Volume 18, No. 5, 2021
Eigen-face Vector-Based Face Recognition Using a Support Vector Machine
Prabhdeep Singh , Vikas Tripathi , Durgaprasad Gangodkar , Rajesh Upadhyay
Abstract
An approach to facial recognition based on a support vector machine is presented in this study. Conditions such as deterioration of picture quality, varied expressions for the same face, wearing enormous glasses to conceal main portion of the face, adding beards and moustaches, etc. have always made developing an accurate face recognition system a challenging job. Here, the facial recognition system is broken down into its two constituent parts: detection and extraction, and matching. Gabor filters and a Support vector Machines classifier are used to identify faces. It's an analytical model for learning from data and spotting patterns, and it relies on a set of learning algorithms. After all the facial data has been processed, it is sent on to the recognition phase, where Eigen Face Vector is used to assess the quality of the feature vector. The names and genders of people who have been identified by face detection are shown with the comparison results in this feature vector.
Pages: 3174-3177
Keywords: SVM, Face detection, Gabor filter.