Automated quality inspection on tile border detection using vision system - Mohd Shah, Hairol Nizam (Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP), 2019)
Most of the ceramic tile industry still doing the quality control by manually. The accuracy of the manual inspection by human is lower due to the harsh industrial environment with noise, extreme temperature and humidity. A camera should replace the human eyes to recognise the defect tile effectively. Thus, a suitable method have to investigate for implementing this function. This project aim to design and develop an automated quality inspection in ceramic tile industry using vision system. The performance of the system is analysed. An Imaging Source CMOS industrial camera is use to capture the tile border. Image processing with edge detection technique is use to analyse the captured image of tile border and identify the defective tiles. The image filtering and intensity of the light are adjust to evaluate the performance of the system. The overall automation process involves image capturing, image processing, and decision making. The defect detection algorithms are develop to differentiate the defective tile based on the edge detection technique. The system using background subtraction method has achieved 50% accuracy in identify the status of tile since it consist of many limitation. By evaluate the gradient variation on the tile border edge, the accuracy of the defect detection has achieved 80% in identify the tile condition