Handwritten Document Editor: An Approach
Keywords:
K-NN classifier, Handwriting Recognition, Genetic Algorithm, Contour Tracing, Marching Squares Algorithm,, Image ProcessingAbstract
With advancement in new technologies many individuals are moving towards personalization of the same. The same idea inspired us to develop a system which can provide a personal touch to all our documents including both electronic and paper media. In this article we are proposing a novel idea for creating an editor system which will take handwritten scanned document as the input, recognizes the characters from the document, then proceed with creating the font of recognized handwriting to allow user to edit the document. We have proposed use of genetic algorithm along with K-NN classifier for fast recognition of handwritten characters and use of marching squares algorithm for tracing contour points of characters to generate a handwritten font.
References
Yonghong Song, Guilin Xiao, Yuanlin Zhang, Lei Yang, Liuliu Zhao, “A Handwritten Character Extraction Algorithm for Multi-language Document Image”, International Conference on Document Analysis and Recognition 2011.
Rahul Kala, Harsh Vazirani, Anupam Shukla, Ritu Tiwari, “Offline Handwritten Recognition using Genetic Algorithm”, IJCSI Vol. 7, Issue. 2, March 2010.
S. Impedovo, F. M. Mangini, “A Novel Technique For Handwritten Digit Classification using Genetic Clustering”, International Conference on Frontiers in Handwriting Recognition, 2012.
Vijay Patil, Sanjay Shimpi, “Handwritten English character recognition using neural network”, Elixir International Journal, 2011.
Maple, C. " Geometric design and space planning using the marching squares and marching cube algorithms". Proc. 2003 International Conference Geometric Modeling and Graphics: 90–95.
A. M. Baumberg & D. C. Hogg, “An Efficient Method for Contour Tracking using Active Shape Models”, University of Leeds, School of Computer Studies Research Report Series, Report 94.11.
H. Zhang, A. Berg, M. Maire, and J. Malik, “SVMKNN: Discriminative nearest neighbor classification for visual category recognition”, in Proc.CVPR, 2006.
R. R. Sokal and C. D. Michener, “A statistical method for evaluating systematic relationships”, University of Kansas Scientific Bulletin 38, 1958, pp. 1409-1438.
D. Beasley, D.R. Bull, R.R. Martin, “An Overview of Genetic Algorithms: Part 1, Fundamentals”, University Comput. ,Vol 15,n.2, 1993, pp. 58-69.
S. Impedovo, G. Pirlo, R. Modugno, A. Ferrante, “Zoning Methods for Handwritten Character Recognition: An Overview”, Proc. 12th ICFHR, Kolkata ( India ), 16-18 Nov. 2010, pp. 329-334.
N. Otsu. “A Threshold Selection Method from GrayLevel Histograms”, IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1): 62-66.
Sumedha B. Hallale, Geeta D. Salunke, “Twelve Directional Feature Extraction for Handwritten English Character Recognition”, International Journal of Recent Technology and Engineering, Vol 2, Issue 2, May 2013.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2014 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
