Bayesian classifier in Tea Sorting

摘要

This article describes a new method for tea sorting based on the minimal error probability's Bayesian classifier. This new set of shape feature vectors can discriminate the images of leaves and stalks with more efficiency than the only color feature vectors do. A multiple Gauss model is used for classifications. The Bayesian classification accuracy outperforms the other results obtained by using threshold classification.