bibtype |
C -
Conference Paper (international conference)
|
ARLID |
0106294 |
utime |
20240103173132.8 |
mtime |
20050324235959.9 |
title
(primary) (eng) |
A Gaussian mixture-based colour texture model |
specification |
|
serial |
title
|
Proceedings of the 17th IAPR International Conference on Pattern Recognition |
part_num |
3 |
page_num |
177-180 |
ISBN |
0-7695-2128-2 |
publisher |
place |
Los Alamitos |
name |
IEEE |
year |
2004 |
|
|
title
(cze) |
Texturní model založený na gaussovských směsích |
keyword |
texture synthesis |
keyword |
mixture models |
author
(primary) |
ARLID |
cav_un_auth*0101093 |
name1 |
Haindl |
name2 |
Michal |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101091 |
name1 |
Grim |
name2 |
Jiří |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101197 |
name1 |
Somol |
name2 |
Petr |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101182 |
name1 |
Pudil |
name2 |
Pavel |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
name1 |
Kudo |
name2 |
M. |
country |
JP |
ARLID |
cav_un_auth*0021088 |
|
COSATI |
09K |
cas_special |
project |
project_id |
IST-2001-34744 |
agency |
Commission EC |
country |
XE |
ARLID |
cav_un_auth*0200688 |
|
project |
project_id |
507752 |
country |
XE |
agency |
EC |
ARLID |
cav_un_auth*0200689 |
|
project |
project_id |
GA402/03/1310 |
agency |
GA ČR |
ARLID |
cav_un_auth*0009030 |
|
research |
CEZ:AV0Z1075907 |
abstract
(eng) |
A new method of colour texture modelling based on Gaussian distribution mixtures is discussed. We estimate the local statistical properties of the monospectral version of the target texture in the form of a Gaussian mixture of product components. The synthesized texture is obtained by means of a step-wise prediction of the texture image. The proposed texture modelling method can be viewed as a statistically controlled sampling. |
abstract
(cze) |
Práce popisuje novou metodu pro modelování barevných textur založenou na pravděpodobnostním modelu typu gaussovské distribuční směsi. Odhadujeme lokální statistické vlastnosti monospektrální verze cílové textury ve formě gaussovské směsi součinových složek. Syntéza textury je založena na predikci texturního obrazu |
action |
ARLID |
cav_un_auth*0129876 |
name |
International Conference on Pattern Recognition /17./ |
place |
Cambridge |
dates |
23.08.2004-26.08.2004 |
country |
GB |
|
reportyear |
2005 |
RIV |
BD |
permalink |
http://hdl.handle.net/11104/0013476 |
ID_orig |
UTIA-B 20040106 |
arlyear |
2004 |
mrcbU63 |
Proceedings of the 17th IAPR International Conference on Pattern Recognition 3 0-7695-2128-2 177 180 Los Alamitos IEEE 2004 |
mrcbU67 |
Kittler J. 340 |
mrcbU67 |
Petrou M. 340 |
mrcbU67 |
Nixon M. 340 |
|