| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0436547 |
| utime |
20240103205225.1 |
| mtime |
20150119235959.9 |
| SCOPUS |
84928523007 |
| WOS |
000380564200009 |
| DOI |
10.1109/SITIS.2014.48 |
| title
(primary) (eng) |
Accurate Detection of Non-Iris Occlusions |
| specification |
| page_count |
8 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0436546 |
| ISBN |
978-1-4799-7978-3 |
| title
|
Proceedings of the Tenth International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2014 |
| page_num |
49-56 |
| publisher |
| place |
Los Alamitos, USA |
| name |
IEEE Computer Society CPS |
| year |
2014 |
|
| editor |
| name1 |
Yetongno |
| name2 |
Kokou |
|
| editor |
| name1 |
Dipanda |
| name2 |
Albert |
|
| editor |
| name1 |
Chbeir |
| name2 |
Richard |
|
|
| keyword |
iris occlusions |
| keyword |
detection |
| keyword |
textural model |
| author
(primary) |
| ARLID |
cav_un_auth*0101093 |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| full_dept |
Department of Pattern Recognition |
| name1 |
Haindl |
| name2 |
Michal |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0292156 |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| full_dept |
Department of Pattern Recognition |
| name1 |
Krupička |
| name2 |
Mikuláš |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0303439 |
| project_id |
GA14-10911S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
Accurate detection of iris eyelids and reflections is the prerequisite for the accurate iris recognition, both in near-infrared or visible spectrum measurements. Undected iris occlusions otherwise dramatically decrease the iris recognition rate. This paper presents a fast multispectral iris occlusions detection method based on the underlying multispectral spatial probabilistic iris textural model and adaptive thresholding. The model adaptively learns its parameters on the iris texture part and subsequently checks for iris reflections, eyelashes, and eyelids using the recursive prediction analysis. Our method obtains better accuracy with respect to the previously performed Noisy Iris Challenge Evaluation contest. It ranked first from the 97+2 alternative methods on this large colour iris database. |
| action |
| ARLID |
cav_un_auth*0310868 |
| name |
Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS 2014) |
| dates |
23.11.2014-27.11.2014 |
| place |
Marrakech |
| country |
MA |
|
| RIV |
BD |
| reportyear |
2015 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0242825 |
| confidential |
S |
| arlyear |
2014 |
| mrcbU14 |
84928523007 SCOPUS |
| mrcbU34 |
000380564200009 WOS |
| mrcbU63 |
cav_un_epca*0436546 Proceedings of the Tenth International Conference on Signal-Image Technology & Internet-Based Systems, SITIS 2014 978-1-4799-7978-3 49 56 Los Alamitos, USA IEEE Computer Society CPS 2014 |
| mrcbU67 |
Yetongno Kokou 340 |
| mrcbU67 |
Dipanda Albert 340 |
| mrcbU67 |
Chbeir Richard 340 |
|