Intelligent Machine Vision System for Automated Quality Control in Ceramic Tiles Industry

Intelligent system for automated visual quality control of ceramic tiles based on machine vision is presented in this paper. The ceramic tiles production process is almost fully and well automated in almost all production stages with exception of quality control stage at the end. The ceramic tiles quality is checked by using visual quality control principles where main goal is to successfully replace man as part of production chain with an automated machine vision system to increase production yield and decrease the production costs. The quality of ceramic tiles depends on dimensions and surface features. Presented automated machine vision system analyzes those geometric and surface features and decides about tile quality by utilizing neural network classifier. Refined methods for geometric and surface features extraction are presented also. The efficiency of processing algorithms and the usage of neural networks classifier as a substitution for human visual quality control are confirmed.

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