Automated Quality Inspection on Tile Border Detection using Vision System
Hairol Nizam Mohd Shah1,Yap Sher Kee2, Zalina Kamis3, Mohd Rizuan Baharon4, Mohd Zamzuri Ab Rashid5
1H.N.M. Shah, Center of Excellence for Robotics and Industrial Automation Laboratory, Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.
2M. Sulaiman, Center of Excellence for Robotics and Industrial Automation Laboratory, Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.
3K.S.M. Isa, Center of Excellence for Robotics and Industrial Automation Laboratory, Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.
4Z. Kamis, Center of Excellence for Robotics and Industrial Automation Laboratory, Fakulti Kejuruteraan Elektrik, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.
5M. R. Baharon, Department of Computer System and Communication, Faculty of Communication and Information Technology, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia.
Manuscript received on 02 August 2019. | Revised Manuscript received on 10 August 2019. | Manuscript published on 30 September 2019. | PP: 3737-3745 | Volume-8 Issue-3 September 2019 | Retrieval Number: C3983098319/2019©BEIESP | DOI: 10.35940/ijrte.C3983.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Index Terms: Border Defect Detection, Ceramic Tile, Crack, Vision, Visual Inspection.
Scope of the Article: Automated Software Specification