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ICDAR
2005
IEEE

Mode detection in on-line pen drawing and handwriting recognition

9 years 5 months ago
Mode detection in on-line pen drawing and handwriting recognition
On-line pen input benefits greatly from mode detection when the user is in a free writing situation, where he is allowed to write, to draw, and to generate gestures. Mode detection is performed before recognition to restrict the classes that a classifier has to consider, thereby increasing the performance of the overall recognition. In this paper we present a hybrid system which is able to achieve a mode detection performance of 95.6% on seven classes; handwriting, lines, arrows, ellipses, rectangles, triangles, and diamonds. The system consists of three kNN classifiers which use global and structural features of the pen trajectory and a fitting algorithm for verifying the different geometrical objects. Results are presented on a significant amount of data, acquired in different contexts like scribble matching and design applications.
Don Willems, Stéphane Rossignol, Louis Vuur
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDAR
Authors Don Willems, Stéphane Rossignol, Louis Vuurpijl
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