Structured light is considered one of the most effective techniques to acquire 3D models. This technique is based on projecting a light pattern and capturing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be quickly found and 3D information easily retrieved.
One of the most commonly exploited coding strategies is based on trmatime-multiplexing. In this case, a set of patterns are successively projected onto the measuring surface. The codeword for a given pixel is usually formed by the sequence of illuminance values for that pixel across the projected patterns. Thus, the codification is called temporal because the bits of the codewords are multiplexed in time [234] .
In this module a time-multiplexing coding strategy based on Gray encoding is implemented following the (stereo) approach described in 3DUNDERWORLD algorithm [124] . For more details, see Structured Light tutorials.
#include <opencv2/structured_light/sinusoidalpattern.hpp>
Type of sinusoidal pattern profilometry methods.
| Enumerator | |
|---|---|
| FTP Python: cv.structured_light.FTP | |
| PSP Python: cv.structured_light.PSP | |
| FAPS Python: cv.structured_light.FAPS | |
#include <opencv2/structured_light/structured_light.hpp>
Type of the decoding algorithm.