Offline signature verification via structural methods : graph edit distance and inkball models

Maergner, Paul (Department of Informatics, University of Fribourg, Fribourg, Switzerland) ; Howe, Nicholas R. (Department of Computer Science, Smith College, Northampton, Massachusetts, USA) ; Riesen, Kaspar (Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland) ; Ingold, Rolf (Department of Informatics, University of Fribourg, Fribourg, Switzerland) ; Fischer, Andreas (School of Engineering and Architecture (HEIA-FR), HES-SO // University of Applied Sciences Western Switzerland)

For handwritten signature verification, signature images are typically represented with fixed-sized feature vectors capturing local and global properties of the handwriting. Graphbased representations offer a promising alternative, as they are flexible in size and model the global structure of the handwriting. However, they are only rarely used for signature verification, which may be due to the high computational complexity involved when matching two graphs. In this paper, we take a closer look at two recently presented structural methods for handwriting analysis, for which efficient matching methods are available: keypoint graphs with approximate graph edit distance and inkball models. Inkball models, in particular, have never been used for signature verification before. We investigate both approaches individually and propose a combined verification system, which demonstrates an excellent performance on the MCYT and GPDS benchmark data sets when compared with the state of the art.

Conference Type:
full paper
Ingénierie et Architecture
iCoSys - Institut des systèmes complexes
Niagara Falls, USA, 5-8 August 2018
Niagara Falls, USA
5-8 August 2018
6 p.
Published in:
Proceedings of ICFHR 2018, the 16th International Conference on Frontiers in Handwriting Recognition, 5-8 August 2018, Niagara Falls, USA
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 Record created 2019-02-26, last modified 2020-10-27

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