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Writer Recognition by Combining Local and Global Methods

  • The research project "Herbar Digital" was started in 2007 with the aim to digitize 3.5 million dried plants on paper sheets belonging to the Botanic Museum Berlin in Germany. Frequently the collector of the plant is unknown, so a procedure had to be developed in order to determine the writer of the handwriting on the sheet. In the present work the static character was transformed into a dynamic form. This was done with the model of an inert ball which was rolled along the written character. During this off-line writer recognition, different mathematical procedures were used such as the reproduction of the write line of individual characters by Legendre polynomials. When only one character was used, a recognition rate of about 40% was obtained. By combining multiple characters, the recognition rate rose considerably and reached 98.7% with 13 characters and 93 writers (chosen randomly from the international IAM-database [3]). A global statistical approach using the whole handwritten text resulted in a similar recognition rate. By combining local and global methods, a recognition rate of 99.5% was achieved.

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Author:Karl-Heinz SteinkeGND, Martin Gehrke, Robert Dzido
Document Type:Conference Proceeding
Year of Completion:2009
Publishing Institution:Hochschule Hannover
Release Date:2009/11/24
Tag:Erkennungssoftware; OCR
Herbar Digital; Recognition software
GND Keyword:Herbarium; Angewandte Botanik; Gepresste Pflanzen; Digitalisierung; Virtualisierung
Source:International Congress on Image and Signal Processing, Tianjin China, October 2009
Link to catalogue:613575695
Institutes:Fakult├Ąt I - Elektro- und Informationstechnik
DDC classes:004 Informatik
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung 3.0