Product Defect Detection using Image Template Matching with MATLAB

Penulis

  • Muhammad Hasya Abdillah University of Al Azhar Indonesia
  • Muhammad Arip Putra Sabilah University of Al Azhar Indonesia
  • Andika Suherman University of Al Azhar Indonesia
  • Dwi Astharini University of Al Azhar Indonesia

DOI:

https://doi.org/10.36722/exc.v1i1.2344

Abstrak

Abstract— In industrial manufacturing processes, ensuring the quality of products is crucial. This paper proposes a system for detecting defects in products using image template matching techniques implemented in MATLAB. The system's primary function is to compare captured images of products with predefined templates to identify potential defects accurately. The method employed in this system is template matching, a well-established approach in image analysis that allows for efficient defect detection. MATLAB, a widely used software tool for image processing, provides the necessary functionality and a robust set of algorithms to implement the proposed system. The experimental results demonstrate the effectiveness of the approach in detecting various types of defects, such as scratches, cracks, and misalignments. This defect detection system offers a reliable and automated solution for improving the efficiency and productivity of manufacturing industries. By enabling early detection and intervention, it contributes to enhancing product quality control and minimizing defective outputs, ultimately leading to cost savings and customer satisfaction. Keywords— Defect Detection; MATLAB; Template Matching; Image Processing

Biografi Penulis

  • Muhammad Hasya Abdillah, University of Al Azhar Indonesia
    Department of Electrical Engineering
  • Muhammad Arip Putra Sabilah, University of Al Azhar Indonesia
    Department of Electrical Engineering
  • Andika Suherman, University of Al Azhar Indonesia
    Department of Electrical Engineering
  • Dwi Astharini, University of Al Azhar Indonesia
    Department of Electrical Engineering

Referensi

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Z. Indera Putera, "Printed Circuit Board Defect Detection Using Mathematical Morphology and MATLAB Image Processing Tools," in International Conference on Education Technology and Computer (ICETC), Malaysia, 2010.

M. H. Abdel-Aziz I, "A real-time approach for automatic defect detection from PCBs based on SURF features and morphological operations," Multimedia Tools and Applications, vol. 78, no. 35, pp. 1-21, 2019.

J. P. R. Nayak, K. Anitha, B. D. D. Parameshachari, R. D. Banu and P. Rashmi, "PCB Fault Detection Using Image Processing," Materials Science and Engineering, vol. 225, no. 1, p. 012244, 2017.

K. Briechle and U. D. Hanebeck, "Template matching using fast normalized cross- correlation," Journal of SPIE, 2021.

Q. Y. W. Y. Yufan Wang, "An improved Normalized Cross Correlation algorithm for SAR image registration," in Conference: Geoscience and Remote Sensing Symposium (IGARSS), IEEE International, 2012.

Diterbitkan

2023-12-31

Terbitan

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