Abstract: In the ceramic tile industry, the bulk amount of ceramic tiles are manufactured, it is challenging to monitor the quality of each tile manually. An automated defect detection and classification technique has been proposed in this report that can have ensured the better quality of tiles in the manufacturing process as well as production rate. There are two steps are followed in this study feature extraction and classification. Feature extraction is based on the properties of Gray Level Co-occurrence Matrix (GLCM) technique. The evaluation of the system is carried on V×C TSG image database. Then Support Vector Machine (SVM) classifier is used for classification step. SVM classifier is used to detect the tile.