This paper presents a multi-matcher on-line signature verification system which fuses the verification scores in pen-position parameter and pen-movement angle parameter at decision level. Features of pen-position and pen-movement angle are extracted by the sub-band decomposition using the discrete wavelet transform (DWT). In the pen-position, high frequency sub-band signals are considered as individual features to enhance the difference between a genuine signature and its forgery. On the other hand, low frequency sub-band signals are utilized as the features for suppressing the intra-class variation in the pen-movement angle. Verification is achieved by adaptive signal processing using the extracted features. Verification scores in the pen-position and the pen-movement angle are integrated by using a weighted sum rule to make a total decision. Experimental results show that fusion of pen-position and pen-movement angle can improve verification performance.
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