Sistema de Reconhecimento Facial Baseado em Análise de Componentes Principais

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Ernesto Luiz Andrade Neto
Lee Luan Ling

Abstract

We present the development and implementation of a face recognition system using principal component analysis to construct a face model from a training set of face images. The computed principal component face model is applied in the feature extraction task. We tested the system in the task of correctly classifying 435 images from 102 people with a minimum distance classifier. These images have a great deal of variations concerning position, scale, expression and illumination, even among images of the same person. The proposed system was able to handle such variations and achieved a recognition rate of 97.70%.

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How to Cite
Andrade Neto, E. L., & Ling, L. L. (2017). Sistema de Reconhecimento Facial Baseado em Análise de Componentes Principais. Journal of Communication and Information Systems, 13(1). https://doi.org/10.14209/jcis.1998.15
Section
Regular Papers