Reconhecimento automático de impressões digitais utilizando wavelets e redes neuronais artificiais

• Ano de defesa: 1998
• Autor(a) principal: Vieira Neto, Hugo
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Centro Federal de Educação Tecnológica do Paraná; Curitiba; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial
• Palavras-chave em Português: Processamento de imagens - Técnicas digitais; Sistemas de reconhecimento de padrões; Redes neurais (Computação); Image processing - Digital techniques; Pattern recognition systems; Neural networks (Computer science)
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/643

This work proposes a new approach for automatic fingerprint recognition. Differently from traditional techniques, based on the analysis of peculiarities existing in fingerprint patterns and dedicated search algorithms for that purpose, it is suggested a methodology centred in signal representation tools and connectionist classification models. Basically, the methodology proposed here supports itself in two main techniques: the FBI’s Wavelet Scalar Quantization standard for fingerprint image compression as method for the feature extraction; and Artificial Neural Networks models that use linear training techniques as method for the classification of the resulting patterns. The main objective of the suggested method is the development of a recognition system independent from specific fingerprint image analysis techniques, looking for low false acceptance and false rejection rates, with priority for the false acceptance rate. The methodologies and results achieved in the executed experiments are presented, as well as their respective analysis and yet some proposals for future work and enhancements. Some aspects pertinent to the image acquisition hardware and some digital image processing techniques are also presented.