Handwritten Mathematical Expression
recognition and grading system is a challenging task in the
field of pattern recognition. A lot of researchers have
already worked on Handwritten Mathematical Expression
recognition and have used various classifiers. In past,
Convolutional Neural Network, also called CNN, has been
highly used for recognizing patterns. In this paper, We
propose an idea to recognize HME and evaluate offline
using CNN for classification. The steps included are, first
the worksheet is scanned and is sent to the work-spaces
detection module where it will return all the rectangular
work-spaces from the given worksheet, then the workspaces are sent to the line extraction module to extract all
the lines. The extracted lines are then passed to the
character segmentation module where it will segment the
character and then characters will be classified using deep
learning model DCCNN. Finally, the evaluation module will
assess the line and draw a green/red bounding box
depending on whether the line is correct or not.