Comparative Analysis of Face Recognition Methodologies and Techniques Farwa Abdul Hannan, Zainab Khalid, Ammar Rafiq* Department of Computer Sciences NFC-Institute of Engineering and Fertilizers Research Faisalabad, Pakistan *Corresponding Author: ammar.rafiq@iefr.edu.pk Abstract — In the field of computer sciences such as graphics and also analyzing the image and its processing, face recognition is the most prominent problem due to the comprehensive variation of faces and the complexity of noises and image backgrounds. The purpose and working of this system is that it identifies the face of a person from the real time video and verifies the person from the images store in the database. This paper provides a review of the methodologies and techniques used for face detection and recognition. Firstly a brief introduction of Facial Recognition is given then the review of the face recognition’s working which has been done until now, is briefly introduced. Then the next sections covered the approaches, methodologies, techniques and their comparison. Holistic, Feature based and Hybrid approaches are basically used for face recognition methodologies. Eigen Faces, Fisher Faces and LBP methodologies were introduced for recognition purpose. Eigen Faces is most frequently used because of its efficiencies. To observe the efficient techniques of facial recognition, there are many scenarios to measure its performance which are based on real time. Index Terms —Face Recognition, Automated Teller Machine, Principal Component Analysis, Fisher’s Discriminant Analysis, Linear Discriminant Analysis, extended Local Binary Pattern Histograms, 3 Dimension , 2 Dimension. I. INTRODUCTION Human beings can easily recognize the faces of person from eyes without any fluctuation but computers can’t do so easily. This was the interesting problem in computer domain. To make the computers efficient in recognizing the faces, face recognition system introduced. There are many areas in which we can use this system for various purposes. For example to check the record of those who are illegal criminals. Moreover, this system also uses for security purpose. Like by fixing the cameras in social or public areas. The benefit of using the camera is that we can easily find the misplaced children’s from the images captured by the camera. Is the same way there are many examples in which the face recognition system used. So our computers work more efficiently than humans as they are more than intelligent. Human can let the computers to do intelligent work like recognizing the images, videos and pattern recognition. Face recognition involves the pattern recognition technique which means it gives the ability to people to make the integrated power into the system to make it intelligent enough that they can do non-trivial work easily. The task of face recognition is to “identifying or verifying one or more person in the scene from still images or video sequences using a stored database of facial images”. Already stored images are unknown to the system. When the system will recognize the face it will match with the stored input images. The system will further accepts or rejects the claimed identity of query face [1]. This will works automatically. In general, manual attendance is the tradition in institutes. They marks the attendance on the paper by hand. This takes a lot of time to keep the records of every person manually and also complicated to manage and confirm everyone [2]. To end up the manual system it was necessary to mark the attendance automatically by recognizing the faces of person. For this purpose automatic attendance management system introduced. This system works in various areas like in institutes for attendance, also as a security as well as in social uses. The technology of face recognition based on computer system is playing a great role in the field of research. The working of automatic attendance by recognition of face is efficient and quick task without any time consuming. Attendance marks automatically after recognizing the face. It detects the face, recognize it and match it from predefined database. It saves a lot of time and also note the time of attendance. The working is easily understandable [3]. II. LITERATURE REVIEW Because of the increasing security threats in daily life, the demand of something easier to work with, for the identification or suspects and for security purposes, is also increasing day by day. Hence Face Detection and Recognition is becoming more important aspect of Computer Vision in the application of security. Therefore OpenCV was introduced as a solution to Computer Vision’s problem of better recognition and increased security. OpenCV is a multi-platform framework used for image processing and face detection & Recognition purposes. Its functionality for face recognition is in its several modules like Machine-learning interface, CVCam contains information about video access on 32-bit windows platform though DirectX, CXCore namespace containing the persistence functions, basic data type definitions, linear algebra and statistics methods, and the error handlers, CVaux, HighGUI. Its implementation contains VOL. 04: DECEMBER, 2016 ISSN 2222-1247 37 DOI: 10.24081/nijesr.2016.1.0008