Design and implementation of iris recognition based attendance management system

Khatun, Amena; Haque, Aminul; Ahmed, Sharmin; Rahman, Mohammad Mahfujur

doi:10.1109/iceeict.2015.7307458

Cited by 38 publications

(16 citation statements)

References 5 publications

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“…From [8], [9] and [10], it is clear that in these system the scanners read the basic elemental biometric data their systems rely on for e.g., segments from fingerprints, iris scans or others. These systems use the fact that humans have a built in uniqueness in their fingerprints and iris and take advantage of that to ensure that only the correct student is marked attended.…”

Section: 1biometric Basedmentioning

confidence: 99%

Quick Response (QR) Code based Attendance Marking System

Shah¹

2020

IJCA

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Every classroom/lab/workshop has an attendance tracking system in them. Currently the ways in which one can take such attendance/presence marking is via manual calling of IDs (roll numbers in case of universities), fingerprint scanners or face detection mechanisms. But all these either require an infrastructure (scanners) or are too tedious. This paper puts forward a new technique of marking the attendance of students. It uses QR code mechanism, which is very common in payments and shipment tracking today, to mark attendance or presence. General TermsFaculty: The entity willing to register the attendance of students.Student: The entity to be marked attended/present at some place typically classroom, lab, workshops, and community sessions KeywordsAttendance decentralized QR-code on-demand-server

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Section: 1biometric Basedmentioning

confidence: 99%

Quick Response (QR) Code based Attendance Marking System

Shah¹

2020

IJCA

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“…For the iris-based attendance system, Teh and Mohamed [96] and Khatun et al [97] implemented their system using a webcam. In terms of system design, Teh and Mohamed [96] installed the webcam inside a box while Khatun et al [97] attached the webcam above a laptop. However, the system by Teh and Mohamed [96] caters to low resolution iris image captured through a webcam.…”

Section: Biometric Sensormentioning

confidence: 99%

“…However, the system by Teh and Mohamed [96] caters to low resolution iris image captured through a webcam. There is no information provided by the authors [76,96,97] regarding the model of webcams or sensors used; thus, comparison between this equipment cannot be made. Generally, the preference of using a webcam in an iris-based attendance system is due to lower cost and acceptable image quality as a whole.…”

Section: Biometric Sensormentioning

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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“…The facial recognition has great problem due to the fact that the human faces changes over time due to growth development in human nature. The fingerprint unlike the facial recognition does not change for as long as we leave however face setback such as the need for the authenticated individual to scan his or her hand to the scanning device, this make it difficult to authenticate an individual without his or her knowledge, sometimes the scanning device maybe dirty [7]. The identified problems make iris recognition an alternative as the best biometric authentication; iris is neither affected by age nor requires an individual to have a contact with its scanning device Presently, iris recognition methods can work very well with frontal-looking and high-quality images.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Iris Partial Recognition based on Legendre Wavelet Filter

Danlami¹,

Jamel²,

Ramli³

et al. 2019

IJACSA

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An increasing need for biometrics recognition system has grown substantially to address the issues of recognition and identification especially in highly dense areas such as airport, train stations and for financial transaction. Evidences of these can be seen in some airports and also the implementation of these technologies in our mobile phones. Among the most popular biometric technologies include facial, fingerprints and iris recognition. The iris recognition is considered by many researchers to be the most accurate and reliable form of biometric recognition, because iris can neither be surgically operated with a chance of losing slight nor change due to ageing. However, presently most iris recognition system available can only recognize iris image with frontal-looking and high-quality images. Angular image and partially capture image cannot be authenticated with existing method of iris recognition. This research investigates the possibility of developing a framework for recognition partially captured iris image. The research also adopts the Legendre wavelet filter for the iris feature extraction. Selected iris images from CASIA, UBIRIS and MMU database were used to test the accuracy of the introduced framework. A threshold for the minimum iris image required was established.

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Design and implementation of iris recognition based attendance management system

Cited by 38 publications

References 5 publications

Quick Response (QR) Code based Attendance Marking System

Quick Response (QR) Code based Attendance Marking System

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

A Framework for Iris Partial Recognition based on Legendre Wavelet Filter

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