Quality control is an important issue in the ceramic tile industry. On the other hand maintaining the rate of production with respect to time is also a major issue in ceramic tile manufacturing. Due to massive production of ceramic tiles, using human resources for defect detection is quite tedious and time consuming process. So we need to automate the process. Various optical technology based approaches came into play such as Automatic Optical Imaging. It is effective but very expensive technique for small-scale manufacturers. Therefore, many researchers started developing image processing algorithms for defect detection in ceramic tiles using less expensive cameras. In this paper we proposed an automated computer vision system with efficient defect detection technique, which can detect surface defects like blobs and cracks on tiles with high accuracy and fast response. This automated method helps us to acquire knowledge about the pattern of defect within a very short span of time. To automate the whole process, we have developed a ‘Graphical User Interface’ (GUI) in MATLAB using GUIDE (Graphical user interface design environment). We have used Sobel operator for edge detection and image subtraction techniques for fault detection in ceramic tiles. Index Terms— CV (Computer Vision), GUI (Graphical User Interface), GUIDE (Graphical user interface design environment), Threshold segmentation.

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