V. R. K. Rao, C. A. H. Puwakpitiyage, Dalia Abdulkareem Shafiq, Farhana Islam, D. Handayani, Hamwira Yacoob, T. Mantoro
{"title":"Design and Development of Facial Recognitionbased Library Management System (FRLMS)","authors":"V. R. K. Rao, C. A. H. Puwakpitiyage, Dalia Abdulkareem Shafiq, Farhana Islam, D. Handayani, Hamwira Yacoob, T. Mantoro","doi":"10.1109/ICCED.2018.00032","DOIUrl":null,"url":null,"abstract":"In this paper we propose a facial recognitionbased library management system namely Facial Recognition based Library Management System (FRLMS). This system aims to improve the user experience on library authentication process through facial recognition algorithm. This process would be simple and efficient as the authentication process is performed seamlessly. For the purpose of this study, feature extraction and image classification are obtained using OpenCV and TensorFlow, where the average recognition accuracy reaches up to 92.15%.","PeriodicalId":166437,"journal":{"name":"2018 International Conference on Computing, Engineering, and Design (ICCED)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computing, Engineering, and Design (ICCED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCED.2018.00032","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
In this paper we propose a facial recognitionbased library management system namely Facial Recognition based Library Management System (FRLMS). This system aims to improve the user experience on library authentication process through facial recognition algorithm. This process would be simple and efficient as the authentication process is performed seamlessly. For the purpose of this study, feature extraction and image classification are obtained using OpenCV and TensorFlow, where the average recognition accuracy reaches up to 92.15%.