scholarly journals Facial Recognition on System Prototype to Verify Users using Eigenface, Viola-Jones and Haar

2021 ◽  
Vol 3 (2) ◽  
pp. 213-222
Author(s):  
Robin Robin ◽  
Aldrick Handinata ◽  
Wenripin Chandra
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Prototype System ◽  
Body Parts ◽  
Test Results ◽  
Haar Feature ◽  
System Prototype

Facial recognition is one of the most popular way to authenticate user into a system. This method is preferable considering the tendency of users for using the same password across multiple sites which made the user has already made his own account securities in vulnerable states. Using biometrics might supply solutions to solve this problem and facial recognition is one of the best biometric methods can be apply as a digital account security solution. This study to design a prototype system implementing facial recognition to verify users to measure how accurate these methods are. The method used here is Viola-Jones for face detection, Eigenface and Haar feature for face recognition from the OpenCV. The system was designed in Java. Based on the test results from the system designed, system can recognize user face with 100% accuracy if faces are shot in a well desirable condition. The system is able to recognize the user's face with various expressions including with or without glasses. However, the system has difficulty in recognizing user’s face in facing up, down, sideways position or blocked by accessories or body parts such as hands. After some experiment, it was proven that the system designed is accurate, reliable and safe enough to be implemented to digital authorization process.

scholarly journals A Web-Based Mobile Attendance System with Facial Recognition Feature

2020 ◽  
Vol 14 (05) ◽  
pp. 193
Author(s):  
Noradila Nordin ◽  
Nurul Husna Mohd Fauzi
Keyword(s):  
Face Recognition ◽  
Mobile Devices ◽  
Conventional Method ◽  
Facial Recognition ◽  
Recognition System ◽  
Web Based ◽  
Face Recognition System ◽  
The Face ◽  
System Prototype

Attendance marking in a classroom is one of the methods used to track the student’s presence in the lecture. The conventional method that is being enforced has shown to be vulnerable, inaccurate and time-consuming especially in a large classroom. It is difficult to identify absentees and proxy attendees based on the conventional attendance marking method. In order to overcome the challenges faced in the conventional method, a web-based mobile attendance system with facial recognition feature is proposed. It incorporated the existing mobile devices with a camera and the face recognition system to allow the attendance system to be used in classrooms automatically and efficiently with minor implementation requirements. The system prototype received positive responses from the volunteers who tested the system to replace the conventional attendance marking.

Implementation of Smart Attendance Monitoring Using Open-CV and Python

2019 ◽  
Vol 16 (8) ◽  
pp. 3290-3295 ◽  
Author(s):  
M. D. Anto Praveena ◽  
Mohana Krishna Eriki ◽  
Dharma Teja Enjam
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Important Task ◽  
The Face ◽  
Two Phases ◽  
Facial Contours ◽  
Feature Extraction And Matching

Uniqueness or individuality of a person is his face. In this paper, face of an individual is used for the purpose of attendance taking automatically. Maintaining attendance of a student is very important task in all the institutes to check the performance of students. Every institute has its own way for taking attendance. Some of the institutes use paper or file based approach, and some are using methods of automatic attendance taking using biometrics methods which is very time consuming process. There are many methods available for this purpose. Facial recognition may be a unambiguously distinctive or corroboratory an individual by comparison and analysing the patterns supported person’s facial contours. Facial recognition is mostly used for security purposes at so many places. This process can be divided into two phases, processing before recognition where face detection takes place, and afterwards face recognition takes place through feature extraction and matching steps. This system uses the face recognition for taking automatic attendance of students in the classroom without student’s intervention. This attendance is recorded by using a camera that captures images of students and detect the faces after which it compares and faces are detected with the database and mark the attendance for the students. Attendance sheet will be generated and message will be sent to the parents.

scholarly journals Implementing Facial Recognition by Interfacing MATLAB Along with Arduino

2021 ◽  
Vol 10 (4) ◽  
pp. 66-71
Author(s):  
E. Ramkumar ◽  
T. Guna ◽  
S.M. Dharshan ◽  
V.S. Ashok Ramanan
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Mobile Phones ◽  
Electronic Device ◽  
Facial Recognition ◽  
Residential Buildings ◽  
Biometric Authentication ◽  
Digital Cameras ◽  
Industrial Sectors ◽  
Detection Rule

