The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 13, 1976

Filed:

Jul. 30, 1975
Applicant:
Inventors:

Ellen Willis Bollinger, Poughkeepsie, NY (US);

Anne Marie Chaires, Lanham, MD (US);

Jean Marie Ciconte, Rockville, MD (US);

Allen Harold Ett, Bethesda, MD (US);

John Joseph Hilliard, Potomac, MD (US);

Walter Steven Rosenbaum, Silver Spring, MD (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K / ;
U.S. Cl.
CPC ...
3401 / ; 179 / ; 3401 / ; 3401 / ;
Abstract

A data processing system is disclosed for selecting the correct form of a garbled input word misread by an optical character reader so as to change the number of characters in the word by character splitting or concatenation. Dictionary words are stored in the system, having characters which are flagged for segmentation or concatenation OCR misread propensity. The OCR word and a dictionary word are loaded into a pair of associated shift registers, aligning their letters on one end. The dictionary word characters are inspected for error propensity flags. When a splitting propensity, for example, is found for a character, special conductional probability values are accessed from a storage and a calculation is performed of the probability that the first character of the dictionary word was split by the OCR into the first and second characters of the OCR word. This regional context probability is compared with the probability of a simple substitution error for the characters. If the probability of segmentation is larger, the OCR characters in the first shift register are shifted one space with respect to the dictionary word characters in the second shift register so that subsequent character pairs to be compared are properly matched. The greater calculated probability is combined in a running product. The dictionary word with the largest running product is output by the system as the most likely correct form of the garbled OCR input word. In addition to optical character recognition, the system disclosed may be applied to correcting segmentation errors in phoneme-characters output from a speech analyzer. In addition to optical character recognition, the system disclosed may be applied to correcting character substitutions, transpositions, additions, and omissions inadvertently typed on a keyboard.


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