IEEE Trans Image Process - Unified framework for automated iris segmentation using distantly acquired face images.

Tópicos

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Resumo

Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.

Resumo Limpo

remot human identif use iri biometr high civilian surveil applic success requir develop robust segment algorithm automat extract iri region paper present new iri segment framework can robust segment iri imag acquir use near infrar visibl illumin propos approach exploit multipl higher order local pixel depend robust classifi eye region pixel iri noniri region face eye detect modul incorpor unifi framework automat provid local eye region facial imag iri segment develop robust postprocess oper algorithm effect mitig noisi pixel caus misclassif experiment result present paper suggest signific improv averag segment error previous propos approach ie ubirisv frgc casiav atadist databas respect use propos approach also ascertain recognit experi three differ public avail databas

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