Share Email Print

Proceedings Paper

Model-based morphology
Author(s): Robert M. Haralick; Edward R. Dougherty; Philip L. Katz
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Filtering by morphological operations is particularly suited for removal of clutter and noise objects which have been introduced into noiseless binary images. The morphological filtering is designed to exploit differences in the spatial nature (shape, size, orientation) of the objects (connected components) in the ideal noiseless images as compared to the noise/clutter objects. Since the typical noise models (union, intersection set difference, etc.) for binary images are not additive, and the morphological processing is strongly nonlinear, optimal filtering results conventionally available for linear processing in the presence of additive noise are not directly applicable to morphological filtering of binary images. In this paper, a morphological filtering analog to the classic Wiener filter is described.

Paper Details

Date Published: 1 August 1991
PDF: 10 pages
Proc. SPIE 1472, Image Understanding and the Man-Machine Interface III, (1 August 1991); doi: 10.1117/12.46476
Show Author Affiliations
Robert M. Haralick, Univ. of Washington (United States)
Edward R. Dougherty, Rochester Institute of Technology (United States)
Philip L. Katz, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 1472:
Image Understanding and the Man-Machine Interface III
Eamon B. Barrett; James J. Pearson, Editor(s)

© SPIE. Terms of Use
Back to Top