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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 3/2011

01.08.2011 | Theoretical Advances

On searching for an optimal threshold for morphological image segmentation

verfasst von: Francisco A. Pujol, Mar Pujol, Ramón Rizo, Maria José Pujol

Erschienen in: Pattern Analysis and Applications | Ausgabe 3/2011

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Abstract

Segmentation of images represents the first step in many of the tasks that pattern recognition or computer vision has to deal with. Therefore, the main goal of our paper is to describe a new method for image segmentation, taking into account some Mathematical Morphology operations and an adaptively updated threshold, what we call Morphological Gradient Threshold, to obtain the optimal segmentation. The key factor in our work is the calculation of the distance between the segmented image and the ideal segmentation. Experimental results show that the optimal threshold is obtained when the Morphological Gradient Threshold is around the 70% of the maximum value of the gradient. This threshold could be computed, for any new image captured by the vision system, using a properly designed binary metrics.
Vorheriger Artikel Robust document binarization with OFF center-surround cells
Nächster Artikel A Center-Surround Histogram for content-based image retrieval

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Metadaten
Titel
On searching for an optimal threshold for morphological image segmentation
verfasst von
Francisco A. Pujol
Mar Pujol
Ramón Rizo
Maria José Pujol
Publikationsdatum
01.08.2011
Verlag
Springer-Verlag
Erschienen in
Pattern Analysis and Applications / Ausgabe 3/2011
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-011-0215-0

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