| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0522438 |
| utime |
20240103223800.6 |
| mtime |
20200224235959.9 |
| SCOPUS |
85081552252 |
| DOI |
10.1007/978-3-030-41299-9_33 |
| title
(primary) (eng) |
3D Multi-frequency Fully Correlated Causal Random Field Texture Model |
| specification |
| page_count |
12 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0522437 |
| ISBN |
978-3-030-41298-2 |
| ISSN |
0302-9743 |
| title
|
Pattern Recognition |
| page_num |
423-434 |
| publisher |
| place |
Cham |
| name |
Springer International Publishing |
| year |
2020 |
|
| editor |
| name1 |
Palaiahnakote |
| name2 |
Shivakumara |
|
| editor |
| name1 |
Sanniti di Baja |
| name2 |
Gabriella |
|
| editor |
|
| editor |
|
|
| keyword |
texture modeling |
| keyword |
Markov random field |
| keyword |
Bidirectional Texture Function |
| author
(primary) |
| ARLID |
cav_un_auth*0101093 |
| name1 |
Haindl |
| name2 |
Michal |
| institution |
UTIA-B |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101100 |
| name1 |
Havlíček |
| name2 |
Vojtěch |
| institution |
UTIA-B |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA19-12340S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0376011 |
|
| abstract
(eng) |
We propose a fast novel multispectral texture model with an analytical solution for both parameter estimation as well as unlimited synthesis. This Gaussian random field type of model combines a principal random field containing measured multispectral pixels with an auxiliary random field resulting from a given function whose argument is the principal field data.\nThe model can serve as a stand-alone texture model or a local model for more complex compound random field or bidirectional texture function models.\nThe model can be beneficial not only for texture synthesis, enlargement, editing, or compression but also for high accuracy texture recognition. |
| action |
| ARLID |
cav_un_auth*0389856 |
| name |
The 5th Asian Conference on Pattern Recognition (ACPR 2019) |
| dates |
20191126 |
| mrcbC20-s |
20191129 |
| place |
Auckland |
| country |
NZ |
|
| RIV |
BD |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10102 |
| reportyear |
2021 |
| num_of_auth |
2 |
| mrcbC52 |
4 A sml 4as 20231122144803.6 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0307296 |
| confidential |
S |
| contract |
| name |
Consent to Publish |
| date |
20190920 |
|
| article_num |
33 |
| arlyear |
2020 |
| mrcbTft |
\nSoubory v repozitáři: haindl-0522438-Copyright_ID56.pdf |
| mrcbU14 |
85081552252 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0522437 Pattern Recognition 978-3-030-41298-2 0302-9743 1611-3349 423 434 Cham Springer International Publishing 2020 Lecture Notes in Computer Science 12047 |
| mrcbU67 |
340 Palaiahnakote Shivakumara |
| mrcbU67 |
340 Sanniti di Baja Gabriella |
| mrcbU67 |
340 Wang Liang |
| mrcbU67 |
340 Yan Wei Qi |
|