Anis Farihan Mat Raffei, H. Asmuni, Rohayanti Hassan, R. Othman
{"title":"Analysis on Texture and Colour Based Features of Periocular for Low Resolution Colour Iris Images","authors":"Anis Farihan Mat Raffei, H. Asmuni, Rohayanti Hassan, R. Othman","doi":"10.1109/SPC.2018.8704149","DOIUrl":null,"url":null,"abstract":"The low resolution iris images in non-cooperative environment has resultant in failure to determine the eye center, limbic and pupillary boundary of the iris segmentation. Hence, a combination with periocular area is suggested to improve the accuracy of the recognition system. However, the existing periocular features extraction methods to extract the texture features can be easily affected by a background complication and depends on image size and orientation. Although some of the existing studies have combined the texture and colour features to increase the accuracy of periocular recognition, still, the method of colour feature extraction is limited to spatial information and quantization effects. This paper presents the analysis of texture and colour based features of periocular for low resolution colour iris images. Two datasets: UBIRIS.v2 and UBIPr are used and the proposed method provides robust discriminative structure features and sufficient spatial information which has increased the discriminating power.","PeriodicalId":432464,"journal":{"name":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPC.2018.8704149","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
The low resolution iris images in non-cooperative environment has resultant in failure to determine the eye center, limbic and pupillary boundary of the iris segmentation. Hence, a combination with periocular area is suggested to improve the accuracy of the recognition system. However, the existing periocular features extraction methods to extract the texture features can be easily affected by a background complication and depends on image size and orientation. Although some of the existing studies have combined the texture and colour features to increase the accuracy of periocular recognition, still, the method of colour feature extraction is limited to spatial information and quantization effects. This paper presents the analysis of texture and colour based features of periocular for low resolution colour iris images. Two datasets: UBIRIS.v2 and UBIPr are used and the proposed method provides robust discriminative structure features and sufficient spatial information which has increased the discriminating power.