Abstract
An image-based comparative study of different defect classification methods has been presented. Bayesian Network, Artificial Neural Network (ANN) and Probabilistic Neural Network (PNN) based classification techniques have been used for classifying the defects in frontal surface of fluted ingots, which are used for the production of locomotive wheels. The complete system has been implemented for one of the integrated steel plant of India.
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