Study on Visual Measurement of Riveting Panel Based on Neural Network
The diameter of the riveting hole is one of the important parameters affecting the quality of the riveting hole.This paper proposes a machine vision measurement method based on neural network,which detects products through image preprocessing,region of interest(ROI)extraction,image recognition,and size measurement.The objective of image preprocessing is to obtain a better representation of the original image through the lens compensation model based on a neu-ral network.The detected boundary can be used as the basis for filtering image ROI extraction,and the compressed ROI is stored in the database and sent out by the image recognition module.The image recognition module is constructed based on reverse residual blocks,which reduces the model size and calculation time while maintaining the recognition accuracy,and the image recognition accuracy of holes reaches 94.67％.The pixel diameter of the panel riveted to the measured hole is obtained by using the pixel diameter of the reference.Experimental results show that the diameter measurement accuracy of the proposed method is about 95％on average.
万方数据
维普
