The Strip Steel Surface Defects Classification Method Based on Weak Classifier Adaptive Enhancement

The contradiction between algorithm complexity and classification accuracy exists in current strip steel surface defects detection system classification method. In order to solve the above problem, weak classifier adaptive enhancement classification method is presented in this paper. In this method presented in this paper, weak classifiers will focus on the samples that are difficult to distinguish, by adaptively changing the distribution of the weights of training samples, so that it can reduce the error of classification, and greatly improve the effectiveness of feature classification. The experimental results show that this method has higher accuracy of classification than other methods in steel surface defect classification, and solved the contradiction between algorithm complexity and classification accuracy better, so the method has certain value for engineering application.