Fringe Segmentation Algorithm Based on Improved U-Net

To improve the accuracy of light stripe segmentation in the traditional vision measurement system based on line-structured light, an improved light stripe segmentation algorithm based on U-Net is proposed. The proposed algorithm uses the convolution pooling layer of VGG16 instead of that in the U-Net coding block, introduces the coordinate attention mechanism in the hop connection between U-Net coding and decoding layers, and connects the pyramid pooling module at the end of U-Net coding block. Additionally, it uses a combination of Dice function and cross entropy function as the loss function of the network, so as to solve the problem of imbalance of light stripe proportion. Based on the principle of line-structured light measurement, a workpiece size measurement system is designed. Experimental results show that the mean pixel accuracy (mpa) of the improved U-Net algorithm is 95.61% and mean intersection over union (mIoU) is 89.73%, which are higher than other comparison algorithms. The absolute error of workpiece measurement size is less than 0.1 mm, the relative error is less than 1%, and the repetition accuracy is less than 0.2%, meeting the inspection requirements of the workpiece.