Title :
Distinguishing text from graphics in on-line handwritten ink
Author :
Bishop, Christopher M. ; Svensén, Markus ; Hinton, Geoffrey E.
Author_Institution :
Microsoft Res., Cambridge, UK
Abstract :
We present a system that separates text from graphics strokes in handwritten digital ink. It utilizes not just the characteristics of the strokes, but also the information provided by the gaps between the strokes, as well as the temporal characteristics of the stroke sequence. It is built using machine learning techniques that infer the internal parameters of the system from real digital ink, collected using a tablet PC.
Keywords :
handwriting recognition; image classification; image sequences; learning (artificial intelligence); text analysis; graphics stroke; machine learning; online handwritten digital ink; stroke sequence; tablet PC; text separation; Computer graphics; Computer science; Control systems; Data mining; Educational institutions; Engines; Ink; Machine learning; Personal digital assistants; Text recognition;
Conference_Titel :
Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on
Print_ISBN :
0-7695-2187-8
DOI :
10.1109/IWFHR.2004.34
