DocumentCode :
576622
Title :
Automatic threshold selection for morphological attribute profiles
Author :
Mahmood, Z. ; Thoonen, G. ; Scheunders, P.
Author_Institution :
Dept. of Phys., Univ. of Antwerp, Antwerp, Belgium
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
4946
Lastpage :
4949
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.
Keywords :
geophysical image processing; geophysical techniques; image classification; automatic threshold selection; automatized procedure; classification experiment; clustering algorithm; image scaling effect; morphological attribute profiles; threshold informative values; unsupervised classification; Clustering algorithms; Educational institutions; Gray-scale; Hyperspectral imaging; Manuals; Vectors; Attribute profiles; classification; clustering; contextual information; threshold selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6352502
Filename :
6352502
Link To Document :
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