Online signature verification using segment-level fuzzy modelling

This study presents a new online signature verification system based on fuzzy modelling of shape and dynamic features extracted from online signature data. Instead of extracting these features from a signature, it is segmented at the points of geometric extrema followed by the feature extraction and fuzzy modelling of each segment thus obtained. A minimum distance alignment between the two samples is made using dynamic time warping technique that provides a segment to segment correspondence. Fuzzy modelling of the extracted features is carried out in the next step. A user-dependent threshold is used to classify a test sample as either genuine or forged. The accuracy of the proposed system is evaluated using both skilled and random forgeries. For this, several experiments are carried out on two publicly available benchmark databases, SVC2004 and SUSIG. The experimental results obtained on these databases demonstrate the effectiveness of this system.