| bibtype |
J -
Journal Article
|
| ARLID |
0508907 |
| utime |
20240103222619.0 |
| mtime |
20190927235959.9 |
| SCOPUS |
85072665108 |
| WOS |
000487789000023 |
| DOI |
10.1049/iet-ipr.2019.0250 |
| title
(primary) (eng) |
Texture Spectral Similarity Criteria |
| specification |
| page_count |
10 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0320541 |
| ISSN |
1751-9659 |
| title
|
IET Image Processing |
| volume_id |
13 |
| volume |
11 (2019) |
| page_num |
1998-2007 |
| publisher |
|
|
| keyword |
Spectral similarity criterion |
| keyword |
bidirectional Texture Function |
| keyword |
hyper-spectral data |
| keyword |
texture modelling |
| author
(primary) |
| ARLID |
cav_un_auth*0283206 |
| name1 |
Havlíček |
| 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*0101093 |
| name1 |
Haindl |
| name2 |
Michal |
| 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 |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0376011 |
| project_id |
GA19-12340S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
New similarity criteria capable of assessing spectral modelling plausibility of colour, Bidirectional Texture Functions (BTF), and hyper-spectral textures are presented. The criteria credibly compare the multi-spectral pixel values of the textures. They simultaneously consider the pixels of similar values and their mutual ratios. It allows support of the optimal modelling or acquisition setup development by comparing the original data with its synthetic simulations. Analytical applications of the criteria can be spectral-based texture retrieval or classification. The suggested criteria together with existing alternatives are extensively tested and compared on a wide variety of colour, BTF, and hyper-spectral textures. The performance quality of the criteria is examined in a long series of thousands specially designed monotonically degrading experiments where proposed ones outperform all tested alternatives. |
| result_subspec |
WOS |
| RIV |
BD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2020 |
| num_of_auth |
2 |
| mrcbC52 |
4 A hod sml 4ah 4as 20231122144259.7 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0299790 |
| mrcbC64 |
1 Department of Pattern Recognition UTIA-B 10201 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE |
| confidential |
S |
| contract |
| name |
Copyright agreement |
| date |
20190607 |
| note |
Journals Publication Agreement and Assignment of Copyright Form |
|
| mrcbC86 |
2 Article Economics |
| mrcbC91 |
C |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|ENGINEERINGELECTRICALELECTRONIC|IMAGINGSCIENCEPHOTOGRAPHICTECHNOLOGY |
| mrcbT16-j |
0.295 |
| mrcbT16-s |
0.442 |
| mrcbT16-B |
20.662 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q4 |
| arlyear |
2019 |
| mrcbTft |
\nSoubory v repozitáři: haindl-0508907.pdf, haindl-0508907-copyright.pdf |
| mrcbU14 |
85072665108 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000487789000023 WOS |
| mrcbU63 |
cav_un_epca*0320541 IET Image Processing 1751-9659 1751-9667 Roč. 13 č. 11 2019 1998 2007 Wiley |
|