This invention provides a method and
system for detecting the flatness of a self-insulating concrete wall with a stone-like paint finish. Specifically, a composite
structured light pattern is projected onto the wall surface to be tested. The pattern uses logarithmically modulated sinusoidal fringes as a high-resolution phase carrier, and Gray codes encoding two-dimensional absolute position information are superimposed on the
chromaticity channels. Deformed pattern images are acquired simultaneously, and a
frequency response confidence map is generated based on the image. A
global energy function containing confidence weights and
smoothing constraints is constructed, and a high-precision
absolute phase map is obtained by solving it and converted into an initial three-dimensional
point cloud. A high-fidelity three-dimensional
point cloud is obtained through weighted nonlinear optimization. The three-dimensional
point cloud is converted into a depth-
height map, and decomposed to the scale of the corresponding detection standard through a two-dimensional
discrete wavelet transform associated with physical scales. The L1 norm of the key scale
wavelet detail components is calculated, and the macroscopic undulations and surface texture energy coefficients are separated to achieve a quantitative representation of the macroscopic flatness deviation of the wall surface.