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Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.ORCID-id: 0000-0002-0612-558x
Terra3D.
MINES ParisTech, PSL Research University, CMM - Centre for Mathematical Morphology.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.ORCID-id: 0000-0001-7764-1787
Vise andre og tillknytning
2019 (engelsk)Inngår i: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, 2019Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2019.
HSV kategori
Forskningsprogram
Datoriserad bildbehandling
Identifikatorer
URN: urn:nbn:se:uu:diva-388524DOI: 10.1007/978-3-030-20867-7_29ISBN: 978-3-030-20866-0 (tryckt)ISBN: 978-3-030-20867-7 (digital)OAI: oai:DiVA.org:uu-388524DiVA, id: diva2:1333651
Konferanse
International Symposium on Mathematical Morphology (ISMM 2019)
Forskningsfinansiär
Swedish Research Council, 2014-5983Tilgjengelig fra: 2019-07-01 Laget: 2019-07-01 Sist oppdatert: 2019-10-17
Inngår i avhandling
1. Precise Image-Based Measurements through Irregular Sampling
Åpne denne publikasjonen i ny fane eller vindu >>Precise Image-Based Measurements through Irregular Sampling
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Alternativ tittel[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.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2019. s. 63
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1869
Emneord
image analysis, image processing, mathematical morphology, irregular sampling, adaptive morphology, missing samples, continuous morphology, path opening.
HSV kategori
Forskningsprogram
Datoriserad bildbehandling
Identifikatorer
urn:nbn:se:uu:diva-395205 (URN)978-91-513-0783-1 (ISBN)
Disputas
2019-12-06, Room 2446, ITC, Lägerhyddsvägen 2, Uppsala, 13:00 (engelsk)
Opponent
Veileder
Forskningsfinansiär
Swedish Research Council, 2014-5983
Tilgjengelig fra: 2019-11-13 Laget: 2019-10-17 Sist oppdatert: 2019-11-13

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