Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2021
|
| Online Access: | https://doi.org/10.5281/zenodo.15852246 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866901642412032000 |
|---|---|
| author | Duwal, Rukesh |
| author_facet | Duwal, Rukesh |
| contents | <p>In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Despite of having low accuracy when compared to iris recognition and fingerprint recognition, it is being widely used due to its contactless and non-invasive process. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. This system aims to build a class attendance system which uses the concept of face recognition as existing manual attendance system is time consuming and cumbersome to maintain. And there may be chances of proxy attendance. Thus, the need for this system increases. This system consists of four phases- dataset creation, face detection, face recognition, attendance updating. Dataset is created by the images of the students in class. The system is designed in TKINTER platform for GUI supported with a script of PYTHON as well as SQL database. Face detection and recognition is performed using Haar-Cascade classifier and Local Binary Pattern Histogram algorithm respectively. Faces are detected and recognized from live streaming video of the classroom. The system has output in the form of excel sheet. </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15852246 |
| institution | Zenodo |
| language | |
| publishDate | 2021 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Attendance System With Facial Recognition Using AI Duwal, Rukesh <p>In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Despite of having low accuracy when compared to iris recognition and fingerprint recognition, it is being widely used due to its contactless and non-invasive process. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. This system aims to build a class attendance system which uses the concept of face recognition as existing manual attendance system is time consuming and cumbersome to maintain. And there may be chances of proxy attendance. Thus, the need for this system increases. This system consists of four phases- dataset creation, face detection, face recognition, attendance updating. Dataset is created by the images of the students in class. The system is designed in TKINTER platform for GUI supported with a script of PYTHON as well as SQL database. Face detection and recognition is performed using Haar-Cascade classifier and Local Binary Pattern Histogram algorithm respectively. Faces are detected and recognized from live streaming video of the classroom. The system has output in the form of excel sheet. </p> |
| title | Attendance System With Facial Recognition Using AI |
| url | https://doi.org/10.5281/zenodo.15852246 |