Abstract
In this paper we present classification experiments made on occluded irises images, using color and SIFT features. We used previously proposed extensions for a well-known, simple, global color criterion and a modified SIFT method. We present the results obtained in classification on a well-known iris dataset, UPOL, and on several occluded image datasets generated from it. The results obtained are compared with those provided by the Masek implementation of the Daugman's method. The classification rate, EER (Equal Error Rate) and AUC (Area Under the ROC Curve) were computed for the evaluation of the results.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
