Multispectral Texture Benchmark

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00370130" target="_blank" >RIV/68407700:21240/23:00370130 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.procs.2023.10.308" target="_blank" >https://doi.org/10.1016/j.procs.2023.10.308</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2023.10.308" target="_blank" >10.1016/j.procs.2023.10.308</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multispectral Texture Benchmark

Popis výsledku v původním jazyce

Dozens of textural features have been published, but their realistic validation for efficient recognition applications still needs to be discovered. Textural features are derived using various approaches. We present a benchmark that can be used to evaluate these features and categorize them based on their information efficiency. We propose how the features can be benchmarked and explain different ways of measuring their properties and performance. Most textural feature-extracting algorithms are only based on information extraction from monospectral images (gray-level). Apart from native multispectral algorithms, we generalize some of these originally monospectral features for hyperspectral textures in our illustrating examples.

Název v anglickém jazyce

Multispectral Texture Benchmark

Popis výsledku anglicky

Dozens of textural features have been published, but their realistic validation for efficient recognition applications still needs to be discovered. Textural features are derived using various approaches. We present a benchmark that can be used to evaluate these features and categorize them based on their information efficiency. We propose how the features can be benchmarked and explain different ways of measuring their properties and performance. Most textural feature-extracting algorithms are only based on information extraction from monospectral images (gray-level). Apart from native multispectral algorithms, we generalize some of these originally monospectral features for hyperspectral textures in our illustrating examples.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Procedia Computer Science

ISSN

1877-0509

e-ISSN

1877-0509

Svazek periodika

225

Číslo periodika v rámci svazku

December

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

3143-3152

Kód UT WoS článku

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EID výsledku v databázi Scopus

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