Browse by author
Lookup NU author(s): Dr Thomas Ploetz
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
A domain where, even in the era of electronic document processing, hand-writing is still widely used is note-taking on a whiteboard. Such documents are eithercaptured by a pen-tracking device or - which is much more challenging - by a camera. In both cases the layout analysis of realistic whiteboard notes is an open researchproblem. In this paper we propose a camera-based three-stage approach for the automatic layout analysis of whiteboard documents. Assuming a reasonable foreground-backgroundseparation of the handwriting it starts with a locally adaptive binarization followed byconnected component extraction. The latter are then automatically classified as representing either simple graphical elements of a mindmap or elementary text patches. Inthe final stage the text patches are subject to a clustering procedure in order to generate hypotheses for those image regions where textual annotations of the mindmap canbe found. In order to demonstrate the effectiveness of the proposed approach we report results of a writer independent experimental evaluation on a data set of mindmap images created by several different writers without any constraints on writing or drawing style. © J.UCS.
Author(s): Vajda S, Ploetz T, Fink G
Publication type: Article
Publication status: Published
Journal: Journal of Universal Computer Science
ISSN (print): 0948-695X
ISSN (electronic): 0948-6968
Publisher: Technische Universitaet Graz
Altmetrics provided by Altmetric