Ibtisam Mohammed Al-Bahri, S. Fageeri, A. Said, G. A. Sagayee
{"title":"A Comparative Study Between PCA and Sift Algorithm for Static Face Recognition","authors":"Ibtisam Mohammed Al-Bahri, S. Fageeri, A. Said, G. A. Sagayee","doi":"10.1109/ICCCEEE49695.2021.9429610","DOIUrl":null,"url":null,"abstract":"With the rapid growth in the field of information technology, peoples depend on the technology for solving many kinds of issues that can help in running on daily bases activities, as one of information security features, face recognition became one of the business intelligence methods to identify and recognize peoples in different domains, this paper compares the well-known and reputed state of arts algorithms for static face recognition such as PCA and Sift. The two algorithms start by reading image from camera and then Pre-Process the image, extracting the features, and recognize the image. Based on the experiment the results outlined that Sift algorithm achieved better performance of face recognition compared to the PCA.","PeriodicalId":359802,"journal":{"name":"2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCEEE49695.2021.9429610","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
With the rapid growth in the field of information technology, peoples depend on the technology for solving many kinds of issues that can help in running on daily bases activities, as one of information security features, face recognition became one of the business intelligence methods to identify and recognize peoples in different domains, this paper compares the well-known and reputed state of arts algorithms for static face recognition such as PCA and Sift. The two algorithms start by reading image from camera and then Pre-Process the image, extracting the features, and recognize the image. Based on the experiment the results outlined that Sift algorithm achieved better performance of face recognition compared to the PCA.