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Publications (8 of 8) Show all publications
Asplund, T., Bengtsson Bernander, K. & Breznik, E. (2019). CNNs on Graphs: A New Pooling Approach and Similarities to Mathematical Morphology. In: : . Paper presented at Swedish Symposium on Deep Learning.
Open this publication in new window or tab >>CNNs on Graphs: A New Pooling Approach and Similarities to Mathematical Morphology
2019 (English)Conference paper, Poster (with or without abstract) (Other academic)
National Category
Computer and Information Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-398138 (URN)
Conference
Swedish Symposium on Deep Learning
Available from: 2019-12-02 Created: 2019-12-02 Last updated: 2019-12-02
Asplund, T., Serna, A., Marcotegui, B., Strand, R. & Luengo Hendriks, C. L. (2019). Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes. In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing: . Paper presented at International Symposium on Mathematical Morphology (ISMM 2019).
Open this publication in new window or tab >>Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
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2019 (English)In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, 2019Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

National Category
Signal Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-388524 (URN)10.1007/978-3-030-20867-7_29 (DOI)978-3-030-20866-0 (ISBN)978-3-030-20867-7 (ISBN)
Conference
International Symposium on Mathematical Morphology (ISMM 2019)
Funder
Swedish Research Council, 2014-5983
Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2019-10-17
Asplund, T. (2019). Precise Image-Based Measurements through Irregular Sampling. (Doctoral dissertation). Uppsala: Acta Universitatis Upsaliensis
Open this publication in new window or tab >>Precise Image-Based Measurements through Irregular Sampling
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Noggranna bildbaserade mätningar via irreguljär sampling
Abstract [en]

Mathematical morphology is a theory that is applicable broadly in signal processing, but in this thesis we focus mainly on image data. Fundamental concepts of morphology include the structuring element and the four operators: dilation, erosion, closing, and opening. One way of thinking about the role of the structuring element is as a probe, which traverses the signal (e.g. the image) systematically and inspects how well it "fits" in a certain sense that depends on the operator.

Although morphology is defined in the discrete as well as in the continuous domain, often only the discrete case is considered in practice. However, commonly digital images are a representation of continuous reality and thus it is of interest to maintain a correspondence between mathematical morphology operating in the discrete and in the continuous domain. Therefore, much of this thesis investigates how to better approximate continuous morphology in the discrete domain. We present a number of issues relating to this goal when applying morphology in the regular, discrete case, and show that allowing for irregularly sampled signals can improve this approximation, since moving to irregularly sampled signals frees us from constraints (namely those imposed by the sampling lattice) that harm the correspondence in the regular case. The thesis develops a framework for applying morphology in the irregular case, using a wide range of structuring elements, including non-flat structuring elements (or structuring functions) and adaptive morphology. This proposed framework is then shown to better approximate continuous morphology than its regular, discrete counterpart.

