Ayman A. Wazwaz, Amir O. Herbawi, Mohammad J. Teeti, Sajed Y. Hmeed
{"title":"Raspberry Pi and computers-based face detection and recognition system","authors":"Ayman A. Wazwaz, Amir O. Herbawi, Mohammad J. Teeti, Sajed Y. Hmeed","doi":"10.1109/CATA.2018.8398677","DOIUrl":null,"url":null,"abstract":"This paper aims to deploy a network that consists a group of computers connected with a microcomputer with a camera. The system takes images of people, analyze, detect and recognize human faces using image processing algorithms. The system can serve as a security system in public places like Malls, Universities, and airports. It can detect and recognize a human face in different situations and scenarios. This system implements “Boosted Cascade of Simple Features algorithm” to detect human faces. “Local Binary Pattern algorithm” to recognize these faces. Raspberry Pi is the main component connected to a camera for image capturing. All needed programs were written in python. Tests and performance analysis were done to verify the efficiency of this system.","PeriodicalId":231024,"journal":{"name":"2018 4th International Conference on Computer and Technology Applications (ICCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Computer and Technology Applications (ICCTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CATA.2018.8398677","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33
Abstract
This paper aims to deploy a network that consists a group of computers connected with a microcomputer with a camera. The system takes images of people, analyze, detect and recognize human faces using image processing algorithms. The system can serve as a security system in public places like Malls, Universities, and airports. It can detect and recognize a human face in different situations and scenarios. This system implements “Boosted Cascade of Simple Features algorithm” to detect human faces. “Local Binary Pattern algorithm” to recognize these faces. Raspberry Pi is the main component connected to a camera for image capturing. All needed programs were written in python. Tests and performance analysis were done to verify the efficiency of this system.