Morphology-based symbolic image modeling, multi-scale nonlinearsmoothing, and pattern spectrum
Maragos, P.
Div. of Appl. Sci., Harvard Univ., Cambridge, MA ;
This paper appears in: Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Publication Date: 5-9 Jun 1988
On page(s): 766-773
Meeting Date: 06/05/1988 - 06/09/1988
Location: Ann Arbor, MI, USA
ISBN: 0-8186-0862-5
References Cited: 22
INSPEC Accession Number: 3258582
Digital Object Identifier: 10.1109/CVPR.1988.196321
Current Version Published: 2002-08-06
Abstract
The author develops a symbolic modeling of images based on their
shape-size information. First, multiscale multishape structural
distributions in the image are modeled by morphological openings, and a
related shape-size descriptor, the pattern spectrum, is developed that
can detect critical scales. Then the image is modeled as a nonlinear
superposition of simpler parts (the symbols), which are translated and
scaled shape patterns drawn from a finite collection. The model
parameters are found by using the information from openings and pattern
spectrum, and by local searches at points of generalized skeletons. The
results appear promising for multiscale image analysis and shape
recognition
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