An application of the 2D Gaussian filter for enhancing feature extraction in off-line signature verification

Publication Type:
Conference Proceeding
Citation:
Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2011, pp. 339 - 343
Issue Date:
2011-11-03
Full metadata record
Files in This Item:
Filename Description Size
06065331.pdfPublished version252.89 kB
Adobe PDF
Similar to many other pattern recognition problems, feature extraction contributes significantly to the overall performance of an off-line signature verification system. To be successful, a feature extraction technique must be tolerant to different types of variation whilst preserving essential information of input patterns. In this paper, we describe a grid-based feature extraction technique that utilises directional information extracted from the signature contour, i.e. the chain code histogram. Our experimental results for signature verification indicated that, by applying a suitable 2D Gaussian filter on the matrices containing the chain code histograms, an average error rate (AER) of 13.90% can be obtained whilst maintaining the false acceptance rate (FAR) for random forgeries as low as 0.02%. These figures are comparable or better than those reported by other state of the art feature extraction techniques such as the Modified Direction Feature (MDF) and the Gradient feature. © 2011 IEEE.
Please use this identifier to cite or link to this item: