Bothaina F. Gargoum, A. Lawgali, Abdalla Mohamed A. E.
{"title":"Utilizing Ear Biometrics for Individual Identifications Using HOG and LBP","authors":"Bothaina F. Gargoum, A. Lawgali, Abdalla Mohamed A. E.","doi":"10.1109/ICEMIS56295.2022.9914344","DOIUrl":null,"url":null,"abstract":"The demand for more secure authentication has increased on several occasions. Exploiting biometrics in various forms, such as face, voice, handwriting, and gait recognition, is a reliable method for authentication. Recently, the analysis of ear images as a biometric method has become a robust identification method. This paper aims to utilize two different techniques of feature extraction: histograms of oriented gradients and local binary patterns to extract the desired features. Whereas principal component analysis is used to reduce the space of the feature dimensionality. For classification, linear discriminant analysis is used. The proposed technique is applied to the images of the (IIT Delhi-I) database. The proposed method has yielded good achievements compared to other studies.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Engineering & MIS (ICEMIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMIS56295.2022.9914344","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 demand for more secure authentication has increased on several occasions. Exploiting biometrics in various forms, such as face, voice, handwriting, and gait recognition, is a reliable method for authentication. Recently, the analysis of ear images as a biometric method has become a robust identification method. This paper aims to utilize two different techniques of feature extraction: histograms of oriented gradients and local binary patterns to extract the desired features. Whereas principal component analysis is used to reduce the space of the feature dimensionality. For classification, linear discriminant analysis is used. The proposed technique is applied to the images of the (IIT Delhi-I) database. The proposed method has yielded good achievements compared to other studies.