International Conference Image Analysis and Recognition

ICIAR 2010: Image Analysis and Recognition pp 131-140

Classification of Endoscopic Images Using Delaunay Triangulation-Based Edge Features

  • M. Häfner
  • A. Gangl
  • M. Liedlgruber
  • Andreas Uhl
  • A. Vécsei
  • F. Wrba
Conference paper

DOI: 10.1007/978-3-642-13775-4_14

Volume 6112 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Häfner M., Gangl A., Liedlgruber M., Uhl A., Vécsei A., Wrba F. (2010) Classification of Endoscopic Images Using Delaunay Triangulation-Based Edge Features. In: Campilho A., Kamel M. (eds) Image Analysis and Recognition. ICIAR 2010. Lecture Notes in Computer Science, vol 6112. Springer, Berlin, Heidelberg

Abstract

In this work we present a method for an automated classification of endoscopic images according to the pit pattern classification scheme. Images taken during colonoscopy are transformed using an extended and rotation invariant version of the Local Binary Patterns operator (LBP). The result of the transforms is then used to extract polygons from the images. Based on these polygons we compute the regularity of the polygon positions by using the Delaunay triangulation and constructing histograms from the edge lengths of the Delaunay triangles. Using these histograms, the classification is carried out by employing the k-nearest-neighbors (k-NN) classifier in conjunction with the histogram intersection distance metric.

While, compared to previously published results, the performance of the proposed approach is lower, the results achieved are yet promising and show that a pit pattern classification is feasible by using the proposed system.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • M. Häfner
    • 1
  • A. Gangl
    • 2
  • M. Liedlgruber
    • 3
  • Andreas Uhl
    • 3
  • A. Vécsei
    • 4
  • F. Wrba
    • 5
  1. 1.Department for Internal MedicineSt. Elisabeth HospitalVienna
  2. 2.Department of Gastroenterology and HepatologyMedical University of ViennaAustria
  3. 3.Department of Computer SciencesSalzburg UniversityAustria
  4. 4.St. Anna Children’s HospitalViennaAustria
  5. 5.Department of Clinical PathologyMedical University of ViennaAustria