bibtype C - Conference Paper (international conference)
ARLID 0508021
utime 20240103222501.9
mtime 20190904235959.9
SCOPUS 85072864730
DOI 10.1007/978-3-030-29891-3_36
title (primary) (eng) Orthogonal Affine Invariants from Gaussian-Hermite Moments
specification
page_count 12 s.
media_type P
serial
ARLID cav_un_epca*0508720
ISBN 978-3-030-29929-3
title Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings
page_num 413-424
publisher
place Cham
name Springer
year 2019
editor
name1 Vento
name2 M.
editor
name1 Percannella
name2 G.
editor
name1 Colantonio
name2 S.
editor
name1 Giorgi
name2 D.
editor
name1 Matuszewski
name2 B. J.
editor
name1 Kerdegari
name2 H.
editor
name1 Razaak
name2 M.
keyword Affine transformation
keyword Invariants
keyword Image normalization
keyword Gaussian-Hermite moments
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*0236665
name1 Yang
name2 B.
country CN
source
url http://library.utia.cas.cz/separaty/2019/ZOI/flusser-0508021.pdf
cas_special
project
ARLID cav_un_auth*0360229
project_id GA18-07247S
agency GA ČR
abstract (eng) We propose a new kind of moment invariants with respect to an affine transformation. The new invariants are constructed in two steps. First, the affine transformation is decomposed into scaling, stretching and two rotations. The image is partially normalized up to the second rotation, and then rotation invariants from Gaussian-Hermite moments are applied. Comparing to the existing approaches – traditional direct affine invariants and complete image normalization – the proposed method is more numerically stable. The stability is achieved thanks to the use of orthogonal Gaussian-Hermite moments and also due to the partial normalization, which is more robust to small changes of the object than the complete normalization. Both effects are documented in the paper by experiments. Better stability opens the possibility of calculating affine invariants of higher orders with better discrimination power. This might be useful namely when different classes contain similar objects and cannot be separated by low-order invariants.
action
ARLID cav_un_auth*0380252
name International Conference on Computer Analysis of Images and Patterns, CAIP 2019 /18./
dates 20190902
mrcbC20-s 20190906
place Salerno
country IT
RIV JD
FORD0 20000
FORD1 20200
FORD2 20206
reportyear 2020
num_of_auth 3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0299553
confidential S
contract
name Copyright transfer
date 20190528
note Copyright
arlyear 2019
mrcbTft \nSoubory v repozitáři: flusser-0508021-copyright transfer.pdf
mrcbU14 85072864730 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0508720 Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Springer 2019 Cham 413 424 978-3-030-29929-3 Communications in Computer and Information Science 1089
mrcbU67 340 Vento M.
mrcbU67 340 Percannella G.
mrcbU67 340 Colantonio S.
mrcbU67 340 Giorgi D.
mrcbU67 340 Matuszewski B. J.
mrcbU67 340 Kerdegari H.
mrcbU67 340 Razaak M.