bibtype J - Journal Article
ARLID 0584124
utime 20250310160018.7
mtime 20240313235959.9
SCOPUS 85173756924
WOS 001080214500001
DOI 10.1080/24751839.2023.2265190
title (primary) (eng) Texture recognition under scale and illumination variations
specification
page_count 19 s.
media_type P
serial
ARLID cav_un_epca*0584123
ISSN 2475-1839
title Journal of Information and Telecommunication
volume_id 8
volume 1 (2024)
page_num 130-148
keyword Markovian Textural features
keyword LBP
keyword Gabor features
keyword scale sensitivity
keyword illumination sensitivity
author (primary)
ARLID cav_un_auth*0213290
name1 Vácha
name2 Pavel
institution UTIA-B
full_dept (cz) Rozpoznávání obrazu
full_dept (eng) Department of Pattern Recognition
department (cz) RO
department (eng) RO
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101093
name1 Haindl
name2 Michal
institution UTIA-B
full_dept (cz) Rozpoznávání obrazu
full_dept Department of Pattern Recognition
department (cz) RO
department RO
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url https://www.tandfonline.com/doi/full/10.1080/24751839.2023.2265190
source
url http://library.utia.cas.cz/separaty/2024/RO/haindl-0584124.pdf
cas_special
project
project_id GA19-12340S
agency GA ČR
country CZ
ARLID cav_un_auth*0376011
abstract (eng) 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.\nMarkovian 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 hemisphere. Recognition accuracy is tested on textile patterns from the University of East Anglia and wood veneers from UTIA BTF databases.
reportyear 2025
RIV BD
result_subspec WOS
FORD0 20000
FORD1 20200
FORD2 20205
num_of_auth 2
mrcbC52 2 R hod 4 4rh 4 20250310154629.1 4 20250310160018.7
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0352103
confidential S
mrcbC91 A
mrcbT16-s 0.674
mrcbT16-E Q2
arlyear 2024
mrcbTft \nSoubory v repozitáři: haindl-0584124.pdf
mrcbU14 85173756924 SCOPUS
mrcbU24 PUBMED
mrcbU34 001080214500001 WOS
mrcbU63 cav_un_epca*0584123 Journal of Information and Telecommunication 2475-1839 2475-1847 Roč. 8 č. 1 2024 130 148