Steel Surface Defect Detection Using Texture Segmentation Based on Multifractal Dimension

Recently, it becomes significant to enhance quality of products as well as to increase quantity of products in the steel manufacturing industry. As a manufacturing gets faster, the fast and exact detection of defect is important to acquire a competitive power. Without automatic machine vision technology, steel rolling operations is not able to perform real-time inline surface defect inspection. In this paper, we propose a new defect detection algorithm based on multifractal. Then, some suitable features are extracted and presented to neural network for classification. The obtained accuracy is 97.9 %.