scholarly journals Attendance Management System using Google Facenet for Facial Recognition

2021 ◽  
Vol 9 (VI) ◽  
pp. 5029-5036
Author(s):  
Rakesh Duggempudi
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Open Source ◽  
Management System ◽  
Facial Recognition ◽  
Cost Effective ◽  
Source Image ◽  
Student Attendance ◽  
Manual Work ◽  
View Update

Attendance management system is a required tool for attaining attendance in any habitat where attendance is essential. Yet, many of the available techniques consume time, are invasive and it demands manual work from the users. This research is directed at building a less invasive, cost effective and more efficient automated student attendance management system using face recognition that leverages on OpenCV functions for facial recognition. The system provides a GUI for marking attendance. It provides an interface for updating attendance using facial recognition libraries of OpenCV. The system stores attendance in a database which is maintained by the administrator. The administrator can view, update, and change the attendance of the students. The students can view and update their attendance. The system is developed on Open-Source image processing library and the interface is developed using Python Tkinter module. The Tkinter module is an open-source module by which we can develop GUI screens hence, it is not software dependent nor vendor hardware. The OpenCV module used for image processing is interfaced using python.

scholarly journals Student Attendance Management System using Principal Component Analysis Method

2020 ◽  
Vol 9 (4S2) ◽  
pp. 9-15
Keyword(s):  
Management System ◽  
Iris Recognition ◽  
Principal Component ◽  
Cost Effective ◽  
Analysis Method ◽  
Academic Institutions ◽  
Student Attendance ◽  
Eigen Values ◽  
Cost Effective Technique ◽  
Day By Day

Attendance taking and maintaining is a tedious job in the academic institutions where the time of class is restricted. The manual attendance i.e., roll call or paper-based signature systems usually consumes more time and error prone and also possibility of recording proxy attendance is more. Attendance is one of the criteria in considering students’ eligibility for attending the external examinations and also for the promotion to the next semester / year, where these kinds of problems may cause severe effect on the academic institutions. As the strength of students in a class is increasing day by day; monitoring, awarding and maintenance of attendance has becoming a challenge for the academic institutions. As a solution, attendance can be recorded using anyone of the existing biometric techniques like fingerprinting, iris recognition, signature, face recognition etc. Face identification is the best method among all the earlier mentioned methods for implementing in the academic institutions as it does not require human intervention and it is a cost-effective technique. A novel student attendance recording and management system using a MATLAB application, LabVIEW, Camera interface and GSM is proposed in this paper. Students’ faces will be captured with the help of a camera connected to a computer and Eigen values of the captured images will be detected with the help of MATLAB executed by LabVIEW Mathscript node. LabVIEW, a graphical programming environment is adopted for acquiring face, processing and authenticating the student once the match is found. Authenticated student attendance will be updated, and a message will be sent with the help of GSM module interface to myRIO. Proposed system replaces the manual attendance system which improves the performance of existing system.

Image Processing using Open Source Tools and their Implementation in the Analysis of Complex Microstructures

2021 ◽  
Vol 58 (8) ◽  
pp. 484-506
Author(s):  
U. P. Nayak ◽  
M. Müller ◽  
D. Britz ◽  
M.A. Guitar ◽  
F. Mücklich
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
User Interface ◽  
Open Source ◽  
Microstructural Analysis ◽  
Microstructural Characterization ◽  
Source Image ◽  
Versatile Tool ◽  
Processing Software ◽  
Image Processing Software

Abstract Considering the dependance of materials’ properties on the microstructure, it is imperative to carry out a thorough microstructural characterization and analysis to bolster its development. This article is aimed to inform the users about the implementation of FIJI, an open source image processing software for image segmentation and quantitative microstructural analysis. The rapid advancement of computer technology in the past years has made it possible to swiftly segment and analyze hundreds of micrographs reducing hours’ worth of analysis time to a mere matter of minutes. This has led to the availability of several commercial image processing software programs primarily aimed at relatively inexperienced users. Despite the advantages like ‘one-click solutions’ offered by commercial software, the high licensing cost limits its widespread use in the metallographic community. Open-source platforms on the other hand, are free and easily available although rudimentary knowledge of the user-interface is a pre-requisite. In particular, the software FIJI has distinguished itself as a versatile tool, since it provides suitable extensions from image processing to segmentation to quantitative stereology and is continuously developed by a large user community. This article aims to introduce the FIJI program by familiarizing the user with its graphical user-interface and providing a sequential methodology to carry out image segmentation and quantitative microstructural analysis.

