationNeural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages459-466
Number of pages8
EditionPART 3
DOIs
Publication statusPublished - 2011
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China
Duration: 13 Nov 201117 Nov 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7064 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Neural Information Processing, ICONIP 2011
Country/TerritoryChina
CityShanghai
Period13/11/1117/11/11

Keywords

  • color image
  • image segmentation
  • region growing
  • region merging
  • seeds clustering

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