Linking Broken Characters in Online Handwritten Chemical Formulas
Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference（2009）
Abstract
In this paper, we present an effective approach to link the broken characters in online handwritten chemical formulas. By observing a large number of formula samples, we classify the common broken problems in online handwritten chemical formulas into three types, ldquopoint-likerdquo broken type, liner-type and arc-type. The proposed method combines the strokes characteristic of handwritten chemical characters, online information and structural characteristics of chemical formulas. The main process can be divided into three stages: preprocessing, location of broken strokes and linking. Experiment results indicate that the proposed method can not only satisfy the real-time demand, but also achieve a high linking accuracy of 94.0%.
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Key words
effective approach,broken character linking,online handwritten chemical formulas,chemistry computing,online handwritten chemical formula,pattern classification,online information,common broken problem,handwritten chemical character,broken,handwritten character recognition,arc-type stroke,chemical formula,broken type,broken characters,broken character,broken stroke,point-like broken stroke,liner-type stroke,data mining,real time,noise,chemicals,handwriting recognition,probability density function,satisfiability,spline
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