A carrier removal technique for Fourier transform profilometry based on principal component analysis

We present a carrier removal method for Fourier transform profilometry using the principal component analysis. The proposed approach is able to decompose the phase map into several principal components, in which the phase of the carrier can be extracted from the first dominant component acquired. It can cope well with the nonlinear carrier problem resulted from the divergent illumination which is commonly adopted in the fringe projection profilometry. It is effective, fully automatic and does not require the estimation for system geometrical parameters or the prior knowledge on the measured object. Further, the influence of the lens distortion is considered thus the carrier can be determined more accurately. The principle of the technique is verified by our experiments, showing that it performs well in both static and dynamic measurements.