Reconhecimento de face utilizando transformada discreta do cosseno bidimensional, análise de componentes principais bidimensional e mapas auto-organizáveis concorrentes

• Ano de defesa: 2010
• Autor(a) principal: Guimarães, Thayso Silva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; BR; Programa de Pós-graduação em Engenharia Elétrica; Engenharias; UFU
• Palavras-chave em Português: Reconhecimento de faces; 2D-DCT; 2D-PCA; SOM; CSOM; Reconhecimento de padrões; Face recognition; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: https://repositorio.ufu.br/handle/123456789/14430

The identification of a person by their face is one of the most effective non-intrusive methods in biometrics, however, is also one of the greatest challenges for researchers in the area, consisting of research in psychophysics, neuroscience, engineering, pattern recognition, analysis and image processing, computer vision and applied in face recognition by humans and by machines. The algorithm proposed in this dissertation for face recognition was developed in three stages. In the first stage feature matrices are derived of faces using the Two-Dimensional Discrete Cosine Transform (2D-DCT) and Two-Dimensional Principal Component Analysis (2D-PCA). The training of the Concurrent Self-Organizing Map (Csoma) is performed in the second stage using the characteristic matrices of the faces. And finally, the third stage we obtain the feature matrix of the image consulting classifying it using the CSOM network of the second step. To check the performance of face recognition algorithm proposed in this paper were tested using three well-known image databases in the area of image processing: ORL, YaleA and Face94.