Methods and apparatuses for handwriting recognition

Details Methods and apparatuses for handwriting recognition Methods and apparatuses for handwriting recognition

2005-10-18

2005-10-18

Chang, Jon (Department: 2623)

Image analysis

Pattern recognition

Ideographic characters

C382S187000

Reexamination Certificate

active

06956969

ABSTRACT:
Method and apparatus for handwriting recognition system for ideographic characters and other characters based on subcharacter hidden Markov models. The ideographic characters are modeled using a sequence of subcharacter models and by using two-dimensional geometric layout models of the subcharacters. The subcharacter hidden Markov models are created according to one embodiment by following a set of design rules. The combination of the sequence and geometric layout of the subcharacter models is used to recognize the handwriting character.

REFERENCES:
patent: 5142589 (1992-08-01), Lougheed et al.
patent: 5295238 (1994-03-01), Dickson
patent: 5459809 (1995-10-01), Kim et al.
patent: 5559897 (1996-09-01), Brown et al.
patent: 5594810 (1997-01-01), Gourdol
patent: 5675665 (1997-10-01), Lyon
patent: 5687254 (1997-11-01), Poon et al.
patent: 5878164 (1999-03-01), Brown et al.
Yoshida et al. “Online Handwritten Character Recognition for a Personal Computer System.” IEEE Transactions on Consumer Electronics, vol. CE-28, No. 3, pp. 202-209, Aug. 1992.
Jeng et al. “Optical Chinese Character Recognition With a Hidden Markov Model Classifier—A Novel Approach.” Electronics Letters, vol. 26, No. 18, Aug. 30, 1990, pp. 1530-1531.
Bose et al. “Connected and Degraded Text Recognition Using Hidden Markov Model.” Proc. 11th Int. Conf. on Pattern Recognition, vol. II, Conf. B: Pattern Recognition Methodology and Systems, Aug. 30, 1992, pp. 116-119.
Chen et al. “Word Spotting in Scanned Images Using Hidden Markov Models.” IEEE Int. Conf. on Acoustics, Speech and Signal Processing, vol. 5, Apr. 27, 1993, pp. 1-4.
Chen et al. “Handwritten Word Recognition Using Continuous Density Variable Duration Hidden Markov Model.” IEEE Int. Conf. on Acoustics, Speech and Signal Processing, vol. 5, Apr. 27, 1993, pp. 105-108.
Wang et al. “Optical Recognition of Handwritten Chinese Characters by Partial Matching.” Proc. 2ndInt. Conf. on Document Analysis and Recognition, Oct. 20, 1993, pp. 822-825.
Bellegarda et al. “A Discrete Parameter HMM Approach to On-Line Handwriting Recognition.” Int. Conf. on Acoustics, Speech and Signal Processing, vol. 4, May 9, 1995, pp. 2631-2634.
K. Lee “Automatic Speech Recognition; The Development of The SPHINX Systems”,Kluwer, Boston, 1989.
Nag, R., et al. “Script Recognition Using Hidden Markow Models”, Proceedings of the International Conference on Acoustics, Speech and Signal Processing, pp. 2071-2074, 1986.
Jeng, B., et al., “On The Use Of Discrete-state Markov Process for Chinese Character Recognition”, SPIE, vol. 1360, Visual Comm. and Image Processing'90, pp. 1663-1670, 1990.
Ng, T.M. and Low, H.B., “Semiautomatic Decomposition and Partial Ordering of Chinese Radicals”, Proceedings of the Int. Conf. on Chinese Computing, pp. 250-254, 1988.
Mori et al., “Research on Machine Recognition of Handprinted Characters”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, No. 4, pp. 386-405, 1984.
Tappert, C.C., et al., “The State of The Art In On-Line Handwriting Recognition”. IEEE Transactions on Pattern Analysis and Machine Intelligence, ol. 12, No. 8, pp. 787-808, 1990.
L.E. Baum, “Inequality and Associated Maximization Technique In Statistical Estimation of Probabilistic Functions of Markov processes”, Inequalities, vol. 3, pp. 1-8, 1972.
Sato, Y., and K. Kogure, “Online Signature Verification Based on Shape, Motion, and Writing Pressure”, Proceedings, 6th International Converence of Pattern Rec. vol. 6 pp. 823-826, 1982.
Parizeau and Plamondon, Allograph Adjacency Constraints for Cursive Script REconition, Pre-Proceedings IWFHR III, 1993, 252-61.
PCT/US97/08796 International Search Report.
Y.S. Haung and C.Y. Suen. “An Optimal Method of Combining Multiple Classifiers for Unconstrained Handwritten Numeral Recognition”. Proceedings of the Third International Workshop on Frontiers in Handwriting Recognition. USA pp. 11-20, 1993.

Affiliated with

Also associated with

Rating

Methods and apparatuses for handwriting recognition does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Methods and apparatuses for handwriting recognition, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Methods and apparatuses for handwriting recognition will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3439468