Local Polynomial Approximation for Unsupervised Segmentation of Endoscopic Images

  • Artur Klepaczko
  • Piotr Szczypiński
  • Piotr Daniel
  • Marek Pazurek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)


In this paper we present a novel technique for unsupervised texture segmentation of wireless capsule endoscopic images of the human gastrointestinal tract. Our approach integrates local polynomial approximation algorithm with the well-founded methods of color texture analysis and clustering (k-means) leading to a robust segmentation procedure which produces fine-grained segments well matched to the image contents.


Endoscopic Image Capsule Endoscopy Video Wireless Capsule Endoscopy Unsupervised Segmentation Local Polynomial Approximation 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Artur Klepaczko
    • 1
  • Piotr Szczypiński
    • 1
  • Piotr Daniel
    • 2
  • Marek Pazurek
    • 2
  1. 1.Institute of ElectronicsTechnical University of ŁódźWólczańska
  2. 2.Department of Digestive Tract DiseaseMedical University of ŁódźKopcińskiego

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