M. Fernandez, Kristina Joyce E. Gob, Aubrey Rose M. Leonidas, Ron Jason J. Ravara, A. Bandala, E. Dadios
{"title":"Simultaneous face detection and recognition using Viola-Jones Algorithm and Artificial Neural Networks for identity verification","authors":"M. Fernandez, Kristina Joyce E. Gob, Aubrey Rose M. Leonidas, Ron Jason J. Ravara, A. Bandala, E. Dadios","doi":"10.1109/TENCONSPRING.2014.6863118","DOIUrl":null,"url":null,"abstract":"The study presented aims to design and develop a face recognition system. The system utilized Viola Jones Algorithm in detecting faces from a given image. Also the system used Artificial Neural Networks in recognizing faces detected from the input. Upon experimentation the system generated can recognize human faces with accuracy of 87.05%. The system performs at its best if the person is around 150cm away from the camera with an accuracy rate of 87.59%. Also, the best amount of lighting for the recognition system is at 480 lumens with an accuracy rate of 88.64%. Lastly, the system also performs at its best if the person is directly facing the camera or at 0 degrees with respect to the camera.","PeriodicalId":270495,"journal":{"name":"2014 IEEE REGION 10 SYMPOSIUM","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE REGION 10 SYMPOSIUM","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCONSPRING.2014.6863118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
Abstract
The study presented aims to design and develop a face recognition system. The system utilized Viola Jones Algorithm in detecting faces from a given image. Also the system used Artificial Neural Networks in recognizing faces detected from the input. Upon experimentation the system generated can recognize human faces with accuracy of 87.05%. The system performs at its best if the person is around 150cm away from the camera with an accuracy rate of 87.59%. Also, the best amount of lighting for the recognition system is at 480 lumens with an accuracy rate of 88.64%. Lastly, the system also performs at its best if the person is directly facing the camera or at 0 degrees with respect to the camera.