Abstract: Patterns of intelligence detected in a digital image representation are correlated with pattern classes according to a predetermined set of rules for improved pattern identification. Identified patterns are subsequently mapped to classes for continued use of classification.

Abstract: A system for performing optical pattern recognition includes a first detector neural network for detecting the presence of a particular optical pattern in an input image and a second locator neural network for locating and/or removing the particular optical pattern from the input image. The detector network and the locator network both comprise nodes which can take on the -1, +1, or undefined states. The nodes are arranged in layers and each node in a layer has a location corresponding to a pixel in the input image. A particular application of this neural network is in finding the amount field on a check and removing the line which borders the amount field.

Abstract: A pattern recognition system for recognizing an unknown pattern comprised of symbols which are part of a pattern system which is devoid of inherent context such as numbers. Artificial contextual information based on other than symbol features and the pattern system and in the form of probability weighted expected interpretations are stored and used in the processing phase of recognition. In the system disclosed, the system comprises a neural network whose forward and feedback paths are controlled by the output cells of the network based, in part, on the contextual information.