Ramadan Gad, A. El-Sayed, N. El-Fishawy, M. Zorkany
{"title":"Iris Template Localization over Internet of Things (IoT)","authors":"Ramadan Gad, A. El-Sayed, N. El-Fishawy, M. Zorkany","doi":"10.21608/mjeer.2019.62662","DOIUrl":null,"url":null,"abstract":"Internet of Things (IoT) is growing vastly and survive technology.So; it needs authentication solutions (as iris recognition) to bringsafety, and convenience in data and network sharing in the internetof things era. Iris segmentation is most critical stage in the irisrecognition system. Some challenges to localize iris such asocclusion by eyelids, eyelashes, and corneal or specular reflection.This paper proposes, a modified algorithm based on maskingtechnique; to localize iris. It solves the limitation of the iris data lossand inconsistencies factors, for capturing conditions and differentresolution images. This method gives satisfactory results in factorsof accuracy and execution time to be used over IoT. Thesegmentation success rate is more than 99.545(%), and executiontime in worst case 0.758 (sec).The obtained results improve theefficiency of the proposed iris recognition method and improve IoTsecurity and authentication.","PeriodicalId":218019,"journal":{"name":"Menoufia Journal of Electronic Engineering Research","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Menoufia Journal of Electronic Engineering Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21608/mjeer.2019.62662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Internet of Things (IoT) is growing vastly and survive technology.So; it needs authentication solutions (as iris recognition) to bringsafety, and convenience in data and network sharing in the internetof things era. Iris segmentation is most critical stage in the irisrecognition system. Some challenges to localize iris such asocclusion by eyelids, eyelashes, and corneal or specular reflection.This paper proposes, a modified algorithm based on maskingtechnique; to localize iris. It solves the limitation of the iris data lossand inconsistencies factors, for capturing conditions and differentresolution images. This method gives satisfactory results in factorsof accuracy and execution time to be used over IoT. Thesegmentation success rate is more than 99.545(%), and executiontime in worst case 0.758 (sec).The obtained results improve theefficiency of the proposed iris recognition method and improve IoTsecurity and authentication.