A new article is available in IPOL: http://www.ipol.im/pub/art/2016/175/
Rafael Grompone von Gioi, and Gregory Randall,
Unsupervised Smooth Contour Detection,
Image Processing On Line, 6 (2016), pp. 233–267.
https://doi.org/10.5201/ipol.2016.175
Abstract
An unsupervised method for detecting smooth contours in digital images
is proposed. Following the a contrario approach, the starting point is
defining the conditions where contours should not be detected: soft
gradient regions contaminated by noise. To achieve this, low frequencies
are removed from the input image. Then, contours are validated as the
frontiers separating two adjacent regions, one with significantly larger
values than the other. Significance is evaluated using the Mann-Whitney
U test to determine whether the samples were drawn from the same
distribution or not. This test makes no assumption on the distributions.
The resulting algorithm is similar to the classic Marr-Hildreth edge
detector, with the addition of the statistical validation step. Combined
with heuristics based on the Canny and Devernay methods, an efficient
algorithm is derived producing sub-pixel contours.
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IPOL - Image Processing On Line - http://ipol.im/
contact [email protected] - http://www.ipol.im/meta/contact/
news+feeds twitter @IPOL_journal - http://www.ipol.im/meta/feeds/
announces [email protected] - http://tools.ipol.im/mm/announce/
discussions [email protected] - http://tools.ipol.im/mm/discuss/
