A face recognition system has been developed and demonstrated at the Rutgers University Center for Computer Aids for Industrial Productivity. The system uses a preliminary data reduction step, gray scale projection, and a fast transform technique to greatly reduce the computational complexity of the problem and, consequently, the cost of high-speed implementation. The decision function is a new, extremely cost-effective neural network, the Mammone/Sankar Neural Tree Network. This paper examines the use of gray scale projection in detail, and demonstrates the use of 1D signal processing techniques in 2D imaging applications. Results are presented showing immunity to changes in expression and small rotations about the vertical axis.