Facial recognition has become one of the recent trends in attracting abundant attention within the society of social media network. The face is flat and therefore needs plenty of mathematical computations. Facial knowledge has become one in every of the foremost necessary biometric, we tend to witness it from the day-to-day gadgets like mobile phones. Every transportable electronic device currently being discharged includes a camera embedded in it. Network access management via face recognition not solely makes hackers just about not possible to steal one's "password", however conjointly will increase the user-friendliness in human-computer interaction. For the applications of videophone and conference, the help of face recognition conjointly provides an additional economical secret writing theme. Face detection technologies are employed in an oversized kind of applications like advertising, diversion, video secret writing, digital cameras, CCTV police investigation, and even in military use. Totally different algorithms are used for biometric authentication. The Kanade-Lucas-Tomasi rule makes use of abstraction common intensity transformation to direct the deep explore for the position that shows the simplest match. Another common face detection rule is that the Viola-Jones rule that's the foremost wide used face detection rule. It's employed in most digital cameras and mobile phones to notice faces. It uses cascades to notice edges just like the nose, the ears, etc. Hence, during this paper, we've got planned the Viola-Jones rule because the best one supported our application. The rule is employed within the biometric authentication of individuals and also the pictures are kept during processing. The kept information is employed for recognizing the faces and if the information matches, an impression signal is given to the controller. The MATLAB software is employed to relinquish control signals to the motor, which is employed for gap and shutting the door. The input image is fed by a digital camera and also the image is processed within MATLAB. The output is given to the external controller interfaced with MATLAB. The image process field has several sub-fields, biometric authentication is one in each of them because it gains additional quality for security functions these days. The planned system can be employed in residential buildings, malls, and industrial sectors. Thus, this technique is helpful for homemakers to be safer in their homes.

scholarly journals Face Detection & Recognition using Tensor Flow: A Review

2018 ◽  
Vol 18 ◽  
pp. 7381-7388
Author(s):  
Ishaan Chawla
Keyword(s):  
Social Media ◽  
Face Recognition ◽  
Access Control ◽  
Face Detection ◽  
Facial Recognition ◽  
Rapid Development ◽  
Standard Form ◽  
Surveillance Systems ◽  
Security Systems ◽  
Recognition Systems

Face recognition has become a popular topic of research recently due to increases in demand for security as well as the rapid development of mobile devices. There are many applications which face recognition can be applied to such as access control, identity verification, security systems, surveillance systems, and social media networks. Access control includes offices, computers, phones, ATMs, etc. Most of these forms currently do not use face recognition as the standard form of granting entry, but with advancing technologies in computers along with more refined algorithms, facial recognition is gaining some traction in replacing passwords and fingerprint scanners. Ever since the events of 9/11 there has been a more concerned emphasis on developing security systems to ensure the safety of innocent citizens. Namely in places such as airports and border crossings where identification verification is necessary, face recognition systems potentially have the ability to mitigate the risk and ultimately prevent future attacks from occurring. As for surveillance systems, the same point can be made if there are criminals on the loose. Surveillance cameras with face recognition abilities can aide in efforts of finding these individuals. Alternatively, these same surveillance systems can also help identify the whereabouts of missing persons, although this is dependent on robust facial recognition algorithms as well as a fully developed database of faces. And lastly, facial recognition has surfaced in social media applications on platforms such as Facebook which suggest users to tag friends who have been identified in pictures. It is clear that there are many applications the uses for facial recognition systems. In general, the steps to achieve this are the following: face detection, feature extraction, and lastly training a model.

Recent Progress in Human Face Detection, Tracking and Recognition

2013 ◽  
Vol 760-762 ◽  
pp. 1539-1546
Author(s):  
Xiao Ming Peng
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Image Sequences ◽  
3D Video ◽  
Range Image ◽  
Human Face ◽  
Recent Emergence ◽  
Human Face Detection ◽  
Tracking And Recognition

Facial recognition is an important research topic in biometrics and has wide applications in pattern recognition and computer vision. This paper aims at providing interested readers with recent progresses in human face detection, tracking, video-based face recognition, and 3D+2D hybrid face recognition. For this purpose, it mainly focuses on those state-of-the-arts methods and technologies that emerged in recent previous few years. Most existing methods in this area are still-image based which do not utilize motion information; whereas most video-based methods work only in 2D video sequences, which are subject to pose and illumination variations. The recent emergence of 3D video cameras capable of producing range image sequences and corresponding texture image sequences simultaneously allows for the possibility of facial recognition in a 3D+2D video-based scenario. In view of this fact, a scheme of face detection, tracking and recognition process in 3D video-based manner is also proposed in this paper with further concerns addressed.

scholarly journals Design of Facial Recognition System Based on Visual Communication Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xuhui Fu
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Visual Communication ◽  
Facial Recognition ◽  
Recognition System ◽  
Image Capture ◽  
Hardware System ◽  
Face Recognition System ◽  
The Face ◽  
Facial Recognition System

At present, facial recognition technology is a very cutting-edge science and technology, and it has now become a very hot research branch. In this research, first, the thesis first summarized the research status of facial recognition technology and related technologies based on visual communication and then used the OpenCV open source vision library based on the design of the system architecture and the installed system hardware conditions. The face detection program and the image matching program are realized, and the complete face recognition system based on OpenCV is realized. The experimental results show that the hardware system built by the software can realize the image capture and online recognition. The applied objects are testers. In general, the OpenCV-based face recognition system for testers can reliably, stably, and quickly realize face detection and recognition in this situation. Facial recognition works well.

