[IPOL announce] new article: The Gradient Product Transform: An Image Filter for Symmetry Detection

[announcements about the IPOL journal]

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.