Fringe line detection and phase unwrapping method and system based on fl-net convolutional neural network

Abstract

Provided is a fringe line detection and phase unwrapping method and system based on an FL-Net convolutional neural network. The method includes: constructing the FL-Net convolutional neural network; detecting fringe lines of an input image by using the FL-Net convolutional neural network to obtain an image with detected fringe lines; performing circulation integral on the detected fringe lines to repair the detected fringe lines to thereby obtain an image with repaired fringe lines; performing path integral on the repaired fringe lines to unwrap the repaired fringe lines to thereby obtain an image with unwrapped fringe lines; and identifying error points of the unwrapped fringe lines by using the FL-Net convolutional neural network; and processing the error points. Specifically, an HDC method is used to replace a down-sampling method to avoid the loss of resolution, and residual connection is used to prevent the network from being too deep.