As manufacturing speed increases in the steel industry, fast and exact product inspection becomes more important. This paper deals with defect detection and classification algorithm for high-speed steel bar in coil. We enhance an acquired image by use of a special subtractive method and find the position of defect using local entropy and morphology. The extracted statistical features are then presented to a classifier. We use neural network and fuzzy inference system as a classifier and compare their results. The best accuracy,% 97.19, is obtained by the neural network.
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