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

Md. Mojahidul Islam, Ahsan-Ul-Ambia, Asaduzzaman A.O.m, Md. Shohidul Islam and Md. Atiqur Rahman
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Md. Mojahidul Islam: Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh
Ahsan-Ul-Ambia: Dept. of Computer Science & Engineering, Islamic University, Kushtia, Bangladesh
Asaduzzaman A.O.m: 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

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 4, 137-142

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.

Date: 2024
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