This project is about the development of Robust Attendance System Based on Smart Face Identification RASFI. To record attendance of students, there are several ways which can be used. One approach is the marking attendance on paper and other one is by calling students? name and updating on
Robust Attendance System Based on Smart Face Identification RASFI
This project is about the development of Robust Attendance System Based on Smart Face Identification RASFI. To record attendance of students, there are several ways which can be used. One approach is the marking attendance on paper and other one is by calling students’ name and updating on portals. All the process has several shortcomings, such as requiring a long time to mark attendance and breaking the tempo of the lecture, but the most important of all of these is that all the processes are manual. To counter this problem fully automatic and accurate attendance system was needed to be designed. The main objective of designing this robust and automated attendance system is to mark attendance of students automatically while aiming to achieve the maximum accuracy. Design of this project has been divided in to several phases. Firstly, a camera installed in the class is used to gather different video feeds. In the next phase detection algorithms are implemented for the detection of individual faces of students in the image. In the next part the low-quality images are passed through an algorithm for the enhancement of quality. In the next phase recognition algorithms are used for recognition and identifications purposes. Lastly the attendance of recognized faces has been marked. The video feeds are taken multiple times i.e. at the start of the class and then at the end of class to ensure that the student has attended the whole class. This project can be used in all of such insitutions where attendace marking is crucial and a must to do thing.
The main objective of this project is to design such an algorithm that can mark the attendance of the class autonoumously with maximum accuracy. Old method of marking attendance occupies time of the lecture, time saved due to this technique can be consumed to cover extra contents.
Design of this project has been divided in to several phases. Firstly, a camera installed in the class is used to gather different video feeds. In the next phase detection algorithms are implemented for the detection of individual faces of students in the image. In the next part the low-quality images are passed through an algorithm for the enhancement of quality. In the next phase recognition algorithms are used for recognition and identifications purposes. Lastly the attendance of recognized faces has been marked.
This project can be used in any organization or institution such as schools, colleges, universities, etc. where attendance marking is an important and a must- to-do thing because it results either in the success or failure of any institute or organization. Moreover this project can be used in offices, banks, stores and to all those organizations where attendece marking is crucial.
This project's main operation will be a software in which a video camera is utilized to collect several photographs of a class throughout its usual time. These photographs have several faces since they include practically every student in the class. These photos are processed using a face detection algorithm, which detects and separates the faces of all students in the class. If the identified faces are not aligned or straight, they are pre-processed using a pre-processing algorithm whose purpose it is to realign and to straight the unaligned faces. After pre-processing, the next stage is to pass the pre-processed faces from a quality enhacment algorithm which will refine the quality of the faces. These enhanced faces will be passed to a model that is sophisticated enough to recognize whose face this is. When a face is recognized, it indicates that the matching student is present, and therefore that student's attendance is recorded 'Present.'
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| GeForce GTX 1650 Ti | Equipment | 1 | 69000 | 69000 |
| Total in (Rs) | 69000 |
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