Surface reconstruction from photometric stereo images

Received February 11, 1992; revised manuscript received July 24, 1992; accepted October 21, 1992 In previous research (Tech. Rep. 172, University of Southern California, Los Angeles, Calif., 1991) we developed an iterative shape-from-shading (SFS) algorithm that uses a single image, by combining a triangular-element surface model with a linearized reflectance map. In the current research we generalize the single-image SFS algorithm to the photometric stereo SFS algorithm, which uses multiple images taken under different lighting conditions for more-accurate surface reconstruction. An explicit surface model based on nodal basis-function representation is used so that the integrability problem that arises in conventional photometric stereo SFS algorithms can be solved easily. It is also shown that single-image SFS algorithms have an inherent problem; i.e., the accuracy of the reconstructed surface height is related to the slope of the reflectance-map function defined on the gradient space. The accuracy can be greatly improved by combining two photometric images properly, and the optimal illumination condition that leads to the best shape reconstruction is examined. Simulation results for several test images are given to demonstrate the performance of our new algorithm.