Cachaça Classification Using Chemical Features and Computer Vision
نویسندگان
چکیده
Cachaça is a type of distilled drink from sugarcane with great economic importance. Its classification includes three types: aged, premium and extra premium. These three classifications are related to the aging time of the drink in wooden casks. Besides the aging time, it is important to know what the wood used in the barrel storage in order the properties of each drink are properly informed consumer. This paper shows a method for automatic recognition of the type of wood and the aging time using information from a computer vision system and chemical information. Two algorithms for pattern recognition are used: artificial neural networks and k-NN (k-Nearest Neighbor). In the case study, 144 cachaça samples were used. The results showed 97% accuracy for the problem of the aging time classification and 100% for the problem of woods classification.
منابع مشابه
Identification of Houseplants Using Neuro-vision Based Multi-stage Classification System
In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...
متن کاملFacial Expression Recognition Based on Structural Changes in Facial Skin
Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...
متن کاملClassification of emotional speech using spectral pattern features
Speech Emotion Recognition (SER) is a new and challenging research area with a wide range of applications in man-machine interactions. The aim of a SER system is to recognize human emotion by analyzing the acoustics of speech sound. In this study, we propose Spectral Pattern features (SPs) and Harmonic Energy features (HEs) for emotion recognition. These features extracted from the spectrogram ...
متن کاملTwo New Methods of Boundary Correction for Classifying Textural Images
With the growth of technology, supervising systems are increasingly replacing humans in military, transportation, medical, spatial, and other industries. Among these systems are machine vision systems which are based on image processing and analysis. One of the important tasks of image processing is classification of images into desirable categories for the identification of objects or their sp...
متن کاملClassification of ECG signals using Hermite functions and MLP neural networks
Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. In the first module the stationary wavelet transform (SWF) is used for noise reduction of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014