Evaluating minimum spanning tree based segmentation algorithms

Authors:
Yll Haxhimusa;Adrian Ion;Walter G. Kropatsch;Thomas Illetschko
Affiliations:
Pattern Recognition and Image Processing Group 183/2, Institute for Computer Aided Automation, Vienna University of Technology, Austria;Pattern Recognition and Image Processing Group 183/2, Institute for Computer Aided Automation, Vienna University of Technology, Austria;Pattern Recognition and Image Processing Group 183/2, Institute for Computer Aided Automation, Vienna University of Technology, Austria;Pattern Recognition and Image Processing Group 183/2, Institute for Computer Aided Automation, Vienna University of Technology, Austria
Venue:
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Year:
2005

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Abstract

Two segmentation methods based on the minimum spanning tree principle are evaluated with respect to each other. The hierarchical minimum spanning tree method is also evaluated with respect to human segmentations. Discrepancy measure is used as best suited to compute the segmentation error between the methods. The evaluation is done using gray value images. It is shown that the segmentation results of these methods have a considerable difference.