Off-Line signature verification based on directional gradient spectrum and a fuzzy classifier

Authors:
Young Woon Woo;Soowhan Han;Kyung Shik Jang
Affiliations:
Department of Multimedia Engineering, Dong-Eui University, Pusan, Korea;Department of Multimedia Engineering, Dong-Eui University, Pusan, Korea;Department of Multimedia Engineering, Dong-Eui University, Pusan, Korea
Venue:
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Year:
2006

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Abstract

In this paper, a method for off-line signature verification based on spectral analysis of directional gradient density function and a weighted fuzzy classifier is proposed. The well defined outline of an incoming signature image is extracted in a preprocessing stage which includes noise reduction, automatic thresholding, image restoration and erosion process. The directional gradient density function derived from extracted signature outline is highly related to the overall shape of signature image, and thus its frequency spectrum is used as a feature set. With this spectral feature set, having a property to be invariant in size, shift, and rotation, a weighted fuzzy classifier is evaluated for the verification of freehand and random forgeries. Experiments show that less than 5% averaged error rate can be achieved on a database of 500 samples including signature images written by Korean letters as well.