Publication
Title
Automatic threshold selection for morphological attribute profiles
Author
Abstract
In this article, an automatized procedure for selecting informative values of the thresholds, essential for the construction of morphological attribute profiles, is proposed. To this end, connected component analysis is performed on a preliminary supervised or unsupervised classification result that does not involve contextual information. Subsequently, after extracting the relevant attributes from each of the connected components, the threshold values are found by grouping the attribute vectors using a clustering algorithm. In our experiments, we demonstrate the effect of image scaling on the selected thresholds. In addition, we show the advantage of using our automatic threshold selection approach with respect to manual selection, by both monitoring redundancy and performing a classification experiment.
Language
English
Source (book)
IEEE IGARSS 2012, International Geoscience and Remote Sensing Symposium , Munich, 22-27 July 2012
Publication
S.l. : 2012
ISBN
978-1-4673-1158-8
Volume/pages
p. 4946-4949
ISI
000313189404242
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 28.11.2012
Last edited 15.08.2017
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