Lachi Reddy Poreddy, Harish Gannavarapu, Sai Bhaskara Pavan Kumar Valavala, Saran Babu Seeram, Sai Teja Indla
{"title":"A System which procures Attendance by using Face Recognition and Raspberry pi","authors":"Lachi Reddy Poreddy, Harish Gannavarapu, Sai Bhaskara Pavan Kumar Valavala, Saran Babu Seeram, Sai Teja Indla","doi":"10.1109/SSTEPS57475.2022.00041","DOIUrl":null,"url":null,"abstract":"It’s been a challenging task for a professor to mark attendance by using some conventional method which might have human errors. Any how we had some existing techniques to record attendance like fingerprint, RFID, and barcode. In these techniques, a big block of system needs to be setup at one way traffic which can record inflows and takes attendance. To avoid manual based attendance in our project we are using face recognition technique. This proposed system consists of 6 phases creating an application, image capturing, Segmentation of image, face detection, face recognition and comparison, updating of Attendance in database. Initially the images of the students are stored in a data base in the form of haars cascade algorithm, when we enable our raspberry pi using application it captures live class and images will be segmented, it would compare the haars cascade algorithm that was initially stored in the database. Based on this attendance will be generated in spread sheet, generated data would be mailed to the respected faculty. The main agenda of our proposed system was to take attendance with ease.","PeriodicalId":289933,"journal":{"name":"2022 International Conference on Smart and Sustainable Technologies in Energy and Power Sectors (SSTEPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Smart and Sustainable Technologies in Energy and Power Sectors (SSTEPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSTEPS57475.2022.00041","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
It’s been a challenging task for a professor to mark attendance by using some conventional method which might have human errors. Any how we had some existing techniques to record attendance like fingerprint, RFID, and barcode. In these techniques, a big block of system needs to be setup at one way traffic which can record inflows and takes attendance. To avoid manual based attendance in our project we are using face recognition technique. This proposed system consists of 6 phases creating an application, image capturing, Segmentation of image, face detection, face recognition and comparison, updating of Attendance in database. Initially the images of the students are stored in a data base in the form of haars cascade algorithm, when we enable our raspberry pi using application it captures live class and images will be segmented, it would compare the haars cascade algorithm that was initially stored in the database. Based on this attendance will be generated in spread sheet, generated data would be mailed to the respected faculty. The main agenda of our proposed system was to take attendance with ease.