Title :
The first ICB* competition on iris recognition
Author :
Man Zhang ; Jing Liu ; Zhenan Sun ; Tieniu Tan ; Wu Su ; Alonso-Fernandez, Fernando ; Nemesin, Valerian ; Othman, Norazila ; Noda, Kentaro ; Peihua Li ; Hoyle, Edmundo ; Joshi, Akanksha
Author_Institution :
Center for Res. on Intell. Perception & Comput., Inst. of Autom., Beijing, China
fDate :
Sept. 29 2014-Oct. 2 2014
Abstract :
Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB* Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database (e.g. CASIA-Iris-Thousand [3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0.0001 are taken to rank the submitted algorithms.
Keywords :
image matching; image texture; iris recognition; CASIA-Iris-Thousand public database; FMR; FNMR; First ICB* Competition on Iris Recognition; ICIR2013; false match rate; false nonmatch rate; human iris visual patterns; intraclass iris image matching; personal identification; texture information; unconstrained environments; unpublished database; Databases; Image edge detection; Image segmentation; Iris recognition; Magnetic resonance; Noise; Testing;
Conference_Titel :
Biometrics (IJCB), 2014 IEEE International Joint Conference on
Conference_Location :
Clearwater, FL
DOI :
10.1109/BTAS.2014.6996292