{"title":"Iris recognition using curvelet transform and accuracy maximization by particle swarm optimization","authors":"A. Ahamed, Syed Irfan Ali Meerza","doi":"10.1109/WNYISPW57858.2022.9983494","DOIUrl":null,"url":null,"abstract":"This study proposes a low complexity iris recognition technique using particle swarm optimization in the curvelet domain transformation. We utilize the standard CASIA-Iris V4 database to test the performance of our proposed method as compared to other state-of-the-art methods. The proposed method provides 99.4% accuracy in recognizing iris images. In addition, our proposed method requires 50% less computational time compared to other state-of-the-art methods.","PeriodicalId":427869,"journal":{"name":"2022 IEEE Western New York Image and Signal Processing Workshop (WNYISPW)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Western New York Image and Signal Processing Workshop (WNYISPW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WNYISPW57858.2022.9983494","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
This study proposes a low complexity iris recognition technique using particle swarm optimization in the curvelet domain transformation. We utilize the standard CASIA-Iris V4 database to test the performance of our proposed method as compared to other state-of-the-art methods. The proposed method provides 99.4% accuracy in recognizing iris images. In addition, our proposed method requires 50% less computational time compared to other state-of-the-art methods.