Chapter

Attendance System Based on Face Recognition Using Haar Cascade and LBPH Algorithm

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

To manage attendance of each student is much more complex when it’s done manually, and it has to be done for each class. To overcome this, we can use face recognition application where it takes less time comparatively, and it is stored in the database; this avoids confusions, proxies, and error of storing data when done manually. The students need to fill their data along with parent’s details, so when the students are absent, the message will be passed to them. After taking attendance through the application, mails and message of the data entry of attendance will be sent to the respective teachers. In advance, the details need to be entered beforehand, so when the students come in front of the camera, their face is recognized by comparing them from database containing faces. When it is unable to recognize, the faces will be stored in unknown, so when there is a mishap of being absent, it can be checked later on. This method of attendance is much more successful. Compare to other algorithms, haar cascade and local binary pattern histogram is best due to their robustness and less false rate.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
In this paper, the development of an attendance management system using biometrics is proposed. Managing student attendance during lecture periods has become a difficult challenge. The ability to compute the attendance percentage becomes a major task as manual computation produces errors, and also wastes a lot of time. For the stated reason, an efficient attendance management system using biometrics is designed. This system takes attendance electronically with the help of a finger print device and the records of the attendance are stored in a database. Attendance is marked after student identification. For student identification, a biometric (fingerprint) identification based system is used. This process however, eliminates the need for stationary materials and personnel for the keeping of records. Eighty candidates were used to test the system and success rate of 94% was recorded. The manual attendance system average execution time for eighty students was 17.83 seconds while it was 3.79 seconds for the automatic attendance management system using biometrics. The results showed improved performance over manual attendance management system. Attendance is marked after student identification.
Conference Paper
Full-text available
In the entire globe any educational organization is concerned in relation to the attendance of individuals because this has an effect on their overall performances. In conventional method attendance of students are taken by calling student names or signing on paper which is extremely time overwhelming. To eliminate this problem one of the solutions is a biometric-based attendance system that can automatically capture students' attendance by recognizing their iris. Iris recognition is regarded as one of the most reliable, accurate and efficient biometric identification system due to the inner characteristics of iris, such as uniqueness, immovability and time invariance. The aim of this paper is to design and implement an iris recognition based attendance management system with the latest facilities at an accessible price to think about the financial situation of the large figure of developing countries. The paper includes two parts, hardware and software. The hardware part is responsible to capture images and run required program whereas the software part is responsible for accusation, processing, iris localizing, adjusting, matching and storing data; send the attendance report to the predefined E-mail address. Finally, the system detects, calculates, stores, and transmits the results by performing the MATLAB program.
Article
Full-text available
Radio-frequency identification (RFID) is a technology that uses radio waves to transfer data from an electronic tag, called RFID tag or label, attached to an object, through a reader for the purpose of identifying and tracking the object. RFID technology which is a matured technology that has been widely deployed by various organizations as part of their automation systems. In this study, an RFID based system has been built in order to produce a time-attendance management system. This system consists of two main parts which include: the hardware and the software. The hardware consists of the motor unit and the RFID reader. The RFID reader, which is a low-frequency reader (125 kHz), is connected to the host computer via a serial to USB converter cable. The Time-Attendance System GUI was developed using visual basic.Net. The Time-Attendance Management System provides the functionalities of the overall system such as displaying live ID tags transactions, registering ID, deleting ID, recording attendance and other minor functions. This interface was installed in the host computer.
Article
Full-text available
Iris recognition verification is one of the most reliable personal identification methods in Biometrics. With the rapid development of iris recognition verification, a number of its applications have been proposed until now including time attendance system etc. In this paper, a wireless iris recognition attendance management system is designed and implemented using Daugman's algorithm (Daugman, 2003). This system based biometrics and wireless technique solves the problem of spurious attendance and the trouble of laying the corresponding network. It can make the users' attendances more easily and effectively.
Conference Paper
Full-text available
In this work, we present a novel approach to face recognition which considers both shape and texture information to represent face images. The face area is first divided into small regions from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single, spatially enhanced feature histogram efficiently representing the face image. The recognition is performed using a nearest neighbour classifier in the computed feature space with Chi square as a dissimilarity measure. Extensive experiments clearly show the superiority of the proposed scheme over all considered methods (PCA, Bayesian Intra/extrapersonal Classifier and Elastic Bunch Graph Matching) on FERET tests which include testing the robustness of the method against different facial expressions, lighting and aging of the subjects. In addition to its efficiency, the simplicity of the proposed method allows for very fast feature extraction.
Article
The identification of a face from a video or image source is a study of computer vision know as face detection or recognition. Face detection and recognition becomes popular in recent years by the development of computing power. In this study we will present performance aspect of algorithms Eigenfaces, Fisherfaces, and Local Binary Pattern Histograms in different development platforms: Arm and Intel processors.
Article
This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a face descriptor. The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed.
Deep Learning Haar Cascade Explained
  • Will Berger