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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
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
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
Linking options:
https://www.mathnet.ru/eng/rm721https://doi.org/10.1070/RM2004v059n02ABEH000721 https://www.mathnet.ru/eng/rm/v59/i2/p127
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Abstract page: | 1112 | Russian version PDF: | 450 | English version PDF: | 52 | References: | 103 | First page: | 1 |
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