Ceramic Tile Defect Inspection System Implemented on FPGA
DOI:
https://doi.org/10.37537/rev.elektron.6.1.144.2022Keywords:
High Level Synthesis, FPGA, Computer Vision, Blob Detection, Pinhole Detection, Morphological InspectionAbstract
Modernization in factories is the key for production and product quality. However, this modernization can involve an investment that companies cannot take, leaving them out of adaptation to Industry 4.0. In the ceramic tile manufacturing industry visual inspections are used to determine the quality of the final product. These tasks are carried out by operators exposed to risky environments. This work presents a low-cost solution for automatic ceramic tile inspection. The defects analyzed are blobs, pinholes, corners, edges and dimensions. All the algorithms were implemented on SoC FPGA (Xilinx Zynq device) using high level synthesis. The algorithms were verified and validated in a controlled environment built to evaluate visual inspection applications. The results of resource utilization and processing times indicate that the implementation in a real production line is feasible.Downloads
References
D. T. Pham, R. J. Alcock, Smart Inspection Systems: Techniques and applications of intelligent vision, Academic Press, 2003.
G.M.A. Rahaman, M. Hossain, “Automatic Defect Detection and Classification Technique from Image: A Special Case Using Ceramic”, Int. J. Comput. Sci Inf. Secur., vol. 1, n 9, 2009.
L. Echeverz, M. Matías Melograno, L. Leiva. "Inspección automática de defectos de superficie en baldosas cerámicas." XXIV Congreso Argentino de Ciencias de la Computación, La Plata, 2018.
Cognex. (n.d.). In-Sight 7000 Series Vision Systems. Retrieved may 11, 2021, from https://www.cognex.com/productsmachine-vision/2d-machine-vision-systems/in-sight-7000-series
Stemmer Imaging. (n.d.). Machine vision systems. Retrieved may 20, 2021, from https://www.stemmer-imaging.com/en/products/category/vision-systems/
Z. Liu, H. Ukida, H., P. Ramuhalli, K. Niel. Integrated Imaging and Vision Techniques for Industrial Inspection. Springer, 2015.
J.J.R. Andina, E. De la Torre Arnanz, M.D. Valdes. FPGAs: Fundamentals, Advanced Features, and Applications in Industrial Electronics. CRC Press, 2017.
A. Swirski. "TULIPP and ClickCV: How the Future Demands of Computer Vision Can Be Met Using FPGAs." Towards Ubiquitous Low-power Image Processing Platforms. Springer, Cham, 2021, pp. 235-259.
T. Czimmermann, G. Ciuti, M. Milazzo, M. Chiurazzi, S. Roccella, C. M. Oddo, P. Dario. "Visual-based defect detection and classification approaches for industrial applications—a survey." Sensors 20, no. 5 (2020): 1459.
T. Medina, L. Leiva, M. Vázquez. "Plataforma para Procesamiento de Imágenes sobre SoC FPGA de Xilinx." Elektron vol. 4, no. 2, 2020, pp. 81-86.
J. Trein, A. Th Schwarzbacher, B. Hoppe. "FPGA implementation of a single pass real-time blob analysis using run length encoding." MPC-Workshop, February, 2008.
C. Harris and M. Stephens, “A Combined Corner and Edge Detector,” The 4th Alvey Vision Conference, Manchester, 31 August-2 September 1988, pp. 147-151.
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