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Intelligent Face Detection and Recognition

Author(s):

Mohd Danish , Al-Falah School of Engg & Tech.; Dr. Mohd Amjad, Jamia Millia Islamia

Keywords:

Face detection ,Recognition, euclidean distance, PCA.

Abstract

Human face is the identity signature that helps to identify and segregate human beings. This identity signature is dependent on number of parameters ranging from skin color, to geometry of features an contours on human face .Thus face recognition is one challenging field in biometric science .Human brain can recognize these faces despite large changes in the visual stimulus, be it the change in hairstyle, expression, aging, and distractions such as glasses or a new style of beard or many such feature change. Different approaches use the specific databases which consist of single type, format and composition of image. Face detection finds whether there is a face in the given image or not, and where it is, while face recognition finds the identity of a detected face in the image. The face detection algorithm works by locating eyes in the image and the face recognition algorithm uses Principal Analysis to calculate eigenvalues and eigenvectors of the face images. The Viola &Jones face detection algorithm is a popular, learning-based technique that is used in present-day cameras and devices. Face recognition has many issues to deal with, like the type, format and composition of the face images used for recognition. The present paper carries a performance accuracy of PCA based face recognition on different face datasets, which have large variation in lighting condition ,pose variation, age variation and face size.

Other Details

Paper ID: IJSRDV2I3524
Published in: Volume : 2, Issue : 3
Publication Date: 01/06/2014
Page(s): 1259-1263

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