{"title":"Patch based descriptors for iris recognition","authors":"S. Emerich, R. Malutan, E. Lupu, László Lefkovits","doi":"10.1109/ICCP.2016.7737145","DOIUrl":null,"url":null,"abstract":"In recent years, local texture analysis methods have gained increasing attention in many areas of image processing and computer vision. The current paper deals with iris features extraction, based on dense descriptors. A dense descriptor captures the local details, pixel by pixel over the complete image. Three different techniques were employed: Local Binary Pattern, Local Phase Quantization and Differential Excitation in order to provide both spatial and frequency information. To evaluate the proposed system, experiments were performed on the UPOL database, by using a linear SVM classification scheme. The results show that the iris micro-texture patterns such as crypts, furrows or pigment spots can be well characterized by patched based descriptors.","PeriodicalId":343658,"journal":{"name":"2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)","volume":"2537 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCP.2016.7737145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In recent years, local texture analysis methods have gained increasing attention in many areas of image processing and computer vision. The current paper deals with iris features extraction, based on dense descriptors. A dense descriptor captures the local details, pixel by pixel over the complete image. Three different techniques were employed: Local Binary Pattern, Local Phase Quantization and Differential Excitation in order to provide both spatial and frequency information. To evaluate the proposed system, experiments were performed on the UPOL database, by using a linear SVM classification scheme. The results show that the iris micro-texture patterns such as crypts, furrows or pigment spots can be well characterized by patched based descriptors.