App for Evaluating Handwritten Mathematical Expressions

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App for Evaluating Handwritten Mathematical Expressions

OUTPUT


OVERVIEW

We propose to develop an Android app to recognize and evaluate handwritten mathematical expressions and equations. For our initial scope, we plan to focus on recognizing digits (0-9) and basic mathematical operators (+, -, x, and /), and displaying the computed result on the device’s viewfinder. This will be our primary goal. To accomplish this goal, we plan to explore different optical character recognition (OCR) algorithms, including the template matching algorithms we’ve seen in class. Since the app will run on a mobile device, our algorithm will need to tradeoff between performance and computational complexity.

If time permits, we would have several potential stretch goals to choose from. For example, we may add augmented reality features to the app. It would be interesting to overlay answers, error corrections, or incremental calculations onto the device’s viewfinder. We may also be able to identify and solve multiple expressions simultaneously. Finally, we may improve the app to recognize and evaluate a wider range of mathematical symbols and operators.

Potential References
Kato, Nei, et al. "A handwritten character recognition system using directional element feature and
asymmetric Mahalanobis distance." IEEE transactions on pattern analysis and machine intelligence 21.3(1999): 258-262.
Trier, Oivind Due, Anil K. Jain, and Torfinn Taxt. "Feature extraction methods for character recognition-a
survey." Pattern recognition 29.4 (1996): 641-662.
Heutte, Laurent, et al. "A structural/statistical feature based vector for handwritten character recognition."
Pattern recognition letters 19.7 (1998): 629-641.
Liu, Cheng-Lin, et al. "Handwritten digit recognition: benchmarking of state-of-the-art techniques." Pattern
Recognition 36.10 (2003): 2271-2285.
Zhang, Hao, et al. "SVM-KNN: Discriminative nearest neighbor classification for visual category recognition."
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06). Vol.

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