An Analysis of Mathematical Expression Recognition Techniques

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Published: Jun 23, 2017
DOI: https://doi.org/10.26483/ijarcs.v8i5.3846
Keywords:
ANN, HOG (Histogram of Oriented Gradients), KNN, math recognition system, SVM, segmentation, WNN

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Nailah Afshan
Jamia Hamdard

Abstract

The field of mathematics is very important with its applications in every aspect of science in general and engineering in particular. Mathematical expressions form a vital component of mathematical literature. Consequently, recognition of mathematical expressions has become a highly active and challenging research area nowadays having great practical significance. Different concepts from pattern recognition and digital image processing are utilised for the accomplishment of classification and recognition of mathematical expressions. The main task involved is the automatic recognition of different mathematical symbols. Several classification approaches have been used on different databases under different experimental conditions resulting in different performances and classification accuracies. In this paper, a review of different techniques of mathematical expression recognition is presented.

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Vol. 8 No. 5 (2017): May-June 2017
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