Detecting, Contextualizing and Computing Basic Mathematical Equations from Noisy Images using Machine Learning

Abstract

Various machine learning architectures including neural networks have been designed, developed and used to classify data. These networks have been used for Computer Vision, Speech Recognition and Natural Language Processing, to mention but a few and provide near accurate results. One of the major challenges faced in the area of mathematical equational recognition has been background information and noise. This paper presents a system that makes use of image processing and an artificial neural network to recognize, contextualize and compute mathematical equations from noisy images. The system attempts to overcome the challenges faced at segmentation and recognition stages.