Search

This paper describes a method for separating online handwritten patterns into Japanese text, figures and mathematical formulas. Today, Tablet PCs and electronic whiteboards provide much larger writing area for pen interfaces unlike PDAs (Personal Digital Assistants), through which users can easily input text, write mathematical formulas and draw figures on the screen. The fact that these objects can be written by a single pen (marker) without switching the device, mode, software or whatever else, and without any writing restrictions such as grids or boxes is one of the most important benefits of the pen interfaces. However, the task of segmenting these objects is challenging. To address this issue, we have applied a probabilistic model employing stroke features, stroke crossings and stroke densities. Further, we partially apply the approach of segmentation by recognition. Although the current recognizer for formulas is not a true recognizer, we have achieved about 81% correct segmentation for all the strokes when applied to our newly prepared database of mixed patterns. This method has been compared with a neural-network. The results show that our method is generally better but less effective in distinguishing figures from other components. [ABSTRACT FROM AUTHOR]