| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0546216 |
| utime |
20220320214411.1 |
| mtime |
20211005235959.9 |
| DOI |
10.1007/978-3-030-88113-9_52 |
| title
(primary) (eng) |
Optimized Texture Spectral Similarity Criteria |
| specification |
| page_count |
12 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0546212 |
| ISBN |
978-3-030-88113-9 |
| ISSN |
1865-0929 |
| title
|
Advances in Computational Collective Intelligence |
| page_num |
644-655 |
| publisher |
| place |
Cham |
| name |
Springer International Publishing |
| year |
2021 |
|
| editor |
| name1 |
Wojtkiewicz |
| name2 |
Krystian |
|
| editor |
|
| editor |
| name1 |
Pimenidis |
| name2 |
Elias |
|
| editor |
| name1 |
Maleszka |
| name2 |
Marcin |
|
|
| keyword |
Texture spectral similarity criterion |
| keyword |
Bidirectional Texture Function |
| keyword |
hyperspectral data |
| keyword |
texture modeling |
| 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 |
|
| cas_special |
| project |
| project_id |
GA19-12340S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0376011 |
|
| abstract
(eng) |
This paper introduces an accelerated algorithm for evaluating criteria for comparing the spectral similarity of color, Bidirectional Texture Functions (BTF), and hyperspectral textures. The criteria credibly compare texture pixels by simultaneously considering the pixels with similar values and their mutual ratios. Such a comparison can determine the optimal modeling or acquisition setup by comparing the original data with their synthetic simulations. Other applications of the criteria can be spectral-based texture retrieval or classification. Together with existing alternatives, the suggested methods were extensively tested and compared on a wide variety of color, BTF, and hyper-spectral textures. The methods' performance quality was examined in a long series of specially designed experiments where proposed ones outperform all tested alternatives. |
| action |
| ARLID |
cav_un_auth*0414747 |
| name |
International Conference on Computational Collective Intelligence 2021 /13./ |
| dates |
20210929 |
| mrcbC20-s |
20211001 |
| place |
Kallithea, Rhodes |
| country |
GR |
|
| RIV |
BD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20202 |
| reportyear |
2022 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0323757 |
| cooperation |
| ARLID |
cav_un_auth*0414750 |
| name |
Fakulta managementu, VŠE |
| institution |
FM VŠE |
| country |
CZ |
|
| confidential |
S |
| article_num |
52 |
| arlyear |
2021 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0546212 Advances in Computational Collective Intelligence Springer International Publishing 2021 Cham 644 655 978-3-030-88113-9 Communications in Computer and Information Science 1463 1865-0929 |
| mrcbU67 |
Wojtkiewicz Krystian 340 |
| mrcbU67 |
Treur Jan 340 |
| mrcbU67 |
Pimenidis Elias 340 |
| mrcbU67 |
Maleszka Marcin 340 |
|