Home Lista publikacji Informacja o publikacji Acivs 2010 Automated Segmentation of Endoscopic Images Based on Local Shape-Adaptive Filtering and Color Descriptors

Acivs 2010 Automated Segmentation of Endoscopic Images Based on Local Shape-Adaptive Filtering and Color Descriptors

Email Drukuj PDF

Artur Klepaczko and Piotr Szczypinski Automated Segmentation of Endoscopic Images Based on Local Shape-Adaptive Filtering and Color Descriptors

This paper presents a novel technique for automatic segmentation of wireless capsule endoscopic images. The main contribution resides in the integration of three computational blocks: 1) local polynomial approximation algorithm which finds locally-adapted neighborhood of each pixel; 2) color texture analysis which describes each pixel by a vector of numerical attributes that reflect this pixel local neighborhood characteristcs; and 3) cluster analysis (k-means) for grouping pixels into homgeneous regions based on their color information. The proposed approach leads to a robust segmentation procedure which produces fine segments well matched to the image contents.

 

Acivs 2010 , Dec. 13-16, 2010, Macquarie University, Sydney, Australia