Title :
An Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verification
Author :
Nguyen, Vu ; Blumenstein, Michael
Author_Institution :
Sch. of Inf. & Commun. Technol., Griffith Univ., Gold Coast, QLD, Australia
Abstract :
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.
Keywords :
Gaussian processes; feature extraction; gradient methods; handwriting recognition; 2D Gaussian filter; chain code histogram; false acceptance rate; gradient feature; grid based feature extraction technique; modified direction feature; offline signature verification system; pattern recognition problems; random forgeries; signature contour; Feature extraction; Forgery; Histograms; Testing; Training; Vectors; Gaussian Grid feature; Gaussian filter; Gradient feature; Modified Direction Feature; Off-line signature verification; Support Vector Machines;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.76