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Adaptive morphology using tensor-based elliptical structuring elements
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-6186-7116
2013 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, no 12, 1416-1422 p.Article in journal (Refereed) Published
Abstract [en]

Mathematical Morphology is a common strategy for non-linear filtering of image data. In its traditional form the filters used, known as structuring elements, have constant shape once set. Such rigid structuring elements are excellent for detecting patterns of a specific shape, but risk destroying valuable information in the data as they do not adapt in any way to its structure.We present a novel method for adaptive morphological filtering where the local structure tensor, a well-known method for estimation of structure within image data, is used to construct adaptive elliptical structuring elements which vary from pixel to pixel depending on the local image structure. More specifically, their shape varies from lines in regions of strong single-directional characteristics to disks at locations where the data has no prevalent direction.

Place, publisher, year, edition, pages
2013. Vol. 34, no 12, 1416-1422 p.
Keyword [en]
mathematical morphology, local structure tensor, adaptive morphology, Information technology - Signal processing
Keyword [sv]
Informationsteknik - Signalbehandling
National Category
Signal Processing
Research subject
Signal Processing
Identifiers
URN: urn:nbn:se:ltu:diva-5628DOI: 10.1016/j.patrec.2013.05.003Local ID: 3c8db92f-77e0-478c-8ba6-a397b7a35fa6OAI: oai:DiVA.org:ltu-5628DiVA: diva2:978502
Note
Validerad; 2013; 20121023 (andlan)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Landström, AndersThurley, Matthew

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