Grouping text lines in freeform handwritten notes

Handwritten text lines are prominent structures in freeform digital ink notes and their reliable detection is the foundation to a natural and intelligent interface for note editing and repurposing. This paper presents an optimization method for text line grouping. The global´cost function is designed to find the simplest stroke partitioning to maximize the likelihood of the resulting lines and the consistency of their configuration. A dynamic programming algorithm provides an initial segmentation of the time-ordered stroke sequence. Then a local gradient-descent algorithm iteratively evaluates splitting and merging hypotheses to minimize the global cost function. On average, the proposed technique processes each note page in less than a second at 90% accuracy.