Reconhecimento do tipo de cachaça utilizando visão computacional e reconhecimento de padrões

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Rodrigues, Bruno Urbano lattes
Orientador(a): Costa, Ronaldo Martins da lattes
Banca de defesa: Costa, Ronaldo Martins da, Silva, Anderson Soares, Salvini, Rogério Lopes, Caliari, Marcio
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Goiás
Programa de Pós-Graduação: Programa de Pós-graduação em Ciência da Computação (INF)
Departamento: Instituto de Informática - INF (RG)
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tede/5311
Resumo: The cachaça is a type of drink distilled from sugar cane that has a great economic importance. Their classification includes three types: aged, premium and premium extra. These three classifications are related to the aging time drink in wooden barrels. Besides the aging time is relevant to know what the wood used in the barrels of storage for the properties of each drink are informed correctly to the consumer. This dissertation presented a method for the automatic recognition of the type of wood and the aging time using a computer vision system. The computer vision system is used in the analysis of the color models (RGB) additive and subtractive (CIELab) caught on digital camera. In association with computer vision, algorithmics, system of pattern recognition are used in conjunction with chemical information for the classification of samples. Went used four algorithmics: Artificial Neural network, k-NN (k-Nearest Neighbor), SVM (Support Vector Machines) and Naive Bayes. The end is used the ensemble AdaBoost, technique combining classifiers. In the study we used 108 samples of rum. The results obtained show that it was possible to obtain rates excess use of % 96.26 algorithmics of pattern recognition to the problem of the type of wood. The AdaBoost brought 100 indices % hit to the problem of classification of the type of wood and aging time. Your use proves that it is possible the sort of rum using only color model data contributing to a lower cost of production.