Optimized Texture Spectral Similarity Criteria
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F21%3A00546216" target="_blank" >RIV/67985556:_____/21:00546216 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31160/21:00057617
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-88113-9_52" target="_blank" >http://dx.doi.org/10.1007/978-3-030-88113-9_52</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-88113-9_52" target="_blank" >10.1007/978-3-030-88113-9_52</a>
Alternative languages
Result language
angličtina
Original language name
Optimized Texture Spectral Similarity Criteria
Original language description
This paper introduces an accelerated algorithm for evaluating criteria for comparing the spectral similarity of color, Bidirectional Texture Functions (BTF), and hyperspectral textures. The criteria credibly compare texture pixels by simultaneously considering the pixels with similar values and their mutual ratios. Such a comparison can determine the optimal modeling or acquisition setup by comparing the original data with their synthetic simulations. Other applications of the criteria can be spectral-based texture retrieval or classification. Together with existing alternatives, the suggested methods were extensively tested and compared on a wide variety of color, BTF, and hyper-spectral textures. The methods' performance quality was examined in a long series of specially designed experiments where proposed ones outperform all tested alternatives.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
<a href="/en/project/GA19-12340S" target="_blank" >GA19-12340S: Surface material recognition under variable optical observation conditions</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Computational Collective Intelligence
ISBN
978-3-030-88113-9
ISSN
1865-0929
e-ISSN
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Number of pages
12
Pages from-to
644-655
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Kallithea, Rhodes
Event date
Sep 29, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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