By Giuseppe Pirlo, Donato Impedovo, Michael Fairhurst
Within the age of e-society, handwritten signature processing is an permitting know-how in a mess of fields within the electronic schedule of many nations, starting from e-health to e-commerce, from e-government to e-justice, from e-democracy to e-banking, and shrewdpermanent towns. Handwritten signatures are very advanced indicators; they're the results of an difficult approach that is determined by the psychophysical kingdom of the signer and the stipulations less than which the signature apposition technique happens. although, fresh efforts from academies and industries now make attainable the combination of signature-based applied sciences into different general apparatus to shape whole suggestions which are capable of help the safety specifications of present day society.
Advances in electronic Handwritten Signature Processing essentially presents an replace at the such a lot attention-grabbing and useful researches within the multifaceted box of handwritten signature research and processing. The chapters inside of additionally introduce and speak about severe points and necessary possibilities regarding using this know-how, in addition to spotlight basic theoretical and applicative points of the sphere.
This ebook includes papers through well-recognized and energetic researchers and scientists, in addition to via engineers and advertisement managers operating for big overseas businesses within the box of signature-based structures for quite a lot of purposes and for the improvement of e-society.
This book is dedicated to either researchers and specialists energetic within the box of biometrics and handwriting forensics, in addition to pros excited by the advance of signature-based strategies for complicated functions in drugs, finance, trade, banking, private and non-private administrations, and so on. Handwritten Signature Processing can also be used as a complicated textbook via graduate scholars.
Readership: pros, specialists & researchers within the fields of biometrics and signature-based technology/solutions; complicated graduate scholars.
Read or Download Advances in Digital Handwritten Signature Processing: A Human Artefact for e-Society PDF
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Extra info for Advances in Digital Handwritten Signature Processing: A Human Artefact for e-Society
For this data, the threshold can be chosen to be a more robust one. The pre-classifications based on PM , TPM and Tpd did not get any error rate improvements. In the cases of PM and TPM , this seems to be reasonable. The time at which the pressure is maximum TPM is probably an unstable feature, since people is not likely to be consistent in the time where the pen pressure reaches a peak. , making it hard to make pre-classification decisions based only on this feature. On the other hand, in the case of Tpd , the result was unexpected, since it is believed that forgers are not able to accurately reproduce the pen down time of the genuine writers.
Conf. (ISSNIP), pp. 1–6 (2013). J. Ziv. Coding theorems for individual sequences. IEEE. Trans. Inf. Theory, IT-24(4), pp. 405–412 (1978). S. Garcia-Salicetti, N. Houmani and B. Dorizzi. A novel criterion for writer enrolment based on a time-normalized signature sample entropy measure. EURASIP J. on Adv. in Sig. , 2009 (2009). CHAPTER 4 USING GLOBAL FEATURES FOR PRE-CLASSIFICATION IN ONLINE SIGNATURE VERIFICATION SYSTEMS* Marianela Parodi and Juan C. Gómez Lab. ar In this paper, a pre-classification stage based on global features is incorporated to an online signature verification system for the purposes of improving its performance.
Simon, J. Gonzalez, M. Faundez-Zanuy, V. Espinosa, A. Satue, I. Hermanez, J. J. Igarza, C. Vivaracho, D. Escudero and Q. I. Moro. MCYT baseline corpus: a bimodal biometric database. IEEE. Proc. , Sig. , 150(6), pp. 395–401 (2003). J. Canuto, B. Dorizzi and J. Montalvão. Dynamic Signatures Representation Using the Minimum Jerk Principle. In Proc 4th IEEE Biosig. Biorob. Conf. (ISSNIP), pp. 1–6 (2013). J. Ziv. Coding theorems for individual sequences. IEEE. Trans. Inf. Theory, IT-24(4), pp. 405–412 (1978).