Source Code for Color Fringe-Based Phase Measurement Profilometry

Color fringe-based Phase Measurement Profilometry (PMP) is a widely used technique in optical 3D measurement. This method reconstructs three-dimensional surface topography by analyzing phase variations in color fringe patterns projected onto object surfaces. Combining fringe projection and phase demodulation technologies, it offers advantages of high precision and non-contact measurement.

The MATLAB source code implements a complete color fringe PMP pipeline with these key algorithmic steps:

Color fringe generation: Creates sinusoidal fringe patterns in red, green, and blue channels based on predefined frequency and orientation parameters. The code typically uses matrix operations to generate phase-shifted sine waves, where color encoding improves measurement efficiency by reducing required projection sequences.

Fringe projection and acquisition: Projects generated color fringes onto target objects and captures deformed fringe images using a camera. Surface height variations modulate the fringe patterns, creating phase-encoded depth information. The implementation includes image acquisition interfaces for synchronizing projection and capture devices.

Phase demodulation: Extracts phase information from each color channel of captured fringe images. The code employs Fourier transform methods or phase-shifting algorithms (e.g., 3-step or 4-step phase shifting) for phase calculation, incorporating filtering techniques to minimize background illumination and noise effects.

Phase unwrapping: Resolves phase ambiguity from arctangent functions (wrapped between [-π, π]) using unwrapping algorithms like quality-guided path following or spatial phase unwrapping. The implementation handles discontinuity issues through reliability-based phase unwrapping approaches.

3D reconstruction: Converts demodulated phase values to height maps using system calibration parameters (camera-projector geometry). The reconstruction module applies coordinate transformation matrices and triangulation principles to generate point cloud data for surface topography.

Compared to monochromatic fringe methods, color fringe PMP reduces projection cycles through simultaneous multi-channel encoding, enabling faster measurement speeds suitable for dynamic 3D scanning applications. This MATLAB source provides a complete framework for 3D topographic analysis in research and industrial inspection scenarios.