| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0447048 |
| utime |
20240103210528.2 |
| mtime |
20150922235959.9 |
| WOS |
000364705500025 |
| SCOPUS |
84945926595 |
| DOI |
10.1007/978-3-319-23192-1_25 |
| title
(primary) (eng) |
Wood Veneer Species Recognition using Markovian Textural Features |
| specification |
| page_count |
12 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0447047 |
| ISBN |
978-3-319-23192-1 |
| ISSN |
0302-9743 |
| title
|
Computer Analysis of Images and Patterns - CAIP 2015 |
| part_num |
I |
| part_title |
9256 |
| page_num |
300-311 |
| publisher |
| place |
Switzerland |
| name |
Springer International Publishing |
| year |
2015 |
|
| editor |
| name1 |
Azzopardi |
| name2 |
George |
|
| editor |
| name1 |
Petkov |
| name2 |
Nicolai |
|
|
| keyword |
Wood recognition |
| keyword |
Textural features |
| keyword |
Illumination invariants |
| keyword |
Surface reflectance field |
| keyword |
Bidirectional texture function |
| author
(primary) |
| ARLID |
cav_un_auth*0101093 |
| name1 |
Haindl |
| name2 |
Michal |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| 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*0213290 |
| name1 |
Vácha |
| name2 |
Pavel |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| institution |
UTIA-B |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA14-10911S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0303439 |
|
| abstract
(eng) |
A mobile Android application that can automatically recognize wood species from a low quality mobile phone photo under varying illumination conditions is presented. The wood recognition is based on the Markovian, spectral, and illumination invariant textural features. The method performance was verified on a wood database, which contains veneers from sixty-six varied European and exotic wood species. The Markovian features improvement of the correct wood recognition rate is about 40 % compared to the best alternative - the Local Binary Patterns features. |
| action |
| ARLID |
cav_un_auth*0319317 |
| name |
16th International Conference on Computer Analysis of Images and Patterns |
| place |
Valletta |
| dates |
02.09.2015-04.09.2015 |
| country |
MT |
|
| reportyear |
2016 |
| RIV |
BD |
| num_of_auth |
2 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0249423 |
| confidential |
S |
| mrcbT16-s |
0.329 |
| mrcbT16-4 |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2015 |
| mrcbU14 |
84945926595 SCOPUS |
| mrcbU34 |
000364705500025 WOS |
| mrcbU63 |
cav_un_epca*0447047 Computer Analysis of Images and Patterns - CAIP 2015 I 978-3-319-23192-1 0302-9743 300 311 Computer Analysis of Images and Patterns - CAIP 2015 Switzerland Springer International Publishing 2015 Lecture Notes in Computer Science 9256 |
| mrcbU67 |
Azzopardi George 340 |
| mrcbU67 |
Petkov Nicolai 340 |
|