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Multispectral Texture Benchmark

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F23%3A00579556" target="_blank" >RIV/67985556:_____/23:00579556 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S1877050923014667?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050923014667?via%3Dihub</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>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Multispectral Texture Benchmark

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Procedia Computer Science : Volume 225, 27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

  • ISBN

  • ISSN

    1877-0509

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    3143-3152

  • Publisher name

    Elsevier

  • Place of publication

    Amsterdam

  • Event location

    Athens

  • Event date

    Sep 6, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article