Reconhecimento do tipo de cachaça utilizando visão computacional e reconhecimento de padrões
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2015-10-01
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Universidade Federal de Goiás
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.
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RODRIGUES, B. U. Reconhecimento do tipo de cachaça utilizando visão computacional e reconhecimento de padrões. 2015. 116 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2015.