Multiple Classifier System for Offline Malayalam Character Recognition

被引：4
作者：
Chacko, Anitha Mary M. O. [1 ]
Dhanya, P. M. [1 ]
机构：
[1] Rajagiri Sch Engn & Technol, Dept Comp Sci & Engn, Kochi 682039, Kerala, India
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES, ICICT 2014 | 2015年 / 46卷
关键词：
Character Recognition; Gradient feature; Density feature; Multiple Classifier System; and Neural Networks;
D O I：
10.1016/j.procs.2015.01.061
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a multiple classifier system for the recognition of offline handwritten Malayalam characters. The features used are the gradient and density based features. These feature sets are fed as input to two feedforward neural networks. The results of both these neural networks are combined using four different combination schemes: Max rule, Sum rule, Product rule and Borda count method. The best combination ensemble with an accuracy of 81.82% is obtained by using the Product rule combination scheme. (C) 2015 The Authors. Published by Elsevier B.V.
引用
收藏
页码：86 / 92
页数：7
相关论文
共 50 条
  • [31] Ensemble Classifier with Dividing Training Scheme for Chinese Scene Character Recognition
    Jiang, Long
    Goto, Hideaki
    2017 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ), 2017,
  • [32] Odia Offline Typewritten Character Recognition using Template Matchingwith Unicode Mapping
    Panda, Smruti Rekha
    Tripathy, Jogeswar
    2015 International Symposium on Advanced Computing and Communication (ISACC), 2015, : 109 - 115
  • [33] Synthetic Scene Character Generator and Multi-Scale Voting Classifier for Japanese Scene Character Recognition
    Horie, Fuma
    Goto, Hideaki
    2018 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ), 2018,
  • [34] MULTIPLE CLASSIFIER COMBINATION FOR RECOGNITION OF WHEAT LEAF DISEASES
    Tian, Yuan
    Zhao, Chunjiang
    Lu, Shenglian
    Guo, Xinyu
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2011, 17 (05) : 519 - 529
  • [35] Offline Arabic Handwriting Recognition System based on HMM
    Xiang, Dong
    Yan, Huahua
    Chen, Xianqiao
    Cheng, Yanfen
    PROCEEDINGS 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, (ICCSIT 2010), VOL 1, 2010, : 526 - 529
  • [36] SVM and HMM classifier combination based approach for online handwritten indic character recognition
    Ghosh R.
    Kumar P.
    Recent Advances in Computer Science and Communications, 2020, 13 (02) : 200 - 214
  • [37] Application of SVM in Embedded Character Recognition System
    Tian Liyan
    Hu Xiaoguang
    Fei Peng
    ICIEA: 2009 4TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-6, 2009, : 1251 - 1255
  • [38] Character recognition using a rule based system
    Ganapathy, K
    Fernando, CG
    Davari, A
    MLMTA '05: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MACHINE LEARNING MODELS TECHNOLOGIES AND APPLICATIONS, 2005, : 104 - 110
  • [39] Character recognition system for pegon typed manuscript
    Ruldeviyani, Yova
    Suhartanto, Heru
    Sotardodo, Beltsazar Anugrah
    Fahreza, Muhammad Hanif
    Septiano, Andre
    Rachmadi, Muhammad Febrian
    HELIYON, 2024, 10 (16)
  • [40] Pest identification based on multiple classifier system
    Liu, Jinhua
    Han, Deqiang
    Yang, Yi
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 9535 - 9539
12345