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Reseach Article

Segmentation of Offline Printed and Handwritten Mathematical Expressions

Published on August 2016 by Manisha Bharambe
National Conference on Digital Image and Signal Processing
Foundation of Computer Science USA
NCDISP2016 - Number 2
August 2016
Authors: Manisha Bharambe
40f0c581-a460-4a2a-9837-0d78c393d854

Manisha Bharambe . Segmentation of Offline Printed and Handwritten Mathematical Expressions. National Conference on Digital Image and Signal Processing. NCDISP2016, 2 (August 2016), 1-5.

@article{
author = { Manisha Bharambe },
title = { Segmentation of Offline Printed and Handwritten Mathematical Expressions },
journal = { National Conference on Digital Image and Signal Processing },
issue_date = { August 2016 },
volume = { NCDISP2016 },
number = { 2 },
month = { August },
year = { 2016 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /proceedings/ncdisp2016/number2/25852-1635/ },
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 Segmentation of Offline Printed and Handwritten Mathematical Expressions
%J National Conference on Digital Image and Signal Processing
%@ 0975-8887
%V NCDISP2016
%N 2
%P 1-5
%D 2016
%I International Journal of Computer Applications
Abstract

Mathematical expression recognition is an active research field and it becomes a challenging problem in the field of Optical character recognition. The fundamental problem of mathematical expression recognition system is the Off-line Printed expression recognition. One of the difficulties of handwritten mathematical symbol recognition lies in the variability of the symbols, different fonts in addition to the recognition of other language characters. The segmentation is the most important phase in the recognition of the expression. This paper deals with efficient segmentation technique to segment logical mathematical expressions with subscripts. In this paper, the database of 288 printed expressions and 960 handwritten expressions using logical symbols was developed. The proposed algorithm was tested on the handwritten and the printed expression database and the results are quite promising.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Optical Character Recognition Printed And Handwritten Logical Mathematical Expressions Segmentation.