Algorithm for Efficient Attendance Management: Face Recognition based approach Naveed Khan Balcoh, M. Haroon Yousaf, Waqar Ahmad and M. Iram Baig Abstract Students attendance in the classroom is very important task and if taken manually wastes a lot of time. There are many automatic methods available for this purpose i.e. biometric attendance. All these methods also waste time because students have to make a queue to touch their thumb on the scanning device. This work describes the efficient algorithm that automatically marks the attendance without human intervention. This attendance is recorded by using a camera attached in front of classroom that is continuously capturing images of students, detect the faces in images and compare the detected faces with the database and mark the attendance. The paper review the related work in the field of attendance system then describes the system architecture, software algorithm and results. Keywords: Automatic Attendance; Face Detection; Face Recognition; Image Enhancement; Enrollment; Verification 1. Introduction Maintaining the attendance is very important in all the institutes for checking the performance of students. Every institute has its own method in this regard. Some are taking attendance manually using the old paper or file based approach and some have adopted methods of automatic attendance using some biometric techniques. But in these methods students have to wait for long time in making a queue at time they enter the classroom (20) (21). Many biometric systems are available but the key authentication are same is all the techniques (2). Every biometric system consists of enrolment process in which unique features of a person is stored in the database and then there are processes of identification (3) and verification (4). These two processes compare the biometric feature of a person with previously stored template captured at the time of enrollment. Biometric templates can be of many types like Fingerprints, Eye Iris, Face, Hand Geometry, Signature, Gait and voice. Our system uses the face recognition approach for the automatic attendance of students in the classroom environment without students’ intervention. Face recognition consists of two steps, in first step faces are detected in the image and then these detected faces are compared with the database for verification. A number of methods have been proposed for face detection i.e. AdaBoost algorithm (8) (9), the FloatBoost algorithm (13), Neural Networks (5) (11), the S-AdaBoost algorithm (15), Support Vector Machines (SVM) (6) (10), and the Bayes classifier (7). The efficiency of face recognition algorithm can be increased with the fast face detection algorithm. In all the above methods Voila and Jones (8) is most efficient. Our system utilized this algorithm for the detection of faces in the classroom image. Face recognition techniques can be divided into two types Appearance based which use texture features that is applied to whole face or some specific regions, other is Feature based which uses geometric features like mouth, nose, eyes, eye brows, cheeks and relation between them. Statistical tools such as Linear Discriminant Analysis (LDA) (12), Principal Component Analysis (PCA) (14), Kernel Methods (16), and Neural Networks (19), Eigen-faces (17) have been used for construction of face templates. Illumination invariant (1) algorithm is utilized for removing the lighting effect inside the classroom. 2. Enrollment First step in every biometric system is the enrollment of persons using general data and their unique biometric features as templates. This work uses the enrollment algorithm as shown in the Figure 1. Capture Image Enhanc- ement Feature Extraction Data base Fig 1. Enrollment Process Image is captured from the camera and then it is enhanced using histogram equalization and noise filtering. In the second step face is detected (8) in the image and features are extracted from it. These unique features are then stored in the face database with certain id of that person. 3. System Description The system consists of a camera that captures the images of the classroom and sends it to the image enhancement module. After enhancement the image comes in the Face Detection and Recognition modules and then the attendance is marked on the database server. This is shown in the experimental setup in Figure2. At the time of enrollment templates of face images of individual students are stored in IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 1, July 2012 ISSN (Online): 1694-0814 www.IJCSI.org 146 Copyright (c) 2012 International Journal of Computer Science Issues. All Rights Reserved.