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Reseach Article

Recognition of Offline Handwritten Mathematical Expressions

Published on April 2015 by Manisha Bharambe
National conference on Digital Image and Signal Processing
Foundation of Computer Science USA
DISP2015 - Number 2
April 2015
Authors: Manisha Bharambe
3301450d-284f-4c03-88dc-0fc0d0392ad4

Manisha Bharambe . Recognition of Offline Handwritten Mathematical Expressions. National conference on Digital Image and Signal Processing. DISP2015, 2 (April 2015), 35-39.

@article{
author = { Manisha Bharambe },
title = { Recognition of Offline Handwritten Mathematical Expressions },
journal = { National conference on Digital Image and Signal Processing },
issue_date = { April 2015 },
volume = { DISP2015 },
number = { 2 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 35-39 },
numpages = 5,
url = { /proceedings/disp2015/number2/20488-3021/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National conference on Digital Image and Signal Processing
%A Manisha Bharambe
%T Recognition of Offline Handwritten Mathematical Expressions
%J National conference on Digital Image and Signal Processing
%@ 0975-8887
%V DISP2015
%N 2
%P 35-39
%D 2015
%I International Journal of Computer Applications
Abstract

Recognition of Handwritten Mathematical Expression (ME) is one of the most fascinating and challenging research area in the field of Image Processing and Pattern Recognition. The recognition of handwritten mathematical expression is difficult due to variability of the symbols in an expression and its two Dimensional structure. This paper deals with the recognition of handwritten logical mathematical expressions. The strength of the proposed approach is efficient preprocessing, feature extraction and segmentation methods .

References
  1. Ahmad Moritaser Awal, Harold Mouchere Christian Viard Gaudin. Towards Handwritten Mathematical Expression recognition. IEEE 978- 07095, 2009.
  2. Ahmad Montaser Awal, Harold Mouchere, Christian Viard Gaudin. The problem of handwritten mathematical expression recognition. ISBN, 978-0- 7695-4221-8,2010.
  3. Christopher Malon, Seiichi Uchid, Masakazu Suzuki, Mathematical symbol recognition with support vector machines, Pattern Recognition Letters 29 (2008) 1326–1332, Elsevier.
  4. Hans Jurgen Winkler and Manfred Lang. On-Line Symbol segmentation and recognition in handwritten mathematical expressions. 0-8186- 7919-0/97,IEEE
  5. Harold Mouch`ere_, hristian Viard-Gaudin_Richard Zanibbiy, Utpal Garainz, Dae Hwan Kimx and Jin Hyung Kimx, ICDAR 2013 CROHME:Third International Competition on Recognition of Online Handwritten Mathematical Expressions,
  6. His-Jian Lee And J. Wang. Design of a mathematical expression recognition system, 0- 8186-7128-9/95,IEEE
  7. Kang kim, Taik Rhee, Jae LEE. Utilizing consistency context for handwritten mathematical expression recognition. 978-0-7695-3725-2/2009 IEEE.
  8. Kazuki Ashida, Masayuki Okamoto, Hiroki Imai, Performance Evaluation of a Mathematical Formula Recognition System with a large scale of printed formula images, Proceedings of the Second International Conference on Document Image, Analysis for Libraries (DIAL'06),0-7695-2531-8/06, 2006 IEEE
  9. Lei Gao, Shulin Pan, Shen Jiao, An Analytic Hierarchy Process Based Method To Process Mathematical Expressions, Journal Of Theoretical And Applied Information Technology 31st January 2013. Vol. 47 No. 3, Issn: 1992-8645
  10. M. Padmanaban, E. A. Yfantis. Handwritten character recognition using conditional probabilities.
  11. Qi Xiangwei Pan Weimin Yusup Wang Yang, The study of structure analysis strategy in handwritten recognition of general mathematical expression, International Forum on Information Technology and Applications, 978-0-7695-3600-2/09, 2009 IEEE
  12. Sanjay S. Gharde, Baviskar Pallavi, V K. P. Adhiya, Evaluation of Classification and Feature Extraction Techniques for Simple Mathematical Equations, International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 1– No. 5, February 2012.
  13. Stephen M. Watt Xiaofang Xie, Prototype Pruning by Feature Extraction for Handwritten Mathematical Symbol Recognition,Department of Computer Science, University of Western Ontario,Canada
  14. Utpal Garain, B. B. Chaudhuri, R. P. Ghosh, A Multiple- Classifier System for Recognition of Printed Mathematical Symbols, Proceedings of the 17th International Conference on Patter Recognition (ICPR'04), 1051-4651/04 , IEEE.
  15. Xue-Dong Tian, Hai-Yan Li, Xin-Fu Li. Research on symbol recognition for mathematical expressions, 0-7695- 2616-0/2006 ,IEEE.
  16. Xie,Xiaofang. On the recognition of handwritten mathematical symbols. Proquest NR39341,2008
  17. Taik HeonRhee, JinHyungKim , Efficient search strategy in structural analysis for handwritten mathematical expression recognition, pattern recognition (ScienceDirect)0031-32,2009 Elsevier
  18. Francisco Álvaro, Richard Zanibbi, A Shape-Based Layout Descriptor for Classifying Spatial Relationships in Handwritten Math, 2013 ACM 978-1-4503-1789/4/13/09
  19. Sanjay S. Garde, Pallavi V. Baviskar, K. P. Adhiya, Identification of Handwritten Simple Mathematical Equation Based on SVM and Projection Histogram, International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231- 2307, Volume-3, Issue-2, May 2013
  20. Anita Jindal,Renu Dhir,Rajneesh Rani, Diagonal Features and SVM classifier for Handwritten Gurumukhi Character recognition, International Journal of Advance Reasearch in Computer science and software engineering, Vol 2, Issue 5, May 2012.
  21. G. G. Rajput, S. M. Mali, Marathi Handwritten Numeral Recognition using Fourier Discropters and Normalized Chain code, IJCA, Special issue ITRPPR, 2010
Index Terms

Computer Science
Information Sciences

Keywords

Pattern Recognition Handwritten Logical Mathematical Expression Preprocessing Feature Extraction Segmentation