Paradigm for shape-based image analysis

Joseph M. Reinhardt, William E. Higgins

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Traditional image segmentation techniques typically divide an image into separate regions based on gray-scale characteristics. Most real-world image-segmentation problems, however, require some subsequent shape-based processing to yield acceptable results. Unfortunately, choosing an appropriate sequence of image-processing operators (a process) for this purpose can be a time-consuming, tedious procedure that requires considerable image-processing expertise. We describe a semiautomatic paradigm for selecting shape-based operations for an image-analysis process. Desired shape information for image regions is provided by the user in the form of easily specified cues. The cues are then automatically interpreted to select suitable image-processing operators and operator parameters; the operators can be morphological, topological, and image-manipulation functions. The paradigm, hence, enables easy prototyping of image-analysis processes for different problems. The user is not required to be an image-processing expert to apply this strategy - he or she need only be able to specify the desired shape properties of the regions in the image. We demonstrate our approach for both 2-D and 3-D image analysis problems.

Original languageEnglish (US)
Pages (from-to)570-581
Number of pages12
JournalOptical Engineering
Issue number2
StatePublished - Feb 1998

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • General Engineering


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