Walter Steven Rosenbaum

Word autocorrelation redundancy match (WARM) technology

Word Autocorrelation Redundancy Match (WARM) is an intelligent facsimile technology which compresses the image of textual documents at nominally 145:l by use of complex symbol matching on both the word and character level. At the word level, the complex symbol match rate i s enhanced by the redundancy of the word image. This creates a unique image compression capability that allows a document to be scanned for the I50 most common words, which make up roughly 50% of the text by usage, and upon their match the words are replaced for storageltransmission by a word identification number. The remaining text is scanned to achieve compaction at the character level and compared to both a previously stored library and a dynamically built library of complex symbol (character) shapes. Applying the complex symbol matching approach at both the word and character levels results in greater efJiciency than is achievable by state of the art CCITT methods.

Multifont OCR postprocessing system

A series of techniques is being developed to postprocess noisy, multifont, nonformatted OCR data on a word basis to 1) determine if a field is alphabetic or numeric; 2) verify that an alphabetic word is legitimate; 3) fetch from a dictionary a set of potential entries using a garbled word as a key; and 4) error-correct the garbled word by selecting the most likely dictionary word. Four algorithms were developed using a technique called vector processing (representing alphabetic words as numeric vectors) and also by applying Bayes maximum likelihoods olutions to correct the OCR output. The result was the development of a software simulator which processed sequential fields generated by the Advanced Optical Character Reader (in use by the U.S. Postal Service in New York City), performed the four functions indicated above, and selected the correct alphabetic word from a dictionary of 62000 entries.