Verification and correction method and system for optical charac

Image analysis – Pattern recognition – Context analysis or word recognition

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

382161, 382178, 382231, 382311, 345338, 39518314, 39518322, G06K 934, G06K 962, G06K 972, G06F 1100

Patent

active

059335319

ABSTRACT:
An optical character recognition method and system are provided, employing context analysis and operator input, alternatively and in combination, on the same batch of documents. After automatic character recognition, the context analyzer processes the fields that are good enough to expect resolution. This will accept as many fields as possible without any operator intervention. For some other fields, the process uses operator input to certify the character-level OCR result of, or to enter, a certain percentage of the characters, so that context analysis may accept some of the remaining fields. If the context analyzer successfully identifies a small set of very close hypotheses, the process asks the operator to certify one or two characters to resolve the ambiguity between the hypotheses. For the fields that are still not resolved, the fields and the hypotheses are shown to the operator for acceptance, correction, or entry.

REFERENCES:
patent: 3969698 (1976-07-01), Bollinger et al.
patent: 4674065 (1987-06-01), Lange et al.
patent: 4979227 (1990-12-01), Mittelbach et al.
patent: 5040227 (1991-08-01), Lyke et al.
patent: 5151948 (1992-09-01), Lyke et al.
patent: 5267327 (1993-11-01), Hirayama
patent: 5739850 (1998-04-01), Hori
Amano, et al. "DRS : A Workstation-Based Document Recognition System for Text Entry", IEEE, vol. 25 issue 7, Jul. 1992.
Sinha, et al. "Hybrid Contextual Text Recognition With String Matching", IEEE, vol. 15, No. 9, Sep. 1993.
Downton, et al. "Syntactic and Contextual Post-Processing of Handwritten Addresses for Optical Character Recognition", IEEE, Jun. 1988.
Cohen, Computational Theory for Interpreting Handwritten Text in Constrained Domains, Elsevier, Artificial Intelligence 67, vol. 26, No. 1, Jul. 1994.
J. K. Mullin, InterfacingCriteria for Recognition Logic Used with a Context Post-Processor, Pattern Recognition Society, vol. 15, No. 3, pp. 271-273, 1982.
R. M. K. Sinha et al., Hybrid Contextual Text Recognition with String Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, No. 9, pp. 915-925, Sep. 1993.
From Card to Marc, Vine, No. 48, pp. 26-30, Mar. 1985.
Ong and Lee, Knowledge-based Contextual Processor for Text Recognition, IEEE, Computer Society Technical Committee on Pattern Analysis and Machine Intelligence, (Proceedings) p. 465, Mar. 1993.
Siddiqui et al., Using Contextual postprocessing to Improve Machine Recognition. . . IEEE Int. Symp. on Information Theory, Absts. of Papers, p. 37, Sep. 1983.
Houle et al., Use of a Priori Knowledge for Character Recognition, SPIE vol. 1661, pp. 146-156, 1992.
Downton et al., Syntactic and Contextual Post-Processing of a Handwritten Addresses for Optical Character Recognition, IEEE 9th Internat. Conf. on pattern Recognition, vol. II, pp. 1072-1076, Nov. 1988.
Baird et al., Components of an Omnifont Page Reader, IEEE 8th Internat. Conf. on Pattern Recognition, pp. 344-348, Oct. 1986.
Borgman et al., Getty's Synoname and Its Cousins: A Survey of Applications of Personal Name-Matching Algorithms, Journal of the American Society for Information Science, pp. 459-476, 1992.
Fukunaga et al., Recognition of Words with Semantic Information, Electronics and Communications in Japan, vol. 59-A, No. 1 1976.
T. G. Rose et al., A Large Vocabulary Semantic Analyzer for Handwriting Recognition, AISB Quarterly, No. 80. pp. 34-39.
Recognition Technologies Under Discussion, Electronic Documents, vol. 2, No. 9, pp. 12-16.
Lecolinet, A New Model for Context-Driven Word Recognition, Proc. 2nd Ann. Symp. on Document Analysis and Information Retrieval, pp. 135-145.
G. Farmer, Automated Data Capture & Deposit System Utilizes OCR for Hand-printed Tax Forms, IMC Journal, vol. 28, #2, Mar/Apr., pp. 23-26, 1992.
M. M. Lankhorst et al., Automatic Word Categorization: An Information-theoretic Approach, (paper), Univ. of Groningen, The Netherlands.
R. A. Wilkinson & C. L. Wilson, Using Self-Organizing Recognition as a Mechanism for Rejecting Segmentation Errors, SPIE vol. 1825, Intelligent Robots and Computer Vision XI (1992), pp. 378-388.
P. B. Cullen, T. K. Ho, J. J. Hull, M. Prussak & S. N. Srihari, Contextual Analysis of Machine Printed Addresses, SPIE vol. 1661 (1992), pp. 257-268.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Verification and correction method and system for optical charac does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Verification and correction method and system for optical charac, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Verification and correction method and system for optical charac will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-857024

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.