Structural and fuzzy techniques in the recognition of online Arabic characters

被引:9
作者
Bouslama, F [1 ]
机构
[1] Hiroshima City Univ, Fac Informat Sci, Asaminami Ku, Hiroshima 7313194, Japan
关键词
character recognition; Arabic letters; structural techniques; fuzzy linguistic features; fuzzy aggregation;
D O I
10.1142/S0218001499000574
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes a new hybrid approach for the automatic recognition of handwritten Arabic characters. The algorithm is based on structural techniques and fuzzy logic. Local features such as lines, curves, diacritic points are extracted from the geometry and topology of characters. Fuzzy linguistic variables are used to model the features and provide a suitable mean to vaguely describe the many styles and variations in the writing system. The combination of local features provide a natural way to describe characters in a compact style. Fuzzy if-then rules are used for classification. This hybrid technique is efficient for large and complex sets such as Arabic characters.
引用
收藏
页码:1027 / 1040
页数:14
相关论文
共 50 条
  • [31] SVM Model Selection Using PSO for Learning Handwritten Arabic Characters
    El Mamoun, Mamouni
    Mahmoud, Zennaki
    Kaddour, Sadouni
    CMC-COMPUTERS MATERIALS & CONTINUA, 2019, 61 (03): : 995 - 1008
  • [32] Arabic handwritten characters classification using Learning Vector Quantization algorithm
    Ali, Mohamed A.
    IMAGE AND SIGNAL PROCESSING, 2008, 5099 : 463 - 470
  • [33] Recognition-based Segmentation of Arabic Handwriting
    Elnagar, Ashraf
    Bentrcia, Rahima
    PATTERN RECOGNITION IN INFORMATION SYSTEMS, PROCEEDINGS, 2009, : 83 - 92
  • [34] ARASTI: A Database for Arabic Scene Text Recognition
    Tounsi, Maroua
    Moalla, Ikram
    Alimi, Adel M.
    2017 1ST INTERNATIONAL WORKSHOP ON ARABIC SCRIPT ANALYSIS AND RECOGNITION (ASAR), 2017, : 140 - 144
  • [35] A Novel Minimal Arabic Script for Preparing Databases and Benchmarks for Arabic Text Recognition Research
    Al-Muhtaseb, Husni A.
    Mahmoud, Sabri A.
    Qahwaji, Rami S.
    SIGNAL PROCESSING SYSTEMS, 2009, : 37 - +
  • [36] FPGA Based Neural Networks for Characters Recognition
    Ivanov, Stefan
    Stankov, Stanko
    Nenov, Toshko
    2018 20TH INTERNATIONAL SYMPOSIUM ON ELECTRICAL APPARATUS AND TECHNOLOGIES (SIELA), 2018,
  • [37] RECOGNITION AND SEGMENTATION OF CONNECTED CHARACTERS WITH SELECTIVE ATTENTION
    FUKUSHIMA, K
    IMAGAWA, T
    NEURAL NETWORKS, 1993, 6 (01) : 33 - 41
  • [38] Mixed neural - Traditional classifier for characters recognition
    Stajniak, A
    Szostakowski, J
    Skoneczny, S
    IMAGING SCIENCES AND DISPLAY TECHNOLOGIES, 1997, 2949 : 102 - 110
  • [39] Recognition of Devanagari characters using neural networks
    Keeni, K
    Shimodaira, H
    Nishino, T
    Tan, Y
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 1996, E79D (05) : 523 - 528
  • [40] Application of Geometry Rectification to Deformed Characters Recognition
    Wang, Liqun
    Fang, Honghui
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON ELECTRONIC, MECHANICAL, INFORMATION AND MANAGEMENT SOCIETY (EMIM), 2016, 40 : 1083 - 1088