scholarly journals Face recognition for automatic vehicle ignition based on Raspberry Pi

2020 ◽  
Vol 1 (2) ◽  
pp. 53-68
Author(s):  
Alex V. Nuñez ◽  
Liliana N. Nuñez
Keyword(s):  
Computer Vision ◽  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Data Gathering ◽  
Software Component ◽  
Security System ◽  
Raspberry Pi ◽  
Hardware Platform ◽  
And Training

In this project a facial recognition application for automatic vehicle ignition is developed. This application is built using a Raspberry Pi as the hardware platform and the OpenCV library for computer vision as the software component. In this research the different methods for automobile security are analyzed, as well as, the different methods used to perform face recognition.  The main goal of this application is to enhance the security system of the vehicle, allowing to ignite the vehicle only by register users. To achieve this goal three main processes are carried out, face detection, data gathering, and training the system to grant access through face recognition.

scholarly journals Design of Intelligent Facial Recognition System using AI for Surveillance Application

2020 ◽  
pp. 346-356
Author(s):  
Syed Ibrahim ◽  
Syed Nahid Suleman ◽  
Manikanta Suthapalli ◽  
Abhishek Sharma ◽  
Shilpa K S
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Facial Recognition ◽  
Recognition System ◽  
Security System ◽  
Software Module ◽  
High Security ◽  
Trained Staff ◽  
Facial Recognition System ◽  
Surveillance Application

Organizations presently continue to encounter significant security concerns; consequently, they require much particularly trained staff to achieve the coveted protection. This staff performs blunders that may affect the extent of security. A suggested solution to the matter mentioned above is a Face Recognition Security System, which can monitor and identify trespassers to blocked or high-security areas and assist in overcoming the margin of manual human oversight. This system is comprised of two halves: the hardware part and the software part. The hardware module incorporates a camera, while the software module includes software that uses face-detection and face-recognition algorithms. If a person infiltrates the confine in question, a set of snaps are captured by the camera and dispatched to the software to be examined/identified and equated with an existent database of trusted people. An alert is conveyed to the user if the infiltrator is not recognized.

scholarly journals A Conceptual Model for Automated Attendance Marking System using Facial Recognition

2020 ◽  
Vol 8 (6) ◽  
pp. 4271`-4273
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Facial Recognition ◽  
Texture Feature ◽  
Extraction Process ◽  
Directional Pattern ◽  
The Face ◽  
Contrast Information

The project represents an automated attendance system based on face recognition using discriminative local binary pattern and local directional pattern descriptors. The proposed system involves face detection, Features extraction and matching. The face detection is to detect faces based on Viola Jones algorithm . In feature extraction stage, the discriminative local binary pattern is used for different object texture feature extraction process. The proposed method with new features retain the contrast information of image patterns. The Facial recognition (or face recognition) is a type of biometric application that can identify a specific individual in a digital image by analyzing and comparing patterns based on the data stored in database. Smart attendance is a real time face recognition used for handling day to day activities of the employees and students. In manual attendance system there are several issues like fake attendance and mistakenly marked absent by carelessness of the faculty/teachers/lectures. In order to overcome these problems we are using this smart attendance system. Here multiple faces are detected and recognized with trained with various features. The automated face attendance marking system gives accurate performance.

scholarly journals Class Attendance Management System using Facial Recognition

2020 ◽  
Vol 32 ◽  
pp. 02001
Author(s):  
Clyde Gomes ◽  
Sagar Chanchal ◽  
Tanmay Desai ◽  
Dipti Jadhav
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Radio Frequency Identification ◽  
Management System ◽  
Facial Recognition ◽  
Automated System ◽  
Time Saving ◽  
Recognition Algorithms ◽  
Conventional Methods ◽  
Identification Tags

Attendance marking in a classroom during a lecture is not only a onerous task but also a time consuming one at that. Due to an unusually high number of students present during the lecture there will always be a probability of proxy attendance(s).Attendance marking with conventional methods has been an area of challenge. The growing need of efficient and automatic techniques of marking attendance is a growing challenge in the area of face recognition. In recent years, the problem of automatic attendance marking has been widely addressed through the use of standard biometrics like fingerprint and Radio frequency Identification tags etc., However,these techniques lack the element of reliability. In this proposed project an automated attendance marking and management system is proposed by making use of face detection and recognition algorithms. Instead of using the conventional methods, this proposed system aims to develop an automated system that records the student’s attendance by using facial recognition technology. The main objective of this work is to make the attendance marking and management system efficient, time saving, simple and easy. Here faces will be recognized using face recognition algorithms. The processed image will then be compared against the existing stored record and then attendance is marked in the database accordingly. Compared to existing system traditional attendance marking system, this system reduces the workload of people. This proposed system will be implemented with 4 phases such as Image Capturing, Segmentation of group image and Face Detection, Face comparison and Recognition, Updating of Attendance in database.

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