The partition-combination method for recognition of handwritten characters

被引:11
|
作者
Li, ZC [1 ]
Suen, CY
机构
[1] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung 80424, Taiwan
[2] Concordia Univ, Ctr Pattern Recognit & Machine Intelligence, Montreal, PQ H3G 1M8, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
character recognition; character models; model discrimination; OCR handprint recognition; classification; regional decomposition method; part combination;
D O I
10.1016/S0167-8655(00)00037-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The partition-combination method is a universal strategy for studying all sciences. This paper introduces such a strategy to handwritten character recognition, which is developed from our previous study. Let a pattern be split into sub-patterns, or called parts, bases, roots, etc. The easier part recognition is first carried out, then recognition of the entire pattern can be completed by integrating the results of part recognition. In this paper, the computational formulas for evaluating the recognition rates of parts and their combinations are derived, and a number of fascinating results have been reported. Many new combinations of parts have been found, leading to better recognition in practical applications. Numerical experiments have also been conducted using 89 patterns of the most frequently used alphanumeric handprints, leading to the discovery of several interesting aspects related to character recognition. Furthermore, human behavior in handwriting may be discovered based on the computational data obtained from the new algorithms. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:701 / 720
页数:20
相关论文
共 50 条
  • [21] On-Line Recognition of Handwritten Chinese Characters
    唐降龙
    刘家锋
    杨辉
    舒文豪
    Journal of Harbin Institute of Technology, 1997, (03) : 22 - 25
  • [22] Handwritten Numbers and English Characters Recognition System
    Li, Wei
    He, Xiaoxuan
    Tang, Chao
    Wu, Keshou
    Chen, Xuhui
    Yu, Shaoyong
    Lei, Yuliang
    Fang, Yanan
    Song, Yuping
    INTELLIGENT DATA ANALYSIS AND APPLICATIONS, (ECC 2016), 2017, 535 : 145 - 154
  • [23] A Handwritten Chinese Characters Recognition Method Based on Sample Set Expansion and CNN
    Song, Xuchen
    Gao, Xue
    Ding, Yanfang
    Wang, Zhixin
    2016 3RD INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2016, : 843 - 849
  • [24] Survey on Handwritten Characters Recognition in Deep Learning
    Malini, M.
    Hemanth, K. S.
    UBIQUITOUS INTELLIGENT SYSTEMS, 2022, 302 : 123 - 133
  • [25] A hierarchical approach to recognition of handwritten Bangla characters
    Basu, Subhadip
    Das, Nibaran
    Sarkar, Ram
    Kundu, Mahantapas
    Nasipuri, Mita
    Basu, Dipak Kumar
    PATTERN RECOGNITION, 2009, 42 (07) : 1467 - 1484
  • [26] ONLINE RECOGNITION OF HANDWRITTEN ISOLATED ARABIC CHARACTERS
    ELWAKIL, MS
    SHOUKRY, AA
    PATTERN RECOGNITION, 1989, 22 (02) : 97 - 105
  • [27] Fuzzy technique based recognition of handwritten characters
    Suresh, RM
    Arumugam, S
    FUZZY LOGIC AND APPLICATIONS, 2006, 2955 : 297 - 308
  • [28] Guided classification for Arabic Characters handwritten Recognition
    Fakhet, Walid
    El Khediri, Salim
    Zidi, Salah
    2022 IEEE/ACS 19TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2022,
  • [29] Feature selection in recognition of handwritten Chinese characters
    Zhang, LX
    Zhao, YN
    Yang, ZH
    Wang, JX
    2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 1158 - 1162
  • [30] Fuzzy recognition of offline handwritten numeric characters
    Batuwita, K. B. M. R.
    Bandara, G. E. M. D. C.
    2006 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2006, : 766 - +