Abstract: Face recognition has been challenging and interesting area in real time applications. Face recognition is a form of biometric identification that relies on data acquired from the face of an individual. A large number of face recognition along with their modifications, have been developed during the past decades. Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. In real world applications, it is desirable to have a stand-alone, embedded facerecognition system. The reason is that such systems provide a higher level of robustness,hardware optimization, and ease of integration. In this paper an attempt is made to review a wide range of methods used for face recognition comprehensively. This include PCA, ICA, LDA, SVM, Gabor wavelet soft computing tool like ANN for recognition, LBP and various hybrid combination of this techniques. This review investigates all these methods with parameters that challenges face recognition like pose variation, facial expressions and illuminations.
Publication Year: 2017
Publication Date: 2017-01-01
Language: en
Type: review
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Cited By Count: 2
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