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Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2
Writer Identification Using Edge-Based Directional Features
Edinburgh, Scotland
August 03-August 06
ISBN: 0-7695-1960-1
Marius Bulacu, Groningen University
Lambert Schomaker, Groningen University
Louis Vuurpijl, Nijmegen University
This paper evaluates the performance of edge-based directional probability distributions as features in writer identification in comparison to a number of non-angular features. It is noted that the joint probability distribution of the angle combination of two "hinged" edge fragments outperforms all other individual features. Combining features may improve the performance. Limitations of the method pertain to the amount of handwritten material needed in order to obtain reliable distribution estimates. The global features treated in this study are sensitive to major style variation (upper- vs lower case), slant, and forged styles, which necessitates the use of other features in realistic forensic writer identification procedures.
Citation:
Marius Bulacu, Lambert Schomaker, Louis Vuurpijl, "Writer Identification Using Edge-Based Directional Features," icdar, vol. 2, pp.937, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003
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