A self-organizing tree map approach for image segmentation

Hao Song Kong, Ling Guan, Sun Yuan Kung

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

3 Scopus citations

Abstract

In this paper, an efficient image segmentation approach by using a self-organizing tree map (SOTM) is proposed. The SOTM neural network is first employed for the coarse segmentation to obtain the global clustering information of the image. Then, a pixel-based classification scheme that utilizes the local features is used to refine the segmentation. The proposed approach considers both global distributions of the image and local pixel characteristics; experimental results clearly show that images can be segmented into meaningful objects or parts. One of the advantages of the proposed approach is that the features used for the coarse segmentation can still be used to help make the final decision of the segmentation.

Original languageEnglish (US)
Title of host publicationICSP 2002 - 2002 6th International Conference on Signal Processing, Proceedings
EditorsBaozong Yuan, Xiaofang Tang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages588-591
Number of pages4
ISBN (Electronic)0780374886
DOIs
StatePublished - Jan 1 2002
Event6th International Conference on Signal Processing, ICSP 2002 - Beijing, China
Duration: Aug 26 2002Aug 30 2002

Publication series

NameInternational Conference on Signal Processing Proceedings, ICSP
Volume1

Other

Other6th International Conference on Signal Processing, ICSP 2002
CountryChina
CityBeijing
Period8/26/028/30/02

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Science Applications

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    Kong, H. S., Guan, L., & Kung, S. Y. (2002). A self-organizing tree map approach for image segmentation. In B. Yuan, & X. Tang (Eds.), ICSP 2002 - 2002 6th International Conference on Signal Processing, Proceedings (pp. 588-591). [1181124] (International Conference on Signal Processing Proceedings, ICSP; Vol. 1). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOSP.2002.1181124