Profilometry for the measurement of three-dimensional object shape using radial basis function, and multi-layer perceptron neural networks

Neural networks have been used to carryout calibration process in fringe projection profilometry for the measurement of three-dimensional object shape. The calibration procedure uses several calibration planes whose positions in space are known. Radial basis function based networks and multi-layer perceptron networks are investigated for the phase recovery. Preliminary studies are also presented for the direct reconstruction of the object without the use of the intermediate step of phase plane calculations. Experimental results are presented for diffuse objects.