A Progressive Structural Analysis Approach for Handwritten Chemical Formula Recognition
Peng Tang, Siu Cheung Hui, Chi‐Wing Fu · 2013
With the recent emergence of pen-based and touch based input devices such as Apple's iPad and Samsung's Galaxy Tablet, it has become more feasible now to input chemical formulas directly by handwriting, which is more natural and efficient than the traditional template-based input methods. In this paper, we propose an effective graph-based chemical structural analysis approach for online progressive handwritten chemical formula recognition. The proposed approach can progressively generate the recognition result after recognizing each symbol and users can make any corrections to the recognition result immediately. In addition, the proposed approach can recognize both cyclic and non-cyclic chemical structures. Recognizing cyclic structural formulas is challenging as bond orientations are very flexible and the relationships between symbols are much more complex than non-cyclic structural formulas. In this paper, the proposed chemical structural analysis approach and its promising performance results will be presented.