Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code

Published: 16 Oct 2018 | Version 1 | DOI: 10.17632/8znncdk4xr.1
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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:

Mirror symmetry detection in curves represented by means of the Slope Chain Code

Published in: Pattern Recognition

Latest version

  • Version 1

    2018-10-16

    Published: 2018-10-16

    DOI: 10.17632/8znncdk4xr.1

    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

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Pattern Recognition

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