A CURSIVE SCRIPT-RECOGNITION SYSTEM BASED ON HUMAN READING MODELS

被引:7
|
作者
BRAMALL, PE [1 ]
HIGGINS, CA [1 ]
机构
[1] UNIV NOTTINGHAM,DEPT COMP SCI,NOTTINGHAM NG7 2RD,ENGLAND
关键词
HANDWRITING RECOGNITION; CURSIVE SCRIPT RECOGNITION; ONLINE; READING MODELS; BLACKBOARD SYSTEM;
D O I
10.1007/BF01219590
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The human reading process is undoubtedly extremely complex; however, much work has been carried out in determining possible mechanisms behind it. A computer recognition system that makes use of some of the proposed models of human reading has been developed at the University of Nottingham. With it, we attempt to solve the problem of recognising handwriting on-line, The system, called NuScript, is based on the blackboard paradigm of artificial intelligence (AI). It initially uses easily extracted features to reduce a large lexicon to a smaller list of candidate words. Later stages use increasingly sophisticated knowledge sources, based on a diverse set of AI paradigms and other pattern-recognition techniques, to determine and subsequently refine a confidence value for each candidate. A description of the elements of the human recognition models on which the system is based is followed by a general description of the computer recognition system as a whole.
引用
收藏
页码:224 / 231
页数:8
相关论文
共 50 条
  • [41] The recognition graph - Language independent adaptable on-line cursive script recognition
    Sternby, J
    Friberg, C
    EIGHTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS 1 AND 2, PROCEEDINGS, 2005, : 14 - 18
  • [42] A Feature Refinement Patch Embedding-Based Recognition Method for Printed Tibetan Cursive Script
    Zhi, Cai Rang Dang
    Huang, Heming
    Fan, Yonghong
    Song, Dongke
    PATTERN RECOGNITION AND COMPUTER VISION, PRCV 2023, PT II, 2024, 14426 : 383 - 399
  • [43] A FUZZY-SYNTACTIC APPROACH TO ALLOGRAGH MODELING FOR CURSIVE SCRIPT RECOGNITION
    PARIZEAU, M
    PLAMONDON, R
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1995, 17 (07) : 702 - 712
  • [44] Cursive character recognition system
    Toscano, Karina
    Sanchez, Gabriel
    Nakano, Mariko
    Perez, Hector
    Yasuhara, Makoto
    CERMA2006: ELECTRONICS, ROBOTICS AND AUTOMOTIVE MECHANICS CONFERENCE VOL 2, PROCEEDINGS, 2006, : 62 - +
  • [45] Interactive Parts model: an application to recognition of on-line cursive script
    Neskovic, P
    Davis, PC
    Cooper, LN
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 13, 2001, 13 : 974 - 980
  • [46] The WuShu Database for Cursive Script Character and Style Recognition<bold> </bold>
    Shan, Xinrui
    Zhang, Kejun
    Shen, Lyukesheng
    Wang, Bolin
    2024 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS, ICMEW 2024, 2024,
  • [47] An Investigation for Cursive Context-Specific Printed Script Recognition Techniques
    Rafique, Humera
    Javid, Tariq
    2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023, 2023, : 393 - 402
  • [48] ONLINE CURSIVE SCRIPT RECOGNITION USING TIME-DELAY NEURAL NETWORKS AND HIDDEN MARKOV-MODELS
    SCHENKEL, M
    GUYON, I
    HENDERSON, D
    MACHINE VISION AND APPLICATIONS, 1995, 8 (04) : 215 - 223
  • [49] Knowledge-based English cursive script segmentation
    Xiao, XH
    Leedham, G
    PATTERN RECOGNITION LETTERS, 2000, 21 (10) : 945 - 954
  • [50] Augmenting the discrimination power of HMM by NN for on-line cursive script recognition
    Lee, SH
    Kim, JH
    APPLIED INTELLIGENCE, 1997, 7 (04) : 305 - 314