[IPOL announce] new article: The Gradient Product Transform: An Image Filter for Symmetry Detection
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Mon Dec 9 00:45:42 CET 2019
A new article is available in IPOL: http://www.ipol.im/pub/art/2019/270/
Christoph Dalitz, Jens Wilberg, and Manuel Jeltsch,
The Gradient Product Transform: An Image Filter for Symmetry Detection,
Image Processing On Line, 9 (2019), pp. 413–431.
https://doi.org/10.5201/ipol.2019.270
Abstract
The Gradient Product Transform (GPT) is an image filter that converts a
grayscale image into a float image, such that points representing a
point reflection symmetry center obtain a high score. Beside the
symmetry score, it also yields an estimator for the size of the symmetry
region around each point. Apart from describing the GPT, the article
also explains its application for two use cases: detection of objects
with a point reflection or C2m rotational symmetry, and the extraction
of blood vessel skeletons from medical images. For the detection of
symmetric objects, a score normalization procedure is suggested that
allows to choose a fixed threshold for score values representing actual
symmetries.
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