The performance of two image segmentation methods are compared according to robustness of the segmentation to image distortion. This criterion is crucial for temporal analysis of screening mammograms where natural changes in the breast plus inherent deformation of soft tissue during image acquisition result in severe image registration problems. A method based on minimum spanning trees (MST) is found to be more robust to the distortions studied than a method based on adaptive pyramids (AP). Although segmentation leads to great differences in segmentation in distorted images for many components of low saliency, salient components (those of primary interest) are found to be segmented consistently regardless of distortion.
|Title of host publication
|Subtitle of host publication
|Digital Image Computing Techniques and Applications 9th Biennial Conference of the Australian Pattern Recognition Society
|Place of Publication
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|0-7695-3067-2 , 978-0-7695-3067-3
|Published - 3 Dec 2007
|9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA) - Adelaide, Australia
Duration: 3 Dec 2007 → 5 Dec 2007
Conference number: 9th
|9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA)
|3/12/07 → 5/12/07