Development a Machine Vision System For Marble Classification

Abstract

In marble sector, marble quality varies depending on vessel pattern and color. These patterns and colors are the most important factors affecting the quality and possible class of marble. The marble tiles in the marble palette ordered by the marble palette and the difference between the pattern and quality of the product causes the return of the product. Therefore, many firms suffer economic damage. In order to prevent this damage, it has become an important issue to automatically process the classification process with image processing and deep learning methods. In this study, it is aimed to make classification by adding new data to pre-trained network by AlexNet model. Fimar Marble Mine Co. Inc. operating in Sivas. In 3 different classes, 600 marble samples were trained by AlexNet model and Local Binary Pattern method and the pattern information was obtained. Local Binary Pattern method was used to classify the characteristic by creating color and pattern.