3D shape reconstruction is one of the most important topics in computer vision and the foundation for a wide field of application. Among various technologies, structured light is one of the most reliable techniques. However, given the field of view of projectors and cameras available in the market, the working distance needed for projectors is typically larger than that for cameras. To reduce the working distance of the projectors while covering the whole working platform, two projectors with their field of view overlapping are used to cover the working area which holds objects to be scanned. We present a spectral analysis based model for the projector-camera system, in order to find the most distinguishable colors for two projectors, and best separate the projected patterns from two projectors. The optimal values of the two colors are determined by the pattern search method in the presence of noise, which is modeled as multivariate Gaussian noise, and characterized for different input colors. The camera sensors' responses to the projector are measured after linearization with gray balance curves. After being properly calibrated, based on one image shot of the object with binary M-array patterns projected on it, the system can reconstruct a 3D shape of the object surface.