Recognition of online handwritten mathematical expressions.
This paper aims at automatic understanding of online handwritten mathematical expressions (MEs) written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. Combination of two different classifiers have been used to achieve high accuracy for the recognition of symbols. Several online and offline features are used in the structural analysis phase to identify the spatial relationships among symbols. A context-free grammar has been designed to convert the input expressions into their corresponding T(E)X strings which are subsequently converted into MathML format. Contextual information has been used to correct several structure interpretation errors. A new method for evaluating performance of the proposed system has been formulated. Experiments on a dataset of considerable size strongly support the feasibility of the proposed system.
Garain
Utpal
U
Computer Vision and Pattern Recognition Unit of Indian Statistical Institute, Kolkata 108, India. utpal@isical.ac.in
Chaudhuri
B B
BB
D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D004282:Documentation / Q000379:methods; D001330:Electronic Data Processing / Q000379:methods*; D006236:Handwriting; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008390:Markov Chains; D008433:Mathematics; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D011932:Reading; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface