X - ray Weld Image Classification Using Improved Convolutional Neural Network

The defect detection of X-ray weld images is an effective method to improve product quality and safety. Due to the low contrast of the image, the way of using traditional feature extraction and machine learning has low accuracy. In this paper, combined theory with practice, the technique based on improved convolutional neural network is proposed to classify X-ray weld images. In comparison with conventional methods, it avoids dc-noising, extracting and enhancing features. Experimental results on the images obtained from the actual production show that the introduced method has superior accuracy of the classification.