Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

An Approach for Recognition and Interpretation of Mathematical Expressions in Printed Document

B.B. Chaudhuri1 and U. Garain1

(1)  Computer Vision & Pattern Recognition Unit, Indian Statistical Institute, Calcutta, India, IN
Abstract:  In this paper, we propose an approach for understanding Mathematical Expressions (MEs) in a printed document. The system is divided into three main components: (i) detection of MEs in a document; (ii) recognition of the symbols present in each ME; and (iii) arrangement of the recognised symbols. The MEs printed in separate lines are detected without any character recognition whereas the embedded expressions (mixed with normal text) are detected by recognising the mathematical symbols in text. Some structural features of the MEs are used for both cases. The mathematical symbols are grouped into two classes for convenience. At first, the frequently occurring symbols are recognised by a stroke-feature analysis technique. Recognition of less frequent symbols involves a hybrid of feature-based and template-based technique. The bounding-box coordinates and the size information of the symbols help to determine the spatial relationships among the symbols. A set of predefined rules is used to form the meaningful symbol groups so that a logical arrangement of the mathematical expression can be obtained. Experiments conducted using this approach on a large number of documents show high accuracy.

Keywords:Document; Mathematical Expression; OCR; Symbol arrangement; Symbol recognition


Fulltext Preview (Small, Large)
Image of the first page of the fulltext


Export this article
Export this article as RIS | Text
 
Referenced by
2 newer articles

  1. ALY, Walaa (2009) Automatic Classification of Spatial Relationships among Mathematical Symbols Using Geometric Features. IEICE Transactions on Information and Systems e92-d(11)
    [CrossRef]
  2. Su Yang (2005) Symbol recognition via statistical integration of pixel-level constraint histograms: a new descriptor. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(2)
    [CrossRef]
Remote Address: 38.107.191.99 • Server: mpweb18
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)