Texture Quality Criteria Comparison

0574371 - ÚTIA 2024 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Haindl, Michal - Shaih, N.
Texture Quality Criteria Comparison.
Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW 2023). Piscataway: IEEE, 2023, č. článku 7101. ISBN 979-8-3503-0262-2.
[IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2023 /48./. Rhodes (GR), 04.06.2023-10.06.2023]
Grant CEP: GA ČR(CZ) GA19-12340S
Institucionální podpora: RVO:67985556
Klíčová slova: Texture quality criteria * Spearman correlation * Human quality ranking * Texture quality benchmark
Obor OECD: Automation and control systems
http://library.utia.cas.cz/separaty/2023/RO/haindl-0574371.pdf

Visual scene recognition or modeling predominantly uses visual textures representing an object's material properties. However, the single material texture varies in scale and illumination angles due to mapping an object's shape. We present a comparative study of thirteen possible texture quality criteria and show the superior performance of two multispectral measures derived from the Markovian descriptive model.
Trvalý link: https://hdl.handle.net/11104/0344727