| bibtype |
J -
Journal Article
|
| ARLID |
0479748 |
| utime |
20240103214725.8 |
| mtime |
20171017235959.9 |
| SCOPUS |
85029597416 |
| WOS |
000413608100029 |
| DOI |
10.1016/j.sigpro.2017.08.027 |
| title
(primary) (eng) |
Rotation invariants from Gaussian-Hermite moments of color images |
| specification |
| page_count |
10 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0255076 |
| ISSN |
0165-1684 |
| title
|
Signal Processing |
| volume_id |
143 |
| volume |
1 (2018) |
| page_num |
282-291 |
| publisher |
|
|
| keyword |
Color images |
| keyword |
Object recognition |
| keyword |
Rotation invariants |
| keyword |
Gaussian–Hermite moments |
| keyword |
Joint invariants |
| author
(primary) |
| ARLID |
cav_un_auth*0236665 |
| name1 |
Yang |
| name2 |
B. |
| country |
CN |
|
| author
|
| ARLID |
cav_un_auth*0101203 |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| name1 |
Suk |
| name2 |
Tomáš |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101087 |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| name1 |
Flusser |
| name2 |
Jan |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0351712 |
| name1 |
Shi |
| name2 |
Z. |
| country |
CN |
|
| author
|
| ARLID |
cav_un_auth*0351713 |
| name1 |
Chen |
| name2 |
X. |
| country |
CN |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0314467 |
| project_id |
GA15-16928S |
| agency |
GA ČR |
|
| abstract
(eng) |
The topic of the paper is recognition of objects and patterns in color images regardless of their position, orientation, and scale. Gaussian–Hermite moment invariants designed especially for color images are in- troduced in this paper. We extend the existing invariants for graylevel images and show that in the case of color images there exist additional independent invariants, which can be constructed as joint invari- ants from cross-channel moments and/or from new non-trivial low-order moments. The experiments on real data confirmed that the new invariants improve the recognition rate. |
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20206 |
| reportyear |
2019 |
| num_of_auth |
5 |
| mrcbC52 |
4 A hod 4ah 20231122142728.3 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0276741 |
| mrcbC64 |
1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS |
| confidential |
S |
| mrcbC86 |
2 Article Engineering Electrical Electronic |
| mrcbT16-e |
ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-j |
0.821 |
| mrcbT16-s |
0.905 |
| mrcbT16-B |
58.44 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2018 |
| mrcbTft |
\nSoubory v repozitáři: suk-0479748.pdf |
| mrcbU14 |
85029597416 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000413608100029 WOS |
| mrcbU63 |
cav_un_epca*0255076 Signal Processing 0165-1684 1872-7557 Roč. 143 č. 1 2018 282 291 Elsevier |
|