International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
A VISUAL ATTENDANCE SYSTEM USING FACE RECOGNITION Dishant Khatri, Kanishka Sharma, Dr Nidhi Sharma Dishant Khatri, Dept. of Information Technology Galgotias College of Engineering and Technology, India Kanishka Sharma, Dept. of Information Technology Galgotias College of Engineering and Technology, India Dr Nidhi Sharma, Dept. of Information Technology Galgotias College of Engineering and Technology, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The attendance system was created to ensure the decorum and discipline of the school, colleges, and universities.
There are a variety of traditional methods for recording student attendance in a class. The first is to call the roll number, and the second is to have pupils sign a sheet of paper next to their roll number. As a result, it was necessary to evolve this system in order for it to become more user friendly, less time-consuming, and efficient. This is a visual attendance system designed to help professors take attendance of the entire class without causing any disruption or wasting time. This visual attendance system can be used in any field that requires regular attendance. In addition, as the project objectives and the design criteria all met, it’s greatest to say this project is an engineering solution for all university and colleges to track and manage the attendance. Key Words: Attendance, face identification, Recognizer, OpenCV
1. INTRODUCTION Students' attendance is traditionally taken manually using an attendance sheet provided by a faculty member in class. Traditional systems were more prone to proxies, blunders, and errors. The more effective the attendance system, the higher the level of involvement and learning in class. Previously, we used tactics such as roll numbering, calling, and signing against a specific roll number. Furthermore, in a large classroom environment with distributed branches, it is extremely difficult to check whether or not authenticated students are replying one by one. Image processing has led to the development of facial recognition systems. Image processing is concerned with the extraction of necessary data from a digital image, and it plays a unique role in technological growth. It is also feasible to detect if a student is sleeping or awake during a lecture, and it can be used to ensure a student's presence during exam sessions. The presence of students may be determined by capturing their faces on a high-definition monitor video streaming service, making it extremely dependable for the computer to recognise all of the pupils in the classroom. For feature detection, the system employs a variety of methods, including image contrasts, integral pictures, colour features, and a cascade classifier. The system is evaluated in a variety of lighting settings, with diverse facial expressions, partial faces (in densely filled classes), and beards and spectacles present or absent. In the majority of the cases studied, improved accuracy (almost 100 percent) is reached. Large data sets and complex features are required for face recognition in order to uniquely identify various persons by adjusting different obstacles such as illumination, stance, and age. Facial recognition technologies have improved significantly during the last few years. In the recent decade, there has been a tremendous advancement in the field of facial recognition. Most facial recognition systems now work effectively with only a few faces in the picture. Furthermore, these methods have been tested under regulated lighting settings, with good face positions and photos that are not fuzzy. The system that is proposed for face recognition in this paper for attendance system is able to recognize multiple faces in a frame without any control on illumination, position of face. Computers may also be programmed to identify the individuality of faces, so we must programme or train the machine how to distinguish between faces based on their distinguishing characteristics. As seen below, facial recognition can be split into two categories: 1.) Verification 2.) Identification Verification is a one-on-one matching process (match or no match). The tool may be used to lock and unlock systems, phones, and other electronic devices. Identification is a technique for distinguishing an individual within a group of individuals, such as one out of N.
© 2022, IRJET
|
Impact Factor value: 7.529
|
ISO 9001:2008 Certified Journal
|
Page 2840