Vison system development by machine learning: mashing assessment in brewing

摘要

This article describes the development of a machine vision application for automatic process assessment by image analysis and machine learning. The system is required to differentiate between the various stages of a mashing process and determine the termination point. A large number of histograms, Haralick and Gabor features (835) were extracted form 275 training images. Three feature selection algorithms-wrapper, consistency filter, and correlation filter-were then applied to the training data, resulting in feature sets of size 29, 15, and 11, respectively. A number of decision tree, rule induction, and nearest neighbor classification algorithms were then applied to the reduced data set.