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Russian Mathematical Surveys, 2004, Volume 59, Issue 2, Pages 319–328
DOI: https://doi.org/10.1070/RM2004v059n02ABEH000721
(Mi rm721)
 

This article is cited in 11 scientific papers (total in 11 papers)

Hausdorff distance and image processing

B. Kh. Sendov

Central Laboratory for Parallel Processing, Bulgarian Academy of Sciences
References:
Abstract: Mathematical methods for image processing make use of function spaces which are usually Banach spaces with integral $L_p$ norms. The corresponding mathematical models of the images are functions in these spaces. There are discussions here involving the value of $p$ for which the distance between two functions is most natural when they represent images, or the metric in which our eyes measure the distance between the images. In this paper we argue that the Hausdorff distance is more natural to measure the distance (difference) between images than any $L_p$ norm.
Received: 20.06.2003
Russian version:
Uspekhi Matematicheskikh Nauk, 2004, Volume 59, Issue 2(356), Pages 127–136
DOI: https://doi.org/10.4213/rm721
Bibliographic databases:
Document Type: Article
UDC: 517.518.222
MSC: Primary 68U10, 28D20; Secondary 54E35
Language: English
Original paper language: Russian
Citation: B. Kh. Sendov, “Hausdorff distance and image processing”, Uspekhi Mat. Nauk, 59:2(356) (2004), 127–136; Russian Math. Surveys, 59:2 (2004), 319–328
Citation in format AMSBIB
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\paper Hausdorff distance and image processing
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\transl
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Linking options:
  • https://www.mathnet.ru/eng/rm721
  • https://doi.org/10.1070/RM2004v059n02ABEH000721
  • https://www.mathnet.ru/eng/rm/v59/i2/p127
  • This publication is cited in the following 11 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Успехи математических наук Russian Mathematical Surveys
    Statistics & downloads:
    Abstract page:1112
    Russian version PDF:450
    English version PDF:52
    References:103
    First page:1
     
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