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Abstract: We derive the decomposition of the anisotropic Gaussian in a one dimensional Gauss filter in the x-direction followed by a one dimensional lter in a non-orthogonal direction '. So also the anisotropic Gaussian can be decomposed by dimension. This appears to be extremely efficient from a computing perspective. An implementation scheme for normal convolution and for recursive filtering is proposed. Also directed derivative filters are demonstrated. (Update)
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BibTeX entry: (Update)
J. Canny, "A computational approach to edge detection, " IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, pp. 679--698, 1986. 18 Weber and Malik http://citeseer.ist.psu.edu/geusebroek02fast.html More
@inproceedings{ geusebroek02fast,
author = "Jan-Mark Geusebroek and Arnold W. M. Smeulders and J. van de Weijer",
title = "Fast Anisotropic Gauss Filtering",
booktitle = "{ECCV} (1)",
pages = "99-112",
year = "2002",
url = "citeseer.ist.psu.edu/geusebroek02fast.html" }
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