Chinese character handwriting recognition system

Image analysis – Pattern recognition – Ideographic characters

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Reexamination Certificate

active

06970599

ABSTRACT:
A handwritten Chinese character input method and system is provided to allow users to enter Chinese characters to a data processor by adding less than three strokes and one selection movement such as mouse clicking or stylus or finger tapping. The system is interactive, predictive, and intuitive to use. By adding one or two strokes which are used to start writing a Chinese character, or in some case even no strokes are needed, users can find a desired character from a list of characters. The list is context sensitive. It varies depending on the prior character entered. Compared to other existing systems, this system can save users considerable time and efforts to entering handwritten characters.

REFERENCES:
patent: 4286329 (1981-08-01), Goertzel et al.
patent: 4573196 (1986-02-01), Crane et al.
patent: 5187480 (1993-02-01), Thomas et al.
patent: 5224179 (1993-06-01), Denker et al.
patent: 5533147 (1996-07-01), Arai et al.
patent: 5586198 (1996-12-01), Lakritz
patent: 5734750 (1998-03-01), Arai et al.
patent: 5796867 (1998-08-01), Chen et al.
patent: 5923793 (1999-07-01), Ikebata
patent: 5926566 (1999-07-01), Wang et al.
patent: 5973676 (1999-10-01), Kawakura
patent: 6002799 (1999-12-01), Sklarew
patent: 6028959 (2000-02-01), Wang et al.
patent: 6041137 (2000-03-01), Van Kleeck
patent: 6075469 (2000-06-01), Pong
patent: 6130962 (2000-10-01), Sakurai
patent: 6144764 (2000-11-01), Yamakawa et al.
patent: 6148104 (2000-11-01), Wang et al.
patent: 6172625 (2001-01-01), Jin et al.
patent: 6212297 (2001-04-01), Sklarew
patent: 6275611 (2001-08-01), Parthasaranthy
patent: 6278445 (2001-08-01), Tanaka et al.
patent: 6493464 (2002-12-01), Hawkins et al.
patent: 6616703 (2003-09-01), Nakagawa
patent: 2002/0168107 (2002-11-01), Tang et al.
patent: 2003/0144830 (2003-07-01), Williams
patent: 114 250 (1992-02-01), None
patent: 762 265 (1997-03-01), None
patent: 961 208 (1999-12-01), None
patent: 1 085 401 (2001-03-01), None
patent: 739 521 (2001-10-01), None
Boxing Code for Stroke-Order Free Handrinted Chinese Character Recognition; Kwok-Wah Hung, Wing-Nin Leung, Yau-Chuen Lai; Proceeding of IEEE International Conference on Systems, Man, Cybernetics; Oct. 8-11, 2000.
On-Line Handwritten Alphanumeric Character Recognition Using Feature Sequences; Xialin Li and Dit-Yan Yeung; Department of Computer Science; Hong Long University of Science and Technology.
Quick Stroke information—www.synaptics.com/products/quickstroke.cfm; and www.synaptics.com/products/quicstroke—faq.cfm.
Online Handwriting Character Analysis Using Stroke Correspondence Search; J. Shin; Journal of Shanghai University, Aizu, University, Fukushima, Japan; Sep. 2001.
JKanji: Wavelet-Based Interactive Kanji Completion; R. Stockton, and R. Sukthankar; Proceedings of the 15thInternational Conference on Pattern Recognition; Sep. 3-7, 2000.
An On-Line Handwritten Chinese Character Recognition System; Fang Fan, and Zhen Yong Lin; Proceedings of the SPIE—The International Society for Optical Engineering; Jan. 26-27, 2000.
Two-layer Assignment Method for Online Chinese Character Recognition; J.Z. Liu, K. Ma, W.K. Cham, M.M.Y. Chang; IEEE Proceedings-Vision, Image and Signal Processing; Feb. 2000.
Radical-Based Neighboring Segment Matching Method for On-Line Chinese Character Recognition; Kuo-Sen Chou, Kuo-Chin Fan, T.-I. Fan; Computer Processing of Oriental Languages; Apr. 1997.
On-Line Chinese Handwriting Character Recognition: Comparision with Japanese Kanji Recognition and Improvement of Input Efficiency; H. Nambu, T. Kawamata, F. Maruyama, F. Yoda, K. Ikeda; Transactions of the Information Processing Society of Japan; Aug. 1999.
