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An Approach to Adaptive Quadratic Structuring Functions Based on the Local Structure Tensor
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
2015 (English)In: Mathematical Morphology and Its Applications to Signal and Image Processing: 12th International Symposium, ISMM 2015, Reykjavik, Iceland, May 27-29, 2015. Proceedings / [ed] Jón Atli Benediktsson ; Jocelyn Chanussot ; Laurent Najman; Hughes Talbot, Encyclopedia of Global Archaeology/Springer Verlag, 2015, 729-740 p.Conference paper (Refereed)
Abstract [en]

Classical morphological image processing, where the same structuring element is used to process the whole image, has its limitations. Consequently, adaptive mathematical morphology is attracting more and more attention.So far, however, the use of non-flat adaptive structuring functions is very limited. This work presents a method for defining quadratic structuring functions from the well known local structure tensor, building on previous work for flat adaptive morphology. The result is a novel approach to adaptive mathematical morphology, suitable for enhancement and linking of directional features in images. Moreover, the presented strategy can be quite efficiently implemented and is easy to use as it relies on just two user-set parameters which are directly related to image measures.

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2015. 729-740 p.
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9082
Research subject
Signal Processing
URN: urn:nbn:se:ltu:diva-38299DOI: 10.1007/978-3-319-18720-4_61Local ID: ca568a98-e4eb-4f6d-bf47-3e6dec981973ISBN: 978-3-319-18719-8ISBN: 978-3-319-18720-4 (PDF)OAI: diva2:1011798
International Symposium on Mathematical Morphology : 27/05/2015 - 29/05/2015
Validerad; 2015; Nivå 1; 20150519 (andlan)Available from: 2016-10-03 Created: 2016-10-03Bibliographically approved

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