bibtype C - Conference Paper (international conference)
ARLID 0575788
utime 20240402214441.9
mtime 20230925235959.9
DOI 10.1007/978-3-031-44237-7_28
title (primary) (eng) 3D Non-separable Moment Invariants
specification
page_count 11 s.
media_type P
serial
ARLID cav_un_epca*0575787
ISBN 978-3-031-44236-0
title Computer Analysis of Images and Patterns. CAIP 2023
page_num 295-305
publisher
place Cham
name Springer
year 2023
editor
name1 Tsapatsoulis
name2 N.
keyword 3D recognition
keyword 3D rotation invariants
keyword non-separable moments
keyword Appell polynomials
author (primary)
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101203
name1 Suk
name2 Tomáš
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0426512
name1 Bedratyuk
name2 L.
country UA
author
ARLID cav_un_auth*0438860
name1 Karella
name2 Tomáš
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2023/ZOI/flusser-0575788.pdf
cas_special
project
project_id GA21-03921S
agency GA ČR
ARLID cav_un_auth*0412209
abstract (eng) In this paper, we introduce new 3D rotation moment invariants, which are composed of non-separable Appell moments. The Appell moments can be substituted directly into the 3D rotation invariants instead of the geometric moments without violating their invariance. We show that non-separable moments may outperform the separable ones in terms of recognition power and robustness thanks to a better distribution of their zero surfaces over the image space. We test the numerical properties and discrimination power of the proposed invariants on three real datasets – MRI images of human brain, 3D scans of statues, and confocal microscope images of worms.
action
ARLID cav_un_auth*0455368
name Computer Analysis of Images and Patterns. CAIP 2023
dates 20230925
mrcbC20-s 20230928
place Limassol
country CY
RIV JD
FORD0 20000
FORD1 20200
FORD2 20206
reportyear 2024
num_of_auth 4
presentation_type PR
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0345843
cooperation
ARLID cav_un_auth*0455369
name Khmelnytsky National University
institution KNU
country UA
confidential S
arlyear 2023
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0575787 Computer Analysis of Images and Patterns. CAIP 2023 Springer 2023 Cham 295 305 978-3-031-44236-0 Lecture Notes in Computer Science 14184
mrcbU67 Tsapatsoulis N. 340