Textural Features Sensitivity to Scale and Illumination Variations

0561404 - ÚTIA 2023 RIV CH eng C - Conference Paper (international conference)
Vácha, Pavel - Haindl, Michal
Textural Features Sensitivity to Scale and Illumination Variations.
Advances in Computational Collective Intelligence : 14th International Conference, ICCCI 2022. Cham: Springer International Publishing, 2022 - (Badica, C.), s. 237-249. Communications in Computer and Information Science, 1653. ISBN 978-3-031-16209-1. ISSN 1865-0929. E-ISSN 1865-0937.
[International Conference on Computational Collective Intelligence (ICCCI 2022) /14./. Hammamet (TN), 26.09.2022-30.09.2022]
R&D Projects: GA ČR(CZ) GA19-12340S
Institutional support: RVO:67985556
Keywords : Markovian Textural Features * Scale Sensitivity * Illumination Sensitivity
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2022/RO/vacha-0561404.pdf

Visual scene recognition is predominantly based on 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 the color histogram, Gabor, opponent Gabor, Local Binary Pattern (LBP), and wide-sense Markovian textural features concerning their sensitivity to simultaneous scale and illumination variations. Due to their application dominance, these textural features are selected from more than
50 published textural features. Markovian features are information preserving, and we demonstrate their superior performance for scale and illumination variable observation conditions over the standard alternative textural features. We bound the scale variation by double size, and illumination variation includes illumination spectra, acquisition devices, and 35 illumination directions spanned above a sample.
Permanent Link: https://hdl.handle.net/11104/0334061