Title :
Contact Lens Detection and Classification in Iris Images through Scale Invariant Descriptor
Author :
Gragnaniello, Diego ; Poggi, Giovanni ; Sansone, Carlo ; Verdoliva, Luisa
Author_Institution :
DIETI, Univ. Federico II di Napoli, Naples, Italy
Abstract :
We propose a new machine-learning technique for detecting the presence and type of contact lenses in iris images. Following the usual paradigm, we extract the regions of interest for classification, compute a feature vector based on local descriptors, and feed it to a properly trained SVM classifier. Major improvements w.r.t. Current state of the art concern the design of a more reliable segmentation procedure and the use of a recently proposed dense scale-invariant image descriptor. Experiments on publicly available datasets show the proposed method to outperform significantly all reference techniques.
Keywords :
contact lenses; feature extraction; image classification; iris recognition; learning (artificial intelligence); support vector machines; vectors; SVM classifier; contact lens classification; contact lens detection; feature vector; iris image; machine-learning technique; regions of interest extraction; scale invariant descriptor; Eyelids; Feature extraction; Image edge detection; Image segmentation; Iris; Iris recognition; Lenses; Contact lens classification; Iris biometrics; local descriptor;
Conference_Titel :
Signal-Image Technology and Internet-Based Systems (SITIS), 2014 Tenth International Conference on
DOI :
10.1109/SITIS.2014.35