CreateSpace Independent Publishing Platform, 2016. — 123 p. — ISBN-10: 151518370X. — ISBN-13: 978-1515183709
Face recognition become very interesting topic of research because of lot of unsolved parameters. From past few decades number of researchers work on the topic to solve the problem of face recognition but still successful face recognition system is not yet implemented hence we proposed face recognition algorithm that match face matrix. As discuss face is nothing but a matrix so using MATLAB software we do matrix manipulation and try to find best possible features for face recognition. In law enforcement and lot of commercial applications, such as in the area of access control systems, national identity, video surveillance, user authentication and retrieval of identity from a data base for criminal investigations face recognition play very important roll but due to challenging problem in real time applications it is not so user friendly. We take look on many unsolved parameters, such as face illumination, expression, pose, scale, low resolution, partial face (occlusion) and other environmental conditions, night video footage and day video footage. However, different pose and occlusion remains as major challenges in face recognition and these two problems affect the performance of face recognition in access control, authentication, and surveillance applications. To meet these challenges, the present study proposed a face recognition system using the analytical approach in which centre of two eye i.e. forehead used for feature extraction. In existing methods of analytical face recognition systems, features like eyes, nose, mouth where used as feature point but in proposed system we used forehead region maximum face recognition rate is 80% using Lab view software. In proposed analytical approach of face recognition, no any work has been done using above mention features but by using different features very little work had done. In literature study maximum recognition rate of analytical, holistic and hybrid approach is below 84% using different face database. In proposed SKM forehead feature work enhancement in recognition rates to 86% and require less time and also solve two big challenges half occlusion and different pose. Facial recognition system is a most useful computer application or device that can identify individuals based on their unique facial characteristics. Unlike many other biometric identification methods (e.g., fingerprints, voiceprint, speech), this can be advantageous in clean environments, for surveillance or tracking, and in automation systems. Because the system keeps a reference model of the individual, and captures their image for identification. They may also be more error-prone when identifying individuals, due to the fairly recent development of the technology. As we know lot of literature available on websites, books, journal etc, we consider international and national paper survey for primary source of data. Various algorithm studies is done from this information collected analysis will be done using various parameters to achieve the basic objective. Study of most popular appearance based face recognition projection methods and detailed descriptions of each module are studied. Our ID cards, passwords can be lost but face is connected part of our body so he/she can be verified with the help of their face. Recently face recognition is attracting much attention in the society of network multimedia information access & also for security purpose. We are providing an up-to-date critical survey of image - and video-based face recognition research. There are two things for us to write this thesis first is to provide an up-to-date review of the existing literature available on net, and the second is to offer some insights into the studies of machine recognition of faces using software. We conclude the thesis with proposed KSM algorithm that helps the government and private sector for security purpose
