Local polynomial approximation for unsupervised segmentation of endoscopic images

Authors:
Artur Klepaczko;Piotr Szczypiński;Piotr Daniel;Marek Pazurek
Affiliations:
Technical University of Łódź, Institute of Electronics, Łódź;Technical University of Łódź, Institute of Electronics, Łódź;Medical University of Łódź, Department of Digestive Tract Disease, Łódź;Medical University of Łódź, Department of Digestive Tract Disease, Łódź
Venue:
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part II
Year:
2010

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Abstract

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.