Authors : D.O. Aborisade
Abstract: The objective of this study is to design a model based on the artificial neural network with radial basis for automatic classification of stainless steel strips into either good (accepted) or bad (rejected) categories. Firstly, defect is segmented from the background image through optimal thresholding technique and then geometry features such as area and shape complexity of the defect were measured. Artificial neural network structure is employed in the classification stage. The experimental results demonstrate that the proposed method is effective and feasible in stainless steel mills.
D.O. Aborisade , 2009. Classification of Stainless Steel Strips Using Artificial Neural Network with Radial Basis Functions. Research Journal of Applied Sciences, 4: 225-229.