Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code
Description of this data
We propose a new method to characterize mirror-symmetry in open and closed curves represented by means of the Slope Chain Code. This representation is invariant under scale, rotation, and translation. The proposed method allows the classification of symmetrical and asymmetrical contours. It also introduces a measure to quantify the degree of symmetry in quasi-mirror-symmetrical objects. Furthermore, it allows the identification of multiple symmetry axes and their location. The proposed algorithm provides properties such as: global, local, and multiple axes’ detection, as well as the capability to classify symmetrical objects.
Experiment data files
This data is associated with the following publication:
Cite this dataset
Alvarado, Alicia Montserrat; Aguilar, Wendy (2018), “Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code”, Mendeley Data, v1 http://dx.doi.org/10.17632/8znncdk4xr.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.