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Surface defect detection plays a significant role in quality enhancement in steel manufacturing. Support Vector Machines and neural networks are the most popular classifiers in this application. Decision trees are also known as other classifiers for steel defect detection yielding a fast but moderate performance. In this paper, we introduce a more accurate classification method by using decision trees...