Application of computer vision algorithm in ceramic surface texture analysis and prediction

Abstract

The recognition and prediction of ceramic surface texture is a key step to improve the quality of ceramic products. The existing ceramic texture feature recognition methods are easily interfered by many factors, resulting in poor texture recognition effect, and the prediction results of texture generation do not match the actual situation. In order to improve the surface quality of ceramic products, this paper proposes a ceramic surface texture recognition analysis and texture generation prediction method based on computer vision algorithm. In this method, laser lines are used to scan along the radial direction of ceramic, and the position of laser stripe is located by straight line detection algorithm. After obtaining the position of laser stripe, the characteristics on laser stripe and the images around laser stripe are detected, so as to judge the quantity and state of ceramic surface texture. From the experimental analysis results, it can be seen that the computer vision algorithm proposed in this paper has good performance in ceramic surface texture recognition analysis and texture generation prediction, which can further improve the quality of subsequent ceramic products.