Barley defects identification

Abstract

In brewing industry, quality of barley accepted for malt production is essential. The visual inspection of grain for malting is performed by a qualified expert. The process is time-consuming, expensive, and still may yield unreproducible results. Therefore, there is a need for automatic systems, based on computer vision, able to verify grain properties. We present a concept of such the system, which implements image preprocessing, texture, color and shape feature extraction, supervised learning and selected classification algorithms. The results of classification are presented and discussed.