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 |
|
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 |
|