• DocumentCode
    3558587
  • Title

    Composition of image analysis processes through object-centered hierarchical planning

  • Author

    Gong, Leiguang ; Kulikowski, Casimir A.

  • Author_Institution
    Dept. of Comput. Sci., Rutgers Univ., New Brunswick, NJ, USA
  • Volume
    17
  • Issue
    10
  • fYear
    1995
  • fDate
    10/1/1995 12:00:00 AM
  • Firstpage
    997
  • Lastpage
    1009
  • Abstract
    This paper presents a new approach to the knowledge-based composition of processes for image interpretation and analysis. Its computer implementation in the VISIPLAN (Vision Planner) system provides a way of modeling the composition of image analysis processes within a unified, object-centered hierarchical planning framework. The approach has been tested and shown to be flexible in handling a reasonably broad class of multi-modality biomedical image analysis and interpretation problems. It provides a relatively general design or planning framework, within which problem specific image analysis and recognition processes can be generated more efficiently and effectively. In this way, generality is gained at the design and planning stages, even though the final implementation stage of interpretation processes is almost invariably problem- and domain-specific
  • Keywords
    image recognition; knowledge based systems; medical image processing; object recognition; planning (artificial intelligence); VISIPLAN; Vision Planner; domain-specific; image analysis; image interpretation; image recognition; knowledge based system; knowledge-based composition; multi-modality biomedical image analysis; object-centered hierarchical planning; problem-specific; Image analysis; Image edge detection; Image generation; Image processing; Image recognition; Image sequence analysis; Layout; Machine vision; Process planning; Strategic planning;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • Conference_Location
    10/1/1995 12:00:00 AM
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.464563
  • Filename
    464563