This paper deals with detection of defects in the manufactured ceramic tiles to ensure high density quality. The problem is concerned with the automatic inspection of ceramic tiles using Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally on samples. Architecture of the system involves binary matrix processing and utilization of Artificial Neural Network (ANN) to detect defects. The above automatic inspection procedures have been implemented and tested on company floor tiles. The results obtained confirmed the efficiency of the methodology in defect detection in raw tile and its relevance as a promising approach on matrix, as well as included in quality control and inspection programs.