A three-dimensional surface profile measurement method for single-frame color fringe projection based on deep learning, comprising: constructing a convolutional neural network-based model CNN; inputting grayscale fringe images in three channels which are red, green, and blue channels of a color fringe image; projecting, by using a projector, three 12-step phase shift fringes having different frequencies; generating training data required by the CNN by using a phase shift (PS) method and a projection minimum distance method (PDM) to train the CNN; during use, inputting the three channel grayscale fringe images of the color fringe image into the CNN to obtain a molecular item, a denominator item, and a low-precision absolute phase containing fringe level information; substituting the molecular item and the denominator item into an arc tangent function, and performing calculating to obtain high-precision absolute phase information in combination with the low-precision absolute phase. According to the method, more accurate phase information and more reliable phase unwrapping can be provided without any complex pre-/post-processing.
THREE-DIMENSIONAL SURFACE PROFILE MEASUREMENT METHOD FOR SINGLE-FRAME COLOR FRINGE PROJECTION BASED ON DEEP LEARNING