On-line Handwritten Character Recognition System for Kannada using Principal Component Analysis Approach for Handheld Devices

被引:0
|
作者
Prasad, Keerthi G. [1 ]
Khan, Imran [1 ]
Chanukotimath, Naveen R. [1 ]
Khan, Firoz [1 ]
机构
[1] GM Inst Technol, Dept Informat Sci & Engn, Davanagere, India
来源
PROCEEDINGS OF THE 2012 WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES | 2012年
关键词
Online handwriting recognition; Character recognition; PCA; Pattern recognition; Handwriting recognition;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, we present an unrestricted Kannada online handwritten character recognizer which is viable for real time applications. It handles all basic characters of the Kannada script. In this paper, the proposed Online Handwritten Kannada Character Recognition System (OHKCRS) is discussed in detail. Developing an Online Handwriting Recognition System for Kannada character set to mobile devices would play an important role in making these devices available and usable for the Indian society as Kannada language is spoken in major part of India. In this paper, we present a model for writer-independent online handwriting character recognition for the 51 basic Kannada characters. The proposed system is implemented on mobile device using two different approaches namely Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW). To find the suitability of these two approaches for handheld devices several experiments were conducted and detailed analysis has been made on the obtained results. The results obtained for PCA approach is quite promising than DTW. On an average, recognition accuracy up to 88% is achieved for the PCA approach and up to 64% is achieved for DTW approach, also the time taken for recognition of unknown character is around 0.8 sec for PCA approach, and around 55 sec for DTW approach, thus the PCA approach is suitable for real-time applications.
引用
收藏
页码:675 / 678
页数:4
相关论文
共 50 条
  • [1] On-line Hindi Handwritten Character Recognition for Mobile Devices
    Prasad, Keerthi G.
    Khan, Imran
    Chanukotimath, Naveen
    PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI'12), 2012, : 1074 - 1078
  • [3] On-line Malayalam Handwritten Character Recognition using HMM and SVM
    Primekumar, K. P.
    Idiculla, Sumam Mary
    INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, IMAGE PROCESSING AND PATTERN RECOGNITION (ICSIPR 2013), 2013, : 322 - 326
  • [4] Offline Kannada Handwritten Character Recognition Using Convolutional Neural Networks
    Ramesh, G.
    Sharma, Ganesh N.
    Balaji, J. Manoj
    Champa, H. N.
    2019 5TH IEEE INTERNATIONAL WIE CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (WIECON-ECE 2019), 2019,
  • [5] A Line-Direction-Free and Character-Orientation-Free On-Line Handwritten Japanese Text Recognition System
    Hao, Yuechan
    Zhu, Bilan
    Nakagawa, Masaki
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2016, E99D (01): : 197 - 207
  • [6] An on-line handwritten Japanese text recognition system free from line direction and character orientation constraints
    Onuma, M
    Kitadai, A
    Zhu, BL
    Nakagawa, M
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2005, E88D (08): : 1823 - 1830
  • [7] Principal Component Analysis-Based Logistic Regression for Rotated Handwritten Digit Recognition in Consumer Devices
    Peng, Chao-Chung
    Huang, Chao-Yang
    Chen, Yi-Ho
    ELECTRONICS, 2023, 12 (18)
  • [8] The Hypercube Separation algorithm: A fast and efficient algorithm for on-line handwritten character recognition
    Ulgen, F
    Akamatsu, N
    Iwasa, T
    APPLIED INTELLIGENCE, 1996, 6 (02) : 101 - 116
  • [9] Large Improvement in Line-direction-free and Character-orientation-free On-line Handwritten Japanese Text Recognition
    Hao, Yuechan
    Zhu, Bilan
    Nakagawa, Masaki
    2014 14TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR), 2014, : 329 - 334
  • [10] Effects of Generating a Large Amount of Artificial Patterns for On-line Handwritten Japanese Character Recognition
    Chen, Bin
    Zhu, Bilan
    Nakagawa, Masaki
    11TH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR 2011), 2011, : 663 - 667