Number of the records: 1
Texture Quality Criteria Comparison
- 1.0574371 - ÚTIA 2024 RIV US eng C - Conference Paper (international conference)
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]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : Texture quality criteria * Spearman correlation * Human quality ranking * Texture quality benchmark
OECD category: 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.
Permanent Link: https://hdl.handle.net/11104/0344727
Number of the records: 1