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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2013 Vol.5(5): 774-779 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.794

Surface Defect Detection and Classification Based on Statistical Filter and Decision Tree

Habibullah Akbar, Nanna Suryana, and Fikri Akbar
Abstract—Industrial quality inspection is a major issue due to the growing of market competitiveness which requires the product to be checked in terms of online defect detection. Meanwhile, labor inspection has been eliminated due to its limitation that restricts the speed of manufacturing process. Hence, automated inspection process is inevitable to preserve the industrial health and lift human function into management tasks. There are huge efforts on Automated Visual Inspection (AVI) research area, particularly in plain surfaces such as ceramics and fabrics. The inspection modeling includes statistical-based, model-based and color analysis. Most systems are well studied and tested on Charge-Coupled Device (CCD) image sensor. However, only few approaches are carried out for Complementary Metal Oxide Semiconductor (CMOS) imaging modality. This study presents an inspection scheme to detect defect in plain fabric based on statistical filter and geometrical features on CMOS-based image input. The advantage of this technology is obvious regarding to its affordable development especially for small and medium industries. We showed that it is suitable for defect inspection applications that does not require specialized lighting environment. In addition, a classification approach is developed based on decision tree framework. The result for static image shows the classification achieve 99% accuracy.

Index Terms—Automated visual inspection, plain surfaces, statistical filter, thresholding, geometrical moments, and decision tree classifier.

A. Habibullah and Fikri Akbar are with the Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia (e-mail: habibrown@gmail.com, fikripunya@gmail.com).
Nanna Suryana is with the International Office and lecturer at Faculty of Information Technology and Communication (FTMK) at Universiti Teknikal Malaysia Melaka, Melaka, Malaysia (e-mail: nsuryana@utem.edu.my).


Cite:Habibullah Akbar, Nanna Suryana, and Fikri Akbar, "Surface Defect Detection and Classification Based on Statistical Filter and Decision Tree," International Journal of Computer Theory and Engineering vol. 5, no. 5, pp. 774-779, 2013.

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