Accessing select properties of the electron with ImageJ: an open-source image-processing paradigm

2013 ◽  
Vol 35 (1) ◽  
pp. 015011 ◽  
Author(s):  
Junaid Alam ◽  
Amrozia Shaheen ◽  
Muhammad Sabieh Anwar
Keyword(s):  
Image Processing ◽  
Open Source ◽  
Source Image

scholarly journals Comparative analysis of selected facial recognition algorithms

2020 ◽  
Vol 39 (3) ◽  
pp. 896-904
Author(s):  
J.A. Popoola ◽  
C.O. Yinka-Banjo
Keyword(s):  
Face Recognition ◽  
Comparative Analysis ◽  
Facial Recognition ◽  
Research Work ◽  
Cost Effective ◽  
Facial Symmetry ◽  
Face Matching ◽  
Computer Based ◽  
Haar Cascade ◽  
Detection And Recognition

Systems and applications embedded with facial detection and recognition capabilities are founded on the notion that there are differences in face structures among individuals, and as such, we can perform face-matching using the facial symmetry. A widely used application of facial detection and recognition is in security. It is important that the images be processed correctly for computer-based facial recognition, hence, the usage of efficient, cost-effective algorithms and a robust database. This research work puts these measures into consideration and attempts to determine a cost-effective and reliable algorithm out of three algorithms examined. Keywords: Haar-Cascade, PCA, Eigenfaces, Fisherfaces, LBPH, Face Recognition.

scholarly journals Face Recognition Based on Statistical Texture Features

2021 ◽  
Vol 7 (1) ◽  
pp. 10-15
Author(s):  
Lama Akram Ibrahim ◽  
Nasser Nasser ◽  
Majd Ali
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Face Recognition ◽  
Processing Time ◽  
Facial Recognition ◽  
Texture Features ◽  
Memory Consumption ◽  
Methods And Techniques ◽  
Recognition Systems ◽  
Occurrence Matrix

Facial recognition has attracted the attention of researchers and has been one of the most prominent topics in the fields of image processing and pattern recognition since 1990. This resulted in a very large number of recognition methods and techniques with the aim of increasing the accuracy and robustness of existing systems. Many techniques have been developed to address the challenges and reliable recognition systems have been reached but require considerable processing time, suffer from high memory consumption and are relatively complex. The focus of this paper is on extracting subset of descriptors (less correlated and less calculations) from the co-occurrence matrix with the goal of enhancing the performance of Haralick’s descriptors. Improvements are achieved by adding the image pre-processing and selecting the proper method according to the database problem and by extracting features from image local regions.

scholarly journals ASSAS: An automatic smart students attendance system based on normalized cross-correlation

2021 ◽  
Vol 10 (2) ◽  
pp. 732-741
Author(s):  
Ruaa H. Ali Al-Mallah ◽  
Dheyaa Alhelal ◽  
Razan Abdulhammed
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Human Being ◽  
Roll Call ◽  
Student Attendance ◽  
Normalized Cross Correlation ◽  
Two Phases ◽  
Cross Correlation Technique

A smart student attendance system (SSAS) is presented in this paper. The system is divided into two phases: hardware and software. The Hardware phase is implemented based on Arduino's camera while the software phase is achieved by using image processing with face recognition depended on the cross-correlation technique. In comparison with traditional attendance systems, roll call, and sign-in sheet, the proposed system is faster and more reliable (because there is no action needed by a human being who by its nature makes mistakes). At the same time, it is cheaper when compared with other automatic attendance systems. The proposed system provides a faster, cheaper and reachable system for an automatic smart student attendance that monitors and generates attendance report automatically.

scholarly journals Face recognition attendance system using Local Binary Pattern (LBP)

2019 ◽  
Vol 8 (1) ◽  
pp. 239-245 ◽  
Author(s):  
Shamsul J. Elias ◽  
Shahirah Mohamed Hatim ◽  
Nur Anisah Hassan ◽  
Lily Marlia Abd Latif ◽  
R. Badlishah Ahmad ◽  
...  
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Recognition System ◽  
Automated System ◽  
Student Attendance ◽  
Recognition Method ◽  
Face Recognition System ◽  
The Face

Attendance is important for university students. However, generic way of taking attendance in universities may include various problems. Hence, a face recognition system for attendance taking is one way to combat the problem. This paper will present an automated system that will automatically saves student’s attendance into the database using face recognition method. The paper will elaborate on student attendance system, image processing, face detection and face recognition. The face detection part will be done by using viola-jones algorithm method while the face recognition part will be carried on by using local binary pattern (LBP) method. The system will ensure that the attendance taking process will be faster and more accurate.

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