Uma metodologia de binarização para áreas de imagens de cheque utilizando algoritmos de aprendizagem supervisionada

• Autor(a) principal: Alves, Rafael Félix
• Data de Publicação: 2015
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do Mackenzie
• Texto Completo: http://dspace.mackenzie.br/handle/10899/24381
• topic: binarização; aprendizagem de máquina; classificação; imagens de cheque; montante de cortesia; CMC-7 (Caracteres Magnéticos Codificados em 7 Barras); redes neurais artificiais; árvore de decisão; binarization; machine learning; classification; check images; courtesy amount; CMC-7; artificial neural network; decision tree; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

The process of image binarization consists of transforming a color image into a new one with only two colors: black and white. This process is an important step for many modern applica-tions such as Check Clearance, Optical Character Recognition and Handwriting Recognition. Improvements in the automatic process of image binarization represent impacts on applications that rely on this step. The present work proposes a methodology for automatic image binariza-tion. This methodology applies supervised learning algorithms to binarize images and consists of the following steps: images database construction; extraction of the region of interest; pat-terns matrix construction; pattern labelling; database sampling; and classifier training. Experi-mental results are presented using a database of Brazilian bank check images and the competi-tion database DIBCO 2009. In conclusion, the proposal demonstrated to be superior to some of its competitors in terms of accuracy and F-Measure.