Research on General Method of Industrial Surface Detection Based on Deep Learning
Product surface detection is an important part of automatic production.The detection accuracy and speed are the main indexes to evaluate the efficiency of automatic inspection system.Surface detection based on deep learning can meet the real-time requirements under complex image background,but it is lack of universality.To solve this problem,a gen-eral method of defect segmentation and classification was proposed.This method can accurately locate the defects through semantic segmentation,and further classify the defects by combining the residual network to meet the requirements of product defect classification.It is also possible to meet the need of classifying only products with classification networks only.
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