Handwritten Equation Solver: A Game-Changer in Mathematical Problem Solving

Handwriting is something which changes from person to person. Finding two people with same handwriting isn’t an easy job and not everyone can recognize all kinds of writing. But, in the growing era of technology and the modern world with the introduction of the domains like OpenCV – image processing and recognition isn’t a tough job. Further, with the growing dependency on technology and the ease of access, students can now solve equations at the comfort of their home. The job is simple, one just has to click picture of a problem written on the page, scan it, and the algorithm does it job. The system can recognize various handwritings and works on a large dataset. This Handwritten Equation Solver system, will aim towards dealing with various handwritings and solving equations with aiming towards the maximum possible accuracy that could be achieved using the various techniques and to find out the most appropriate out of all the proposed techniques. In this study, we initially take a binary image convert it into binary format using preprocessing and eliminating the noise. We use different segmentation and classification techniques have been used to find out the most accurate technique that will give the maximum possible accuracy. We found out that the highest accuracy came in K-Means segmentation and KNN classification technique which are 92.714 and 92.857% respectively. The proposed methodology uses all the techniques of OpenCV.