Abstract: A method for recognizing patterns comprising extracting features from a digital image, generating a numerical representation of each feature, indexing into a look-up table using the numerical representation to determine candidate pattern-types wherein the look-up table was generated by using a number of sample patterns to generate additional patterns based on relationships between the sample patterns; and selecting among the candidate pattern-types using selected contextual information. Extracting features from a digital image comprises identifying line segments in the digital image, grouping together adjacent line segments of the image that form features, storing the coordinates of the features to a file, the coordinates of the feature define a portion of the digital image containing the feature, dividing the portion of the digital image containing the feature into a number of cells, the number of cells is less than the number of pixels in each feature.

Abstract: A method and system includes a method for generating a classifier from a set of collected sample patterns for use in pattern recognition. The sample patterns are representative of data to be processed by the classifier and are converted to electronic signals to be manipulated by a programmed computer. Further, the method and system generate and identify a number of transformers that map between sample patterns of the same pattern-type in the collected sample patterns. The method and system use the transformers and the sample patterns to generate additional patterns. The method and system then forms a table that contains the generated patterns and an indication of the pattern-type to which each pattern belongs. The process repeats the steps of generating additional patterns and forming a table until a measure accuracy for the mapping of the sample patterns and transformers do not provide an acceptable improvement.