Fast adaptive algorithms for low-level scene analysis: Applications of polar exponential grid (PEG) representation to high-speed, scale-and-rotation invariant target segmentation

P. S. Schenker, K. M. Wong, E. G. Cande

    Research output: Contribution to journalArticle

    Abstract

    This paper presents results of experimental studies in image understanding. Two experiments are discussed, one on image correlation and another on target boundary estimation. The experiments are demonstrative of polar exponential grid (PEG) representation, an approach to sensory data coding which the authors believe will facilitate problems in 3-D machine perception. Our discussion of the image correlation experiment is largely an exposition of the PEG-representation concept and approaches to its computer implementation. Our presentation of the boundary finding experiment introduces a new robust stochastic, parallel computation segmentation algorithm, the PEG-Parallel Hierarchical Ripple Filter (PEG-PHRF).

    Original languageEnglish (US)
    Pages (from-to)47-57
    Number of pages11
    JournalProceedings of SPIE - The International Society for Optical Engineering
    Volume281
    DOIs
    StatePublished - Nov 12 1981

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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