Classification Of Malt Barley Seed Using Ensemble Deep Learning Technique

Abstract

The primary step in making beer is selecting the malt barley. Every malt house requires that the types of grain be checked before being purchased. Varietal uniformity is essential for the manufacture of high-quality malt. It is challenging to distinguish between different types of malt barley during inspection since it calls for training and experience. To tackle varietal selection difficulties Malt industries have employed and trained experts; even though, those experts do not work effectively due to tiredness, bias, and other factors. Therefore, many researchers are motivated to the development of classification model based on image processing to support experts across the world. Using digital image processing algorithms based on combined morphological, texture, and color features have been investigated to classify different varieties of Ethiopian malt barley.