Integrated development environment model for visual image processing based on Moore nearest neighbor model

Abstract

With the development of information technology, especially the development of visual image processing technology, more and more automated production links, such as injection molding production, use visualization to realize automatic detection of injection molds, but the traditional integrated environment for visual image processing exists in real time. In order to solve this problem, this paper proposes a visual image processing integrated development environment model based on the Moore nearest neighbor model. The model runs on the visual platform, and the residuals to be detected are highlighted by the Moore nearest neighbor model. In order to solve the error caused by the image shift, the model introduces the support vector machine as the classification method, and the model is used for the simulation experiment. The average accuracy of cavity residual detection in the model is 85.71%, and the average time of residual detection is 0.910 s. The results show that the model solves the real-time and accuracy problems of the traditional visual image processing model.