Color Image Segmentation Through Self-Organizing Map.

Date of Submission

December 2004

Date of Award

Winter 12-12-2005

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science

Department

Machine Intelligence Unit (MIU-Kolkata)

Supervisor

Biswas, Sambhunath|Bandophadyay, Sanghamitra

Abstract (Summary of the Work)

Capability of Kohonen's Self Organizing Map (SOM) in chustering is well established. We have re-examined the capability of SOM in clustering for color image segmentation. Two different methods have been proposed. One method uses non-partitioned input data, and zhe other method uses partitioned input dataset. Their effectiveness is tested on color and MRI brain images with and without noise. Segmentation results have been viewed through some measures.

Comments

ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843174

Control Number

ISI-DISS-2004-119

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

http://dspace.isical.ac.in:8080/jspui/handle/10263/6290

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