Biomedical Color Image Segmentation through Precise Seed Selection in Fuzzy Clustering

  • Byomkesh Mandal
  • Balaram Bhattacharyya
Part of the Communications in Computer and Information Science book series (CCIS, volume 311)


Biomedical color images play major role in medical diagnosis. Often a change of state is identified through minute variations in color at tiny parts. Fuzzy C-means (FCM) clustering is suitable for pixel classification to isolate those parts but its success is heavily dependent on the selection of seed clusters. This paper presents a simple but effective technique to generate seed clusters resembling the image features. The HSI color model is selected for near-zero correlation among components. The approach has been tested on several cell images having low contrast at adjacent parts. Results of segmentation show its effectiveness.


Color image segmentation blood cell images histogram pixel classification fuzzy C-means 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Byomkesh Mandal
    • 1
  • Balaram Bhattacharyya
    • 1
  1. 1.Department of Computer & System SciencesVisva-Bharati UniversitySantiniketanIndia

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