Abstract
With the growing popularity of pen-based and touch-based devices such as Apple's iPad and Samsung's Galaxy Tablet, handwriting has become an important input method. Although handwriting recognition for text contents and mathematical formulae are well-supported in these devices, recognizing handwritten chemical expressions is still very challenging due to its complex spatial structure. In this research, we focus on chemical symbol recognition which is essential for accurate handwritten chemical expression recognition. In particular, we propose an online hybrid Support Vector Machine - Elastic Matching (SVM-EM) approach for handwritten chemical symbol recognition. Based on the proposed chemical symbol recognition approach and an online structural analysis, we have implemented an online handwritten chemical expression recognition system on Apple's iOS platform. In this paper, we present our proposed SVM-EM approach for handwritten chemical symbol recognition and evaluate it with several users to verify its promising performance as a real application.
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