3D reconstruction using spline inverse function analysis

Various methods have been proposed to analyse fringe patterns in Fringe Projection Profilometry (FPP) used for 3D Acquisition systems. FPP is a full frame and high-speed acquisition system that enables fast 3D acquisition of large areas with high accuracy. Most of fringe analysis methods assume that the captured pattern is perfect sinusoidal. However, due to projector response and cross talk between colours, optical aberration and the presence of noise, it is difficult to obtain a perfect sinusoidal signal. In this paper, Spline Inverse Function Analysis (SIFA) is proposed to analyse both sinusoidal and non-sinusoidal patterns in FPP. This method is based on Inverse Function Analysis (IFA) method, but instead using polynomial fitting, this method uses spline to avoid Runge phenomenon and heavy computation on determining the polynomial degree and minimize the error. The proposed method is compared with Fourier Transform Profilometry (FTP) method and results show that SIFA gives 50 times better result than FTP.