Local mean multiphase segmentation with HMMF models

Jacob Daniel Kirstejn Hansen; Francois Bernard Lauze

doi:10.1007/978-3-319-58771-4_32

Local mean multiphase segmentation with HMMF models

Jacob Daniel Kirstejn Hansen^*, Francois Bernard Lauze

^*Corresponding author for this work

Department of Computer Science

1 Citation (Scopus)

Abstract

This paper presents two similar multiphase segmentation methods for recovery of segments in complex weakly structured images, with local and global bias fields, because they can occur in some X-ray CT imaging modalities. Derived from the Mumford-Shah functional, the proposed methods assume a fixed number of classes. They use local image average as discriminative features. Region labels are modelled by Hidden Markov Measure Field Models. The resulting problems are solved by straightforward alternate minimisation methods, particularly simple in the case of quadratic regularisation of the labels. We demonstrate the proposed methods’ capabilities on synthetic data using classical segmentation criteria as well as criteria specific to geoscience. We also present a few examples using real data.

Original language	English
Title of host publication	Scale Space and Variational Methods in Computer Vision : 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings
Editors	François Lauze, Yiqui Dong, Anders Bjorholm Dahl
Number of pages	12
Publisher	Springer
Publication date	2017
Pages	396-407
ISBN (Print)	978-3-319-58770-7
ISBN (Electronic)	978-3-319-58771-4
DOIs	https://doi.org/10.1007/978-3-319-58771-4_32
Publication status	Published - 2017
Event	6th International Conference on Scale Space and Variational Methods in Computer Vision - Kolding, Denmark Duration: 4 Jun 2017 → 8 Jun 2017 Conference number: 6

Conference

Conference	6th International Conference on Scale Space and Variational Methods in Computer Vision
Number	6
Country/Territory	Denmark
City	Kolding
Period	04/06/2017 → 08/06/2017

Series	Lecture notes in computer science
Volume	10302
ISSN	0302-9743

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10.1007/978-3-319-58771-4_32

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Hansen, J. D. K., & Lauze, F. B. (2017). Local mean multiphase segmentation with HMMF models. In F. Lauze, Y. Dong, & A. B. Dahl (Eds.), Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings (pp. 396-407). Springer. Lecture notes in computer science Vol. 10302 https://doi.org/10.1007/978-3-319-58771-4_32

Local mean multiphase segmentation with HMMF models. / Hansen, Jacob Daniel Kirstejn; Lauze, Francois Bernard.

Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings. ed. / François Lauze; Yiqui Dong; Anders Bjorholm Dahl. Springer, 2017. p. 396-407 (Lecture notes in computer science, Vol. 10302).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Hansen, JDK & Lauze, FB 2017, Local mean multiphase segmentation with HMMF models. in F Lauze, Y Dong & AB Dahl (eds), Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings. Springer, Lecture notes in computer science, vol. 10302, pp. 396-407, 6th International Conference on Scale Space and Variational Methods in Computer Vision, Kolding, Denmark, 04/06/2017. https://doi.org/10.1007/978-3-319-58771-4_32

Hansen, Jacob Daniel Kirstejn ; Lauze, Francois Bernard. / Local mean multiphase segmentation with HMMF models. Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings. editor / François Lauze ; Yiqui Dong ; Anders Bjorholm Dahl. Springer, 2017. pp. 396-407 (Lecture notes in computer science, Vol. 10302).

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Local mean multiphase segmentation with HMMF models

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