Fusion of Local and Regional Approaches for On-Line Signature Verification
Function-based methods for on-line signature verification are studied. These methods are classified into local and regional depending on the features used for matching. One representative method of each class is selected from the literature. The selected local and regional methods are based on Dynamic Time Warping and Hidden Markov Models, respectively. Some improvements are presented for the local method aimed at strengthening the performance against skilled forgeries. The two methods are compared following the protocol defined in the Signature Verification Competition 2004. Fusion results are also provided demonstrating the complementary nature of these two approaches.
KeywordsHide Markov Model Regional Approach Dynamic Time Warping Training Signature False Acceptance Rate
Unable to display preview. Download preview PDF.
- 2.Plamondon, R., Srihari, S.N.: On-line and off-line handwriting recognition: A comprehensive survey. IEEE Trans. on PAMI 22, 63–84 (2000)Google Scholar
- 5.Kashi, R.S., Hu, J., Nelson, W.L., Turin, W.: On-line handwritten signature verification using Hidden Markov Model features. In: Proc. of ICDAR, pp. 253–257 (1997)Google Scholar
- 7.Fierrez-Aguilar, J., Nanni, L., Lopez-Penalba, J., Ortega-Garcia, J., Maltoni, D.: An on-line signature verification system based on fusion of local and global information. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 523–532. Springer, Heidelberg (2005)CrossRefGoogle Scholar
- 19.Krawczyk, S.: User authentication using on-line signature and speech. Master’s thesis, Michigan State University, Dep. of Computer Science and Engineering (2005)Google Scholar
- 20.Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. Pattern Recognition (2005) (to appear) Google Scholar
- 22.Martin, A., et al.: The DET curve in assessment of decision task performance. In: Proc. of EuroSpeech, pp. 1895–1898 (1997)Google Scholar