Lossless acceleration for correlation-based nearest-neighbor pattern recognition

This paper presents four lossless acceleration algorithms for a special type of nearest-neighbor pattern recognition whereby correlation functions are used. The algorithms are called template stopping, template ordering, pixel stopping, and pixel ordering. All four algorithms may be used either independently or simultaneously to accelerate the nearest-neighbor search without incurring any loss to accuracy. To illustrate their usefulness, all four algorithms are demonstrated on an optical character recognition system.