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

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

Schenker, P.I. / Wong, K.M. / Cande, E.G.

This paper presents results of experimental studies in image understandig. 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).

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Titel :

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

Weitere Titelangaben:

Schnelle adaptive Algorithmen bei der Szenenanalyse mit niedrigem Level: polare exponentielle Gitterdarstellung fuer die skala- und rotationsinvariante Zielobjektbestimmung bei hoher Geschwindigkeit

Beteiligte:

Schenker, P.I. (Autor:in) / Wong, K.M. (Autor:in) / Cande, E.G. (Autor:in)

Erschienen in:

Proc. Techniques and applications of image understanding ; 47-57

Erscheinungsdatum :

1981

Format / Umfang :

11 Seiten, 13 Bilder, 18 Quellen

Medientyp :

Aufsatz (Konferenz)

Format :

Sprache :