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Scale and Edge Detection with Topological Derivatives

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Dong, Guozhi ; Grasmair, Markus ; Kang, Sung Ha ; Scherzer, Otmar:
Scale and Edge Detection with Topological Derivatives.
In: Kuijper, Arjan ; Bredies, Kristian ; Pock, Thomas ; Bischof, Horst (Hrsg.): Scale Space and Variational Methods in Computer Vision : 4th international conference, SSVM 2013, Schloss Seggau, Leibnitz, Austria, June 2 - 6, 2013 ; proceedings. - Berlin : Springer, 2013. - S. 404-415. - (Lecture Notes in Computer Science ; 7893)
ISBN 978-3-642-38266-6 ; 978-3-642-38267-3

Kurzfassung/Abstract

A typical task of image segmentation is to partition a given image into regions of homogeneous property. In this paper we focus on the problem of further detecting scales of discontinuities of the image. The approach uses a recently developed iterative numerical algorithm for minimizing the Mumford-Shah functional which is based on topological derivatives. For the scale selection we use a squared norm of the gradient at edge points. During the iteration progress, the square norm, as a function varied with iteration numbers, provides information about different scales of the discontinuity sets. For realistic image data, the graph of the norm function is regularized by using total variation minimization to provide stable separation. We present the details of the algorithm and document various numerical experiments.

Weitere Angaben

Publikationsform:Aufsatz in einem Buch
Schlagwörter:Mumford-Shah Functional, Topological Derivatives, Scale Selection, Total Variational Filtering.
Institutionen der Universität:Mathematisch-Geographische Fakultät > Mathematik > Lehrstuhl für Mathematik - Wissenschaftliches Rechnen
Begutachteter Aufsatz:Ja
Titel an der KU entstanden:Ja
KU.edoc-ID:13133
Eingestellt am: 20. Jun 2013 10:26
Letzte Änderung: 26. Jun 2013 11:58
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/13133/
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