bibtype C - Conference Paper (international conference)
ARLID 0574371
utime 20240402214252.0
mtime 20230818235959.9
DOI 10.1109/ICASSPW59220.2023.10193606
title (primary) (eng) Texture Quality Criteria Comparison
specification
page_count 5 s.
media_type P
serial
ARLID cav_un_epca*0574370
ISBN 979-8-3503-0262-2
title Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW 2023)
publisher
place Piscataway
name IEEE
year 2023
keyword Texture quality criteria
keyword Spearman correlation
keyword Human quality ranking
keyword Texture quality benchmark
author (primary)
ARLID cav_un_auth*0101093
name1 Haindl
name2 Michal
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
garant A
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0453250
name1 Shaih
name2 N.
country IN
source
url http://library.utia.cas.cz/separaty/2023/RO/haindl-0574371.pdf
cas_special
project
project_id GA19-12340S
agency GA ČR
country CZ
ARLID cav_un_auth*0376011
abstract (eng) 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.
action
ARLID cav_un_auth*0453251
name IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2023 /48./
dates 20230604
mrcbC20-s 20230610
place Rhodes
country GR
RIV IN
FORD0 20000
FORD1 20200
FORD2 20205
reportyear 2024
num_of_auth 2
presentation_type PR
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0344727
confidential S
article_num 7101
arlyear 2023
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0574370 Proceedings of the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW 2023) IEEE 2023 Piscataway 979-8-3503-0262-2