An Efficient Class of Alternating Sequential Filters in Morphology

Document Type

Article

Publication Date

1-1-1997

Abstract

In this note, an efficient class of alternating sequential filters (ASFs) in mathematical morphology is presented to reduce the computational complexity in the conventional ASFs about a half. The performance boundary curves of the new filters are provided. Experimental results from applying these new ASFs to texture classification and image filtering (grayscale and binary) show that comparable performance can be achieved while much of the computational complexity is reduced. © 1997 Academic Press.

Identifier

0031099993 (Scopus)

Publication Title

Graphical Models and Image Processing

External Full Text Location

https://doi.org/10.1006/gmip.1996.0416

ISSN

10773169

First Page

109

Last Page

116

Issue

2

Volume

59

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