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Robust Estimation of Distance Between Sets of Points
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences.ORCID iD: 0000-0001-5765-2964
Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences.
2013 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, no 16, 2192-2198 p.Article in journal (Refereed) Published
Abstract [en]

This paper proposes a new methodology for computing Hausdorff distances between sets of points in a robust way. In a first step, robust nearest neighbor distance distributions between the two sets of points are obtained by considering reliability measures in the computations through a Monte Carlo scheme. In a second step, the computed distributions are operated using random variables algebra in order to obtain probability distributions of the average, minimum or maximum distances. In the last step, different statistics are computed from these distributions. A statistical test of significance, the nearest neighbor index, in addition to the newly proposed divergence and clustering indices are used to compare the computed measurements with respect to values obtained by chance. Results on synthetic and real data show that the proposed method is more robust than the standard Hausdorff distance. In addition, unlike previously proposed methods based on thresholding, it is appropriate for problems that can be modeled through point processes.

Place, publisher, year, edition, pages
Elsevier, 2013. Vol. 34, no 16, 2192-2198 p.
Keyword [en]
Spatial statistics; Distance estimation; Hausdorff distance; Nearest neighbor distance distribution
National Category
Cardiac and Cardiovascular Systems
Identifiers
URN: urn:nbn:se:liu:diva-97282DOI: 10.1016/j.patrec.2013.08.012ISI: 000333104500019OAI: oai:DiVA.org:liu-97282DiVA: diva2:645994
Funder
Swedish Heart Lung Foundation, 20100460
Available from: 2013-09-06 Created: 2013-09-06 Last updated: 2017-12-06Bibliographically approved

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Moreno, RodrigoKoppal, Sandeepde Muinck, Ebo

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Center for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Health SciencesDivision of Cardiovascular Medicine
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Pattern Recognition Letters
Cardiac and Cardiovascular Systems

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