(Retracted) Image restoration and quantitative metallographic tissue based on machine vision

Abstract

In recent years, with the development of computer image processing technology and quantitative metallography, quantitative metallographic analysis and image restoration based on machine vision image processing have attracted extensive attention. To deeply study the special ability of machine vision technology in metallographic image restoration and quantitative analysis, we adopt a model construction method, parameter design method and comparative analysis method to collect samples and analyze the machine vision system. Through quantitative metallographic organization, based on the progress in artificial neural networks and classification algorithms, a set of analysis system equipment and image restoration algorithm was finally established. The experimental results show that the recognition rate of this method is 5.69% higher than that of method 3, and the overall recognition rate is 5.1% higher than that of method 3, reaching 98.65%. It basically proves the superiority of the image classification algorithm in this paper and also indirectly proves that the system can play a role in the restoration and quantitative analysis of metallographic tissue images.