Discrete fractional cosine transform based online handwritten signature verification

The new method for an online handwritten signature verification based on discrete fractional cosine transformation (DFrCT) for feature extraction is proposed. Various characteristics of the hand-written signature are used to extract different features of the signature. The system for the hand-written signature verification is realized by characterizing three FIR systems. The impulse responses of FIR systems are used to calculate Euclidean norm. The signature can be verified by evaluating the difference between the average of Euclidean norms of reference signatures and the Euclidean norm of signature to be verified. The equal error rate (EER) is calculated to compare the efficiency of the proposed method. It has been verified through simulation results that the DFrCT tool achieves much better results as compared to discrete cosine transform (DCT) for extracting the features. The signature verification experiment was performed on SVC2004 signature database.