Composition of Image Analysis Processes Through Object-Centered Hierarchical Planning

Leiguang Gong, Casimir A. Kulikowski

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)997-1009
Number of pages13
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume17
Issue number10
DOIs
StatePublished - Oct 1995

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

Keywords

  • Image analysis
  • artificial intelligence
  • composition of image analysis processes
  • hierarchical planning
  • knowledge-based systems

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