| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0571260 |
| utime |
20240402213835.5 |
| mtime |
20230428235959.9 |
| DOI |
10.1007/978-3-031-31435-3_20 |
| title
(primary) (eng) |
Affine Moment Invariants of Tensor Fields |
| specification |
| page_count |
15 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0571254 |
| ISBN |
978-3-031-31437-7 |
| title
|
Image Analysis: 23rd Scandinavian Conference, SCIA 2023 |
| page_num |
299-313 |
| publisher |
| place |
Cham |
| name |
Springer |
| year |
2023 |
|
| editor |
|
|
| keyword |
Tensor field |
| keyword |
affine invariants |
| keyword |
template matching |
| 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*0377447 |
| name1 |
Lébl |
| name2 |
Matěj |
| 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 |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0349350 |
| name1 |
Bujack |
| name2 |
R. |
| country |
US |
|
| author
|
| ARLID |
cav_un_auth*0244806 |
| name1 |
Ibrahim |
| name2 |
I. |
| country |
CZ |
|
| source |
|
| cas_special |
| project |
| project_id |
GA21-03921S |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0412209 |
|
| project |
| project_id |
StrategieAV21/1 |
| agency |
AV ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0328930 |
|
| project |
| project_id |
IN 0002300 |
| agency |
GA MZd |
| country |
CZ |
| ARLID |
cav_un_auth*0449355 |
|
| abstract
(eng) |
Tensor fields (TF) are a special kind of multidimensional data, in which a tensor is given for each point in space. Often, it is a 3 × 3 array in each voxel. To detect the patterns of interest in the field, special matching methods must be developed. We propose a method for the description and matching of TF patterns under an unknown affine transformation of the field. Transformations of TFs act not only in the spatial coordinates but also on the field values, which makes the detection more challenging. To measure the similarity between the template and the field patch, we propose original invariants with respect to affine transformations designed from moments. Their performance is demonstrated by experiments on real data from diffusion tensor imaging. |
| action |
| ARLID |
cav_un_auth*0449343 |
| name |
Scandinavian Conference on Image Analysis 2023 /23./ |
| dates |
20230418 |
| mrcbC20-s |
20230421 |
| place |
Levi |
| country |
FI |
|
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20206 |
| reportyear |
2024 |
| num_of_auth |
5 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0342936 |
| cooperation |
| ARLID |
cav_un_auth*0449356 |
| name |
MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine IKEM, V ́ıdeˇnsk ́a 1958/9, 140 21 Praha 4, Czech Republic |
| institution |
IKEM |
| country |
CZ |
|
| confidential |
S |
| arlyear |
2023 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0571254 Image Analysis: 23rd Scandinavian Conference, SCIA 2023 978-3-031-31437-7 299 313 Cham Springer 2023 Lecture notes on computer science LNCS 13886 |
| mrcbU67 |
Gade R. 340 |
|