The implementation of eigenface algorithm for face recognition in attendance system

Kurniawan, Vincentius; Wicaksana, Arya; Prasetiyowati, Maria Irmina

doi:10.1109/conmedia.2017.8266042

Cited by 8 publications

(7 citation statements)

References 6 publications

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“…In addition, it also helps in improving efficiency and reduces the educator's burden as the attendance is marked automatically. Besides marking attendance, some systems can determine the students' seating positions [15,[27][28][29] while the other classifies gender of students using facial features [30]. There are several aspects and specification to be considered in developing this type of system.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

“…With regard to the attendance system based on face recognition, the minimum number of templates is five [31] while the maximum value is 1000 [59]. Furthermore, the numbers of templates for other face recognition systems are below sixty templates [57,60,61] with most of them having values in between six and twenty-one [29,33,46,53,[62][63][64][65][66][67][68][69]. Next is the authentication stage that involved matching captured biometric data with those templates in the database.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

“…Cloud servers hosted over the internet were used to store attendance information which can be accessed remotely and at any time [62,69,116]. Additionally, web servers were used in some attendance systems [29,46]. González-Agulla et al [72] along with Gadhave and Kore [42] stored and managed the attendance activities with modular object-oriented dynamic learning environment (Moodle) server which is an online management system.…”

Section: Database Storagementioning

confidence: 99%

“…and face [29,46,62,69,70,116] Fingerprint [35,[42][43][44]82] Fingerprint [32] Iris [76]; fingerprint [43,54] Fingerprint [38,39,48,82] Fingerprint [42,75,88] 19…”

mentioning

confidence: 99%

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Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements

Hoo

Ibrahim

2019

Journal of Sensors

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The application of biometric recognition in personal authentication enables the growth of this technology to be employed in various domains. The implementation of biometric recognition systems can be based on physical or behavioral characteristics, such as the iris, voice, fingerprint, and face. Currently, the attendance tracking system based on biometric recognition for education sectors is still underutilized, thus providing a good opportunity to carry out interesting research in this area. As evidenced in a typical classroom, educators tend to take the attendance of their students by using conventional methods such as by calling out names or signing off an attendance sheet. Yet, these types of methods are proved to be time consuming and tedious, and sometimes, fraud occurs. As a result, significant progress had been made to mark attendance automatically by making use of biometric recognition. This progress enables a new and more advanced biometric-based attendance system being developed over the past ten years. The setting-up of biometric-based attendance systems requires both software and hardware components. Since the software and hardware sections are too broad to be discussed in one paper, this literature survey only provides an overview of the types of hardware used. Emphasis is then placed on the microcontroller platform, biometric sensor, communication channel, database storage, and other components in order to assist future researchers in designing the hardware part of biometric-based attendance systems.

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Section: Journal Of Sensorsmentioning

confidence: 99%

Section: Journal Of Sensorsmentioning

confidence: 99%

Section: Database Storagementioning

confidence: 99%

“…and face [29,46,62,69,70,116] Fingerprint [35,[42][43][44]82] Fingerprint [32] Iris [76]; fingerprint [43,54] Fingerprint [38,39,48,82] Fingerprint [42,75,88] 19…”

mentioning

confidence: 99%

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Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements

Hoo

Ibrahim

2019

Journal of Sensors

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“…PCA allots a specific weight to each face to compare with the Euclidean distance. The Discrete Cosine Transform (DCT) [17] [19] is another variation to eigenfaces which has an advantage of recognizing the face at deferent variations in illumination [20]. All of the face recognition algorithms/techniques are based on the calculation of a set of geometrical features from the picture of a face.…”

mentioning

confidence: 99%

Student Attendance Management System using Principal Component Analysis Method

2020

IJITEE

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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.

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Labeling Algorithm and Fully Connected Neural Network for Automated Number Plate Recognition System

Alexander

Wicaksana

Iswari

2019

Applied Computing and Information Technology

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The implementation of eigenface algorithm for face recognition in attendance system

Cited by 8 publications

References 6 publications

Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements

Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements

Student Attendance Management System using Principal Component Analysis Method

Labeling Algorithm and Fully Connected Neural Network for Automated Number Plate Recognition System

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