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In the ceramic industry, rarely testing systems were employed to on-line detect the presence of defects in ceramic tiles. This paper is concerned with the problem of automatic inspection of ceramic tiles using Infrared Images and Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally from laboratory and on line tile samples. It has been performed system for IR image processing and, utilizing an Artificial Neural Network (ANN), detecting defected or no defected tile. The system has been applied to detect on-line measurement results achieved at the exit of the press. The above automatic inspection procedures have been implemented and tested on a number of tiles using synthetic and real defects. The results obtained confirmed the efficiency of the methodology defect detection in raw tile and its relevance as a promising approach on-line, as well as included in quality control and inspection programs

Methodology for automatic process of the fired ceramic tile's internal defect using IR images and artificial neural network