automatic attendance scheme using face recognition system
M. GOWTHAM,U. MARIA LIVIN,M. NAVANEETHAKRISHNAN, M.E., Ph.D.,
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 30 March,2021 Pages:1453-1458
Abstract
Face detection can be regarded as a specific case of object-class detection. In object- class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. A reliable face-detection approach based on the genetic algorithm and the eigen-face technique: Firstly, the possible human eye regions are detected by testing all the valley regions in the gray- level image. Then the genetic algorithm is used to generate all the possible face regions which include the eyebrows, the iris, the nostril and the mouth corners. After a number of iterations, all the face candidates with a high fitness value are selected for further verification. At this stage, the face symmetry is measured and the existence of the different facial features is verified for each face candidate.
Kewords
GUI – Graphical User Interface, API – Application Programming Interface, CV – Computer Vision.
Reference
[1]: Refik Samet, Muhammed Tanriverdi, “Face Recognition-Based Mobile Automatic Classroom Attendance Management System” in ICASSP 2017. [2]: Bhattacharya, Gowtham Sandeep Nainala, Prosenjit Das, “Smart Attendance Monitoring System (SAMS): A Face Recognition based Attendance System for Classroom Environment” in ICECA 2018. [3]: Huimin Zhang, Xinlei Feng, Sujatha Krishnamoorthy,“ Cloud-Based Class Attendance Record System ” in ICTSS 2019. [4]: Sharma, Karthikeyan Shanmuga Sundaram, Sathees Kumar Ramasamy, “A Conceptual Model for Automated Attendance Marking System Using Facial Recognition” in ICACT 2019.
