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Object Defect Detection Using Histogram Analysis and Spearman’s Correlation Coefficient

Author

Listed:
  • Md. Mojahidul Islam

    (Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh)

  • Ahsan-Ul-Ambia

    (Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh)

  • A.O.M Asaduzzaman

    (Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh)

  • Md. Shohidul Islam

    (Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh)

  • Md. Atiqur Rahman

    (Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh)

Abstract

In modern manufacturing industry, Automatic defect detection is becoming an attractive alternative to Human Inspection. Automatic defect detection on object surfaces is a compelling process. For accurate automated inspection and classification, computer vision image processing system has been widely used in manufacturing industries. In this article, we proposed histogram based automatic defect detection that process three objects at a time. In the first step we collect image from the camera, perform preprocessing, segmentation then we used histogram and Spearman’s correlation coefficient to find the defect or non-defect objects. The experimental analysis was evaluated on 300 images including defective and non-defective objects.

Suggested Citation

  • Md. Mojahidul Islam & Ahsan-Ul-Ambia & A.O.M Asaduzzaman & Md. Shohidul Islam & Md. Atiqur Rahman, 2024. "Object Defect Detection Using Histogram Analysis and Spearman’s Correlation Coefficient," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(4), pages 137-142, April.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:4:p:137-142
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