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Image segmentation, evaluation, and applications

McGuinness, Kevin (2010) Image segmentation, evaluation, and applications. PhD thesis, Dublin City University.

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This thesis aims to advance research in image segmentation by developing robust techniques for evaluating image segmentation algorithms. The key contributions of this work are as follows. First, we investigate the characteristics of existing measures for supervised evaluation of automatic image segmentation algorithms. We show which of these measures is most effective at distinguishing perceptually accurate image segmentation from inaccurate segmentation. We then apply these measures to evaluating four state-of-the-art automatic image segmentation algorithms, and establish which best emulates human perceptual grouping. Second, we develop a complete framework for evaluating interactive segmentation algorithms by means of user experiments. Our system comprises evaluation measures, ground truth data, and implementation software. We validate our proposed measures by showing their correlation with perceived accuracy. We then use our framework to evaluate four popular interactive segmentation algorithms, and demonstrate their performance. Finally, acknowledging that user experiments are sometimes prohibitive in practice, we propose a method of evaluating interactive segmentation by algorithmically simulating the user interactions. We explore four strategies for this simulation, and demonstrate that the best of these produces results very similar to those from the user experiments.

Item Type:Thesis (PhD)
Date of Award:March 2010
Supervisor(s):O'Connor, Noel E.
Uncontrolled Keywords:interaction; segmentation; evaluation;
Subjects:Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
Funders:Science Foundation Ireland, EU FP6 K-Space Network of Excellence
ID Code:14998
Deposited On:31 Mar 2010 15:03 by Noel Edward O'Connor. Last Modified 09 Feb 2017 13:42

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