click here to download the abstract project of face detection
At datapro, we provide final year projects with source code in python for computer science students in Hyderabad, Visakhapatnam.
ABSTRACT
We provided the face detection project with python code. Smart Attendance using Real-Time Face Recognition is a real-world solution which comes with day to day activities of handling student attendance system. Face recognition-based system is a process of recognizing the students face by using face biometrics. The purpose of developing this system is to computerize the traditional way of taking attendance. It consumes a lot of time for a teacher when it
is done manually, but this system helps in reducing the time taken for the entire process by using face detection. This system helps in resolving the issue of fake attendance & proxies and helps in regulating the process. The concept of face recognition is to give a computer system the ability of finding and recognizing human faces fast and precisely in images. The face recognition is an integral part of biometrics. In biometrics, basic traits of human are matched to the existing data. Facial features are extracted and implemented through algorithms, which are efficient and some modifications are done to improve the existing algorithm models.
Keywords: Smart Attendance, Face Recognition, Face Detection, Attendance, Facial Features
INTRODUCTION
An Attendance Management System which is developed using bio- metrics,in our case face,generally consists of Database development, Face detection, Pre-processing, Feature extraction and Face Recognition. The subsequent sections in this paper are literature survey, detailed description of various stages in the proposed model, results and conclusions and scope for improvement. Automated ttendance System (AAS) is a process to automatically estimate the presence or the absence of the student in the classroom by using face recognition technology. It is also possible to recognize whether the student is sleeping or awake during the lecture and it can also be implemented in the exam sessions to ensure the presence of the student. The presence of the students can be determined by capturing their faces on to a high-definition monitor video streaming service, so it becomes highly reliable for the machine to understand the presence of all the students in the classroom. The two common Human Face Recognition techniques are,
Feature-based approach
Brightness-based approach.
The Feature-based approach also known as local face recognition system, used in pointing the key features of the face like eyes, ears, nose, mouth, edges, etc., whereas the brightnessbased approach also termed as the global face recognition system, used in recognizing all the parts of the image.
The main objective of this project is to develop face recognition based automated student attendance system. In order to achieve better performance, the test images and training images of this proposed approach are limited to frontal and upright facial images that consist of a single face only. The test images and training images have to be captured by using the same device to ensure no quality difference. In addition, the students have to register in the database to be recognized. The enrolment can be done on the spot through the user-friendly interface
