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Proceedings Paper

Multiscale analysis based on mathematical morphology
Author(s): Yi Lu; Robert C. Vogt
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Paper Abstract

In the field of computer vision, multiscale analysis has received much attention in the past decade. In particular, Gaussian scale space has been studied extensively and has proven to be effective in multiscale analysis. Recent research has shown that morphological openings or openings or closings with isotropic structuring elements such as disks define a scale space, where the radius of a disk r is the scale parameter which changes continuously from 0 to infinity. The behaviors of objects described by the morphological scale space provide strong knowledge for multiscale analysis. Based on the theory of morphological scale space, we address in this paper the two fundamental problems in multiscale analysis: (1) how to select proper scale parameters for various applications, and (2) how to integrate the information filtered at multiscales. We propose two algorithms, binary morphological multiscale analysis (BMMA) and gray-scale morphological multiscale analysis (GMMA), for extracting desired regions from binary and gray images.

Paper Details

Date Published: 1 July 1991
PDF: 12 pages
Proc. SPIE 1568, Image Algebra and Morphological Image Processing II, (1 July 1991); doi: 10.1117/12.49882
Show Author Affiliations
Yi Lu, Environmental Research Institute of Michigan (United States)
Robert C. Vogt, Environmental Research Institute of Michigan (United States)


Published in SPIE Proceedings Vol. 1568:
Image Algebra and Morphological Image Processing II
Paul D. Gader; Edward R. Dougherty, Editor(s)

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