Optical character recognition by the method of moments . This gives a rough measure of the ratio of horizontal to vertical lines in the symbol. Another set of characteristics are based on moments about the centroid of the blob. We therefore have a set of dimension weightings which are adjusted by hand on a trial and error basis. All distances in a given dimension are multiplied by the appropriate weighting before being used.
Several methods are available to improve the partitioning of the n space.
The Karhunen Love transform can be used to choose alternative axes which highlight the distribution of the prototypes. Comparison of Handprinted Digit Classifiers - Grother, al. The popularity of OCR research was maintained with the advent of neural network paradigms applicable to feature extraction and classification. G. L. Cash and M. Hatamian. Optical character recognition by the method of moments .