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G. Ramachandran, W. Kropatsch:
"A combined distance measure for 2d shape matching";
Vortrag: International Conference on Computer Vision and Image Analysis, ICCVIA2015, Tunesien, Suisse; 18.01.2015 - 20.01.2015; in: "Proceedings of the International Conference on Computer Vision and Image Analysis, ICCVIA2015", IEEE: Computer Vision and Image Analysis Applications (ICCVIA), 2015 International Conference on, Computer Vision and Image Analysis Applications (ICCVIA), 2015 International Conference on (2015), ISBN: 978-1-4799-7185-5; 5 S.

We present a method for 2D shape matching using
a combination of distance functions and discrete curvature. The
eccentricity transform computes the longest geodesic distance
across the object. This transform is invariant to translation
and rotation. The maximal eccentricity points yield diameters
across the image. We compute the Euclidean distances from the
boundary to the diameter to characterize the curvature of the
shape. Our shape descriptor is comprised of the best matches
retrieved from the normalized histogram of the eccentricities, the
Hausdorff distance between the set of distances to the diameter
and a measure of the number of points lying on either side of the
diameter along with the peak values. We evaluate this descriptor
on 2D image databases consisting of rigid and articulated shapes
by ranking the number of matches. In almost all cases, the shapes
are matched with at least one shape from the same class.

http://dx.doi.org/10.1109/ICCVIA.2015.7351875

http://publik.tuwien.ac.at/files/PubDat_243509.pdf