Recognizing On-Line Handwritten Chinese Character Via FARG Matching; Jing Zheng, Xiaoqing Ding, Youshou Wu; Proceedings of the Fourth International Conference on Document Analysis and Recognition; Aug. 18-20, 1997.
Recognition of Radicals in Handwritten Chinese Characters By Means of Problem Reduction and Knowledge Guidance; Rei-Heng Cheng, Chi-Wei Lee, Zen Chen; International Journal of Pattern Recognition and Artificial Intelligence; Sep. 1996.
A Hierarchical Representation for the Reference Database of On-line Chinese Character Recognition; Ju-Wei Chen, Suh-Yin Lee; Aug. 20-23, 1996.
Stroke Order and Stroke Number Free On-line Chinese Character Recognition Using Attributed Relational Graph Matching; Jianzhuanf Liu, W.K. Cham, M.M.Y. Chang; Proceedings of the 13thInternational Conference on Pattern Recognition; Aug. 25-29, 1996.
Radical-Based Neighboring Segment Matching Method for On-line Chinese Character Recognition; Kuo-Sen Chou, Kuo-Chin Fan, T.-I. Fan; Proceedign sof the 13thInternational Conference on Pattern Recognition; Aug. 25-29, 1996.
On-Line Recognition of Stroke-Order Free Cursive Chinese Characters With Relaxation Matching; Ki-Cheol Kim, Seong-Whan Lee; Journal of the Korea Information Science Society; Mar. 1995.
An On-Line Recognition System for Cursive Chinese Characters with Effective Coarse Classification and Elastic Matching; Hee-Seon Park, Seong-Whan Lee; Journal of Korea Information Science Society; Sep. 1993.
Stroke-Order Independent On-Line Recognition of Handwritten Chinese Characters; Chang-Keng Lin, Bor-Shenn Jeng, Chun-Jen Lee; Proceedings of the SPIE—The International Society for Optical Engineering; Nov. 8-10, 1989.
Recognition of Handprinted Chinese Characters by Stroke Order Codes; Pan Bao-Chang, Huan Shang-Lian, V. Mueller; 1988 International Conference on Computer Processing of Chinese and Oriental Languages; Aug. 29-Sep. 1, 1988.
Stroke Order Free On-Line Handwritten Character Recognition Algorithm; L. Odaka, T. Wakahara, I. Masuda; Transactions of the Institute of Electronics and Communication Engineers of Japan, Section E; Jun. 1982.
Rough Classification for Handprinted Chines Characters by Stroke Density; S. Naito, and K. Komori; Transactions of the Institute of Electronics and Communication Engineers of Japan, Section E; Aug. 1981.
Cherry Blossom; A System for Japanese Character Recognition; Sargur N. Srihari, Tao Hong and Zhixin Shi; Center of Excellence for Document Analysis and Recognition.
Recognition of Hand-printed Chinese Characters Using Decision Trees/Machine Learning C4.5 System; Adnan Amin, and Sameer Singh; Pattern Analysis and Applications; 1998.
Optical Chinese Character Recognition Using Probabilistic Neural Networks; Richard Romero, David Touretzky, and Robert Thibadeau; Imagaing Systems Lab; Carnegie Mellon University.
Large vocabulary Recognition of On-line Handwritten Cursive Words; Giovanni Seni, Rohini L. Srihari, and Nasser Nasrabadi.
Template-based Online Character Recognition; Scott D. Connell, and Anil K. Jain; Department of Computer Science and Engineering, Michigan State University; Aug. 10, 1999.
Coarse Writing-Style Clustering Based on Simple Stroke-Related Features; Louis Vuurpijl, and Lambert Schomaker; Nijmegen Institute for Cogniton and Information, The Netherlands.
Arnott, J.L., et al;Probabilistic Character Disambiguation for Reduced Keyboards Using Small Text Samples; Dept. Math & Comp. Sci.; Univ of Dundee, Dundee, Tayside, Scotland; AAC Augmentative and Alternative Communication; vol. 8, Sep. 1992; Copyright 1992 by ISAAC.

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

Chinese character handwriting recognition system does not yet have a rating. At this time, there are no reviews or comments for this patent.

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

Rate now

     

Profile ID: LFUS-PAI-O-3458987

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