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Shape-Guided Interactive Image Segmentation

  • Author / Creator
    Wang, Hui
  • This dissertation contributes to developing shape-guided algorithms for interactive image segmentation. Prior knowledge which describes what is expected in an image is the key to success for many challenging applications. This research takes advantage of prior knowledge in terms of shape priors, which is one of the most common object features, and user interaction, which is a part of many segmentation procedures to correct or bootstrap the method. In this research, shape-guided algorithms are developed for different types of interactive segmentation: initial segmentation, dealing with certain types of under-segmentation and over-segmentation mistakes, and final object boundary refinement. First, the adaptive shape prior method is developed in the graph cut framework to incorporate shape priors adaptively. After obtaining the initial segmentation, to deal with under-segmentation due to object fusion, the clump splitting method is proposed to take the advantage of shape information on the bottleneck position of the clumps. For over-segmentation which requires merging, the interactive merging method is implemented. Subsequently, to refine the incorrectly segmented object boundaries, the shape PCA method is developed to utilize statistical shape information when intensity information is inadequate. Shape information is embedded as the key in each of the proposed algorithms throughout the whole segmentation process. To integrate these proposed algorithms together, a comprehensive interactive segmentation system is developed which embeds five decisive tools: addition, deletion, splitting, merging and boundary refinement. By combining these tools, a state-of-the-art shape-guided interactive segmentation system can be constructed which is capable of extracting high quality foreground objects from images effectively and efficiently with minimal amount of user input.

  • Subjects / Keywords
  • Graduation date
    2012-11
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3KW37
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Computing Science
  • Supervisor / co-supervisor and their department(s)
    • Zhang, Hong (Computing Science)
  • Examining committee members and their departments
    • Mandal, Mrinal (Electrical and Computer Engineering)
    • Acton, Scott (School of Engineering and Applied Science, University of Virginia)
    • Jagersand, Martin (Computing Science)
    • Ray, Nilanjan (Computing Science)