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

Main Author: Alvarado, Alicia Montserrat
Other Authors: Aguilar, Wendy
Format: Dataset
Terbitan: Mendeley , 2018
Subjects:
Online Access: https:/data.mendeley.com/datasets/8znncdk4xr
ctrlnum 0.17632-8znncdk4xr.1
fullrecord <?xml version="1.0"?> <dc><creator>Alvarado, Alicia Montserrat</creator><title>Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code</title><publisher>Mendeley</publisher><description>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&#x2019; detection, as well as the capability to classify symmetrical objects.</description><subject>Pattern Recognition</subject><contributor>Aguilar, Wendy</contributor><type>Other:Dataset</type><identifier>10.17632/8znncdk4xr.1</identifier><rights>Creative Commons Attribution 4.0 International</rights><rights>http://creativecommons.org/licenses/by/4.0</rights><relation>https:/data.mendeley.com/datasets/8znncdk4xr</relation><date>2018-10-16T10:37:41Z</date><recordID>0.17632-8znncdk4xr.1</recordID></dc>
format Other:Dataset
Other
author Alvarado, Alicia Montserrat
author2 Aguilar, Wendy
title Data for: Mirror Symmetry Detection in Curves Represented by Means of the Slope Chain Code
publisher Mendeley
publishDate 2018
topic Pattern Recognition
url https:/data.mendeley.com/datasets/8znncdk4xr
contents 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.
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institution Universitas Islam Indragiri
affiliation onesearch.perpusnas.go.id
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institution_type library:university
library
library Teknologi Pangan UNISI
library_id 2816
collection Artikel mulono
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city INDRAGIRI HILIR
province RIAU
shared_to_ipusnas_str 1
repoId IOS7969
first_indexed 2020-04-08T08:31:17Z
last_indexed 2020-04-08T08:31:17Z
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