An approach to offline Arabic Character recognition using neural networks

被引：0
|
作者：
Nawaz, SN [1 ]
Sarfraz, M [1 ]
Zidouri, A [1 ]
Al-Khatib, WG [1 ]
机构：
[1] King Fahd Univ Petr & Minerals, Dhahran 31261, Saudi Arabia
来源：
ICECS 2003: PROCEEDINGS OF THE 2003 10TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS, VOLS 1-3 | 2003年
关键词：
arabic character recognition; artificial neural networks; segmentation; feature extaction;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Character recognition system can contribute tremendously towards the advancement of automation process and can be useful in many other applications such as Data Entry, Check Verification etc. This paper presents a technique for the automatic recognition of Arabic Characters. The technique is based on Neural Pattern Recognition Approach. The main features of the system are preprocessing of the text, segmentation of the text to individual characters, Feature extraction using centralized moments technique and recognition using RBF Network. The system is implemented in Java Programming Language under Windows Environment. The System is designed for a single font multi size character set.
引用
收藏
页码：1328 / 1331
页数：4
相关论文
共 50 条
  • [1] An approach to offline Arabic character recognition using neural networks
    [J]. 1600, Emirates Telecommunications Corporation (ETISALAT); Etisalat College of Engineering (ECE); IEEE Circuits and Systems Society (CAS); Institute of Electrical and Electronics Engineers (IEEE); University of Sharjah (UOS) (Institute of Electrical and Electronics Engineers Inc., United States):
  • [2] Offline signature recognition using neural networks approach
    Karouni, Ali
    Daya, Bassam
    Bahlak, Samia
    [J]. WORLD CONFERENCE ON INFORMATION TECHNOLOGY (WCIT-2010), 2011, 3
  • [3] Offline Kannada Handwritten Character Recognition Using Convolutional Neural Networks
    Ramesh, G.
    Sharma, Ganesh N.
    Balaji, J. Manoj
    Champa, H. N.
    [J]. 2019 5TH IEEE INTERNATIONAL WIE CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (WIECON-ECE 2019), 2019,
  • [4] Offline Arabic character recognition system
    黄建华
    唐降龙
    [J]. Journal of Harbin Institute of Technology(New series), 2003, (01) : 80 - 88
  • [5] Arabic Character Recognition using Artificial Neural Networks and Statistical Analysis
    Sarhan, Ahmad M.
    Al Helalat, Omar I.
    [J]. PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 21, 2007, 21 : 32 - +
  • [6] Benchmarking on offline Handwritten Tamil Character Recognition using convolutional neural networks
    Kavitha, B. R.
    Srimathi, C.
    [J]. JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2022, 34 (04) : 1183 - 1190
  • [7] Domain and writer adaptation of offline Arabic handwriting recognition using deep neural networks
    Jemni, Sana Khamekhem
    Ammar, Sourour
    Kessentini, Yousri
    [J]. NEURAL COMPUTING & APPLICATIONS, 2022, 34 (03): : 2055 - 2071
  • [8] Domain and writer adaptation of offline Arabic handwriting recognition using deep neural networks
    Sana Khamekhem Jemni
    Sourour Ammar
    Yousri Kessentini
    [J]. Neural Computing and Applications, 2022, 34 : 2055 - 2071
  • [9] Arabic Handwritten Character Recognition Based on Convolution Neural Networks
    Bouchriha, Lamia
    Zrigui, Ahmed
    Mansouri, Sadek
    Berchech, Salma
    Omrani, Syrine
    [J]. ADVANCES IN COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2022, 2022, 1653 : 286 - 293
  • [10] Arabic Handwritten Character Recognition Based on Convolution Neural Networks
    Research Laboratory in Algebra, Numbers Theory and Intelligent Systems RLANTIS, Monastir University, Monastir, Tunisia
    不详
    不详
    94140, France
    [J]. Commun. Comput. Info. Sci., 2022, (286-293):
12345