Additionally, the thesis contains work dealing with regularly sampled images using regular, discrete morphology and weighting to improve results. However, these cases can be interpreted as specific instances of irregularly sampled signals, thus naturally connecting them to the overarching theme of irregular sampling, precise measurements, and mathematical morphology.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 63
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1869
Keywords
image analysis, image processing, mathematical morphology, irregular sampling, adaptive morphology, missing samples, continuous morphology, path opening.
National Category
Signal Processing Other Computer and Information Science
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-395205 (URN)978-91-513-0783-1 (ISBN)
Public defence
2019-12-06, Room 2446, ITC, Lägerhyddsvägen 2, Uppsala, 13:00 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2014-5983
Available from: 2019-11-13 Created: 2019-10-17 Last updated: 2019-11-13
Asplund, T., Luengo Hendriks, C. L., Thurley, M. J. & Strand, R. (2017). Mathematical morphology on irregularly sampled data in one dimension. Mathematical Morphology - Theory and Applications, 2(1), 1-24
Open this publication in new window or tab >>Mathematical morphology on irregularly sampled data in one dimension
2017 (English)In: Mathematical Morphology - Theory and Applications, ISSN 2353-3390, Vol. 2, no 1, p. 1-24Article in journal (Refereed) Published
National Category
Computer Sciences
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-337288 (URN)10.1515/mathm-2017-0001 (DOI)
Funder
Swedish Research Council, 2014-5983
Available from: 2017-12-29 Created: 2017-12-21 Last updated: 2019-10-17Bibliographically approved
Asplund, T., Luengo Hendriks, C. L., Thurley, M. & Strand, R. (2017). Mathematical Morphology on Irregularly Sampled Signals. In: Computer Vision – ACCV 2016 Workshops. ACCV 2016: . Paper presented at 13th Asian Conference on Computer Vision (ACCV), Taipei, Taiwan, November 20-24, 2016 (pp. 506-520). Springer, 10117
Open this publication in new window or tab >>Mathematical Morphology on Irregularly Sampled Signals
2017 (English)In: Computer Vision – ACCV 2016 Workshops. ACCV 2016, Springer, 2017, Vol. 10117, p. 506-520Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a new operator that can be used to approximate continuous-domain mathematical morphology on irregularly sampled surfaces. We define a new way of approximating the continuous domain dilation by duplicating and shifting samples according to a flat continuous structuring element. We show that the proposed algorithm can better approximate continuous dilation, and that dilations may be sampled irregularly to achieve a smaller sampling without greatly compromising the accuracy of the result.

Place, publisher, year, edition, pages
Springer, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10117
National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-309921 (URN)10.1007/978-3-319-54427-4_37 (DOI)000426193700037 ()978-3-319-54427-4 (ISBN)978-3-319-54426-7 (ISBN)
Conference
13th Asian Conference on Computer Vision (ACCV), Taipei, Taiwan, November 20-24, 2016
Funder
Swedish Research Council, 2014-5983
Available from: 2016-12-08 Created: 2016-12-08 Last updated: 2019-10-17Bibliographically approved
Asplund, T., Luengo, C., Thurley, M. & Strand, R. (2016). A New Approach to Mathematical Morphology on One Dimensional Sampled Signals. In: IEEE Proceedings, International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016: . Paper presented at International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016.
Open this publication in new window or tab >>A New Approach to Mathematical Morphology on One Dimensional Sampled Signals
2016 (English)In: IEEE Proceedings, International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

We present a new approach to approximate continuous-domain mathematical morphology operators. The approach is applicable to irregularly sampled signals. We define a dilation under this new approach, where samples are duplicated and shifted according to the flat, continuous structuring element. We define the erosion by adjunction, and the opening and closing by composition. These new operators will significantly increase precision in image measurements. Experiments show that these operators indeed approximate continuous-domain operators better than the standard operators on sampled one-dimensional signals, and that they may be applied to signals using structuring elements smaller than the distance between samples. We also show that we can apply the operators to scan lines of a two-dimensional image to filter horizontal and vertical linear structures.

National Category
Computer Sciences Computational Mathematics
Identifiers
urn:nbn:se:uu:diva-309925 (URN)10.1109/ICPR.2016.7900244 (DOI)000406771303148 ()
Conference
International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016
Funder
Swedish Research Council, 2014-5983
Available from: 2016-12-08 Created: 2016-12-08 Last updated: 2018-03-16Bibliographically approved
Asplund, T., Luengo Hendriks, C. L., Thurley, M. J. & Strand, R. Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions.
Open this publication in new window or tab >>Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two Dimensions
(English)In: Article in journal (Refereed) Submitted
National Category
Signal Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-395204 (URN)
Funder
Swedish Research Council, 2014-5983
Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-10-25
Asplund, T., Luengo Hendriks, C. L., Thurley, M. J. & Strand, R. Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring Elements.
Open this publication in new window or tab >>Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring Elements
(English)In: Article in journal (Refereed) Submitted
National Category
Signal Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-395200 (URN)
Funder
Swedish Research Council, 2014-5983
Available from: 2019-10-15 Created: 2019-10-15 Last updated: 2019-10-25
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0612-558x

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