Handprinted symbol recognition system

Image analysis – Histogram processing – For setting a threshold

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382 37, G06K 946, G06K 968

Patent

active

044919603

ABSTRACT:
A handprinted symbol recognition system for identifying through computer techniques free-form, unconstrained handprinting in which accuracy is decoupled from efficiency converts a thin-line (skeletonized) figure output from a preprocessing system, in the form of an array of "black" image points from a raster line sampling, into segment-oriented lists. The segment-oriented lists are filtered and data compressed to obtain a reduced more suitable subset of points approximating the symbol for further processing. The topologic features of the image are extracted from the subset. Short segments that are potential spurs are removed, the image is rotated as necessary and normalized as to size. Each segment and their interrelationships are analyzed to extract geometric features for use in conjunction with the topologic features in a logic tree decision mechanism which uses three modules: (1) pre-recognition ("trash" filter), (2) potential symbol identification, and (3) final quality assurance. The pre-recognition module separates all possible non-meaningful images from those the recognition system has a chance of identifying with minimal misclassification. The symbol identification module uses a decision tree approach in which the most reliable and "rugged" features (relative to real-world scanner data) are placed at the top of the tree. The quality assurance module asks more precise questions about the tentatively identified symbol to determine if it is indeed the particular symbol in question, i.e., the symbol meets a sufficient class membership (SCM) criterion.

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"An Application of Optical Character Recognition Techniques for the Digittion of Alpa-Numerics at the Defense Mapping Agency (DMA)-Part 1", Proceedings, American Congress on Surveying and Mapping, 38th Annual Meeting, (1978), pp. 140-170, by Gronmeyer et al.

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