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Research Paper | Electronics & Communication Engineering | India | Volume 4 Issue 7, July 2015 | Popularity: 6.5 / 10

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Face Recognition Using Principal Component Analysis for Security Based System

Madhuri M. Ghodake, Parul S. Arora

Abstract: Security is generally a state or feeling of being saved and protected, it is an assurance that something of value will not be taken which is protected. This system is mainly designed for getting access in the strong rooms of the Military system by recognizing the face. This proposed system consist of two of the emerging artificial intelligence technologies that are Facial Recognition and Eigen Face approach using Principal Component Analysis algorithm for developing a secure keyless door where authentication of authorized faces is the only guarantee for entry in the strong rooms of the Military security system. This mechanically built door, has an interface with the PC for capturing and processing images. A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Proposed System uses face recognition technique for verification in Military security System. For face recognition, there are two types of comparisons are done. The first step is the verification, in this this verification step the system compares the given individual with who that individual says they are and gives a yes or no decision. The next one is of the identification, in the identification the system compares the given individual to all the other individuals in the database and gives a ranked list of matches of the images. Principal component analysis (PCA) is the simplest of the true eigenvector based multivariate analysis. Mathematically, it is an orthogonal linear transformation that transforms the data to a new coordinate system. The use of Eigen faces is commonly called as Principal Component Analysis. With PCA, the image which are used for verification and the identification they should be of same size and they are normalized to line-up the eyes and mouth of the subjects within the image. Using PCA, dimension of data using data compression basics is reduced and precisely decompose the face structure into orthogonal and uncorrelated components know as Eigen faces. Face Recognition, Verification, Eigen faces, Principal Component Analysis (PCA).

Keywords: Face Recognition, Verification, Eigen faces, Principal Component Analysis, PCA

Edition: Volume 4 Issue 7, July 2015

Pages: 1262 - 1267

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