2013 12th International Conference on Document Analysis and Recognition (2007)
Curitiba, Parana, Brazil
Sept. 23, 2007 to Sept. 26, 2007
S. Watt , University of Western Ontario
B. Keshari , University of Western Ontario
Recognition of mathematical symbols is a challenging task, with a large set with many similar symbols. We present a support vector machine based hybrid recognition system that uses both online and offline information for classifica- tion. Probabilistic outputs from the two support vector ma- chine based multi-class classifiers running in parallel are combined by taking a weighted sum. Results from the exper- iments show that giving slightly higher weight to the on-line information produces better results. The overall error rate of the hybrid system is lower than that of both the online and offline recognition systems when used in isolation.
S. Watt, B. Keshari, "Hybrid Mathematical Symbol Recognition Using Support Vector Machines", 2013 12th International Conference on Document Analysis and Recognition, vol. 02, no. , pp. 859-863, 2007, doi:10.1109/ICDAR.2007.136