DocumentCode
2028956
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
fYear
2004
fDate
26-29 Oct. 2004
Firstpage
142
Lastpage
147
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers in Handwriting Recognition, 2004. IWFHR-9 2004. Ninth International Workshop on
ISSN
1550-5235
Print_ISBN
0-7695-2187-8
Type
conf
DOI
10.1109/IWFHR.2004.34
Filename
1363901
Link To Document