Cerine Tafran, Mohamad El-Abed, Islam Elkabani, Ziad Osman
{"title":"A No-Reference Image Quality Assessment For Detecting Illumination Alteration","authors":"Cerine Tafran, Mohamad El-Abed, Islam Elkabani, Ziad Osman","doi":"10.1109/IACS.2019.8809123","DOIUrl":null,"url":null,"abstract":"The Quality assessment of a face image is a topic of great interest for biometric applications where images with bad samples decrease the system performance and increase authentication errors, especially in biometric passport applications that use only a single image for enrollment. Thus, in order to have a useful biometric authentication system, the quality of the biometric sample images must be controlled. This paper presents a no-reference quality assessment method which detects the illumination problem using Symmetric Based Features along with BLIINDS Based Features. The experimental results on the AR database recorded an accuracy of 90.3 % by using Stochastic Gradient Descent (SGD) classifier.","PeriodicalId":225697,"journal":{"name":"2019 10th International Conference on Information and Communication Systems (ICICS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 10th International Conference on Information and Communication Systems (ICICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IACS.2019.8809123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The Quality assessment of a face image is a topic of great interest for biometric applications where images with bad samples decrease the system performance and increase authentication errors, especially in biometric passport applications that use only a single image for enrollment. Thus, in order to have a useful biometric authentication system, the quality of the biometric sample images must be controlled. This paper presents a no-reference quality assessment method which detects the illumination problem using Symmetric Based Features along with BLIINDS Based Features. The experimental results on the AR database recorded an accuracy of 90.3 % by using Stochastic Gradient Descent (SGD) classifier.