Title :
Measuring the Quality of IRIS Segmentation for Improved IRIS Recognition Performance
Author :
Hentati, R. ; Dorizzi, Bernadette ; Aoudni, Y. ; Abid, Mohamed
Author_Institution :
Lab. of Comput. & Embedded Syst. (CES), Nat. Sch. of Eng. of Sfax, Sfax, Tunisia
Abstract :
In this paper, we present three versions of an open source software for biometric iris recognition called OSIRIS_V2, OSIRIS_V3, OSIRIS_V4 which correspond to different implementations of J. Daugman´s approach. The experimental results on the database ICE2005 show that OSIRIS_V4 is the most reliable on difficult images while OSIRIS_V2 is the fastest. So, we propose a novel strategy for iris recognition using OSIRIS_V2 for good quality images and OSIRIS_V4 when the quality of the segmentation of OSIRIS_V2 is not sufficient to ensure good performance. To this end, we measure the quality of an iris segmentation thanks to a GMM model trained on good quality iris texture and we use a threshold on this quality value to shift between the 2 versions of OSIRIS. We show on ICE2005 database how the choice of this threshold value allows compromising between performance and processing speed of the complete process.
Keywords :
Gaussian processes; image segmentation; iris recognition; GMM model; IRIS segmentation; OSIRIS_V2; OSIRIS_V4; biometric iris recognition; iris texture; open source software; Databases; Equations; Feature extraction; Image segmentation; Iris; Iris recognition; Mathematical model; EER; GMM; OSIRIS; execution time; iris authentication; segmentation quality;
Conference_Titel :
Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on
Conference_Location :
Naples
Print_ISBN :
978-1-4673-5152-2
DOI :
10.1109/SITIS.2012.27