Comparison of Triangular Meshes Using Shape Functions and MSA
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F22%3A00357194" target="_blank" >RIV/68407700:21220/22:00357194 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-96302-6_22" target="_blank" >http://dx.doi.org/10.1007/978-3-030-96302-6_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-96302-6_22" target="_blank" >10.1007/978-3-030-96302-6_22</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of Triangular Meshes Using Shape Functions and MSA
Original language description
In computer graphics, shape recognition is widely solved problem. The shape functions, shape distribution and Minkowski norm are the standard methods for the determination of similarity measure. In this paper, the shape functions D2, D3 and new C1 are applied to five triangular meshes of a half-sphere, a cylinder and a plane obtained from ball-bar, ring, and gauge block after trimming. In the using of optical scanners the calibration is necessary and it is done using calibration artefacts with known dimensions (according to which the calibration is executed). So, it is useful to find the algorithm, where the known dimensions are not necessary for calibration. Therefore, the aim of this paper (and the first step for finding the algorithm) is to define whether each shape function is competent to measure the similarity and whether the new shape function C1 is as good as the standard functions. To determine it, Measurement System Analysis (MSA) was used.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
ISBN
978-3-030-96301-9
ISSN
2367-3370
e-ISSN
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Number of pages
12
Pages from-to
237-248
Publisher name
Springer Nature Switzerland AG
Place of publication
Basel
Event location
online
Event date
Dec 15, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000774224200022