Advances in Digital Handwritten Signature Processing: A by Giuseppe Pirlo, Donato Impedovo, Michael Fairhurst PDF

By Giuseppe Pirlo, Donato Impedovo, Michael Fairhurst

ISBN-10: 9814579629

ISBN-13: 9789814579629

Within the age of e-society, handwritten signature processing is an permitting know-how in a mess of fields within the electronic time table 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 complicated symptoms; they're the results of an complex strategy that depends upon the psychophysical nation of the signer and the stipulations below which the signature apposition strategy happens. although, fresh efforts from academies and industries now make attainable the mixing of signature-based applied sciences into different average gear to shape whole ideas which are capable of aid the protection specifications of trendy society.

Advances in electronic Handwritten Signature Processing essentially presents an replace at the such a lot interesting and worthy researches within the multifaceted box of handwritten signature research and processing. The chapters inside additionally introduce and speak about severe features and priceless possibilities relating to using this expertise, in addition to spotlight primary theoretical and applicative points of the sector.

This publication comprises papers by way of well-recognized and lively researchers and scientists, in addition to via engineers and advertisement managers operating for giant foreign businesses within the box of signature-based structures for a variety of purposes and for the advance of e-society.

This e-book is dedicated to either researchers and specialists lively within the box of biometrics and handwriting forensics, in addition to pros interested by the improvement of signature-based recommendations for complex functions in medication, finance, trade, banking, private and non-private administrations, and so forth. Handwritten Signature Processing can also be used as a sophisticated textbook by means of graduate scholars.

Readership: execs, specialists & researchers within the fields of biometrics and signature-based technology/solutions; complex graduate scholars.

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Extra info for Advances in Digital Handwritten Signature Processing: A Human Artefact for e-Society

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3. Feature Extraction Typically, the measured data consists of three discrete time functions: pen coordinates x and y, and pressure p. 4,9 Previous to the feature extraction, the original pen coordinates are normalized regarding scale and translation. 1. Global based features Several global based features can be extracted from the measured and extended time functions. These features should be selected to be discriminative enough in order for the proposed pre-classification to be succesful. The following global based features, corresponding to the better ranked ones by feature selection performed in the literature,4,5 are used in this paper: signature total time duration T, pen down duration Tpd, positive x velocity duration Tvx, average pressure P , maximum pressure PM and the time at which the pressure is maximum TPM.

In way of principle, one would expect that the same stability region appear in all the signatures of a subject, and therefore would define the stability region of a set of signatures as the longest common subsequences of the stability regions computed for every available pair of signatures. In practice, however, both the stroke segmentation and the ink matching may introduce errors in locating the segmentation points and/or in deciding when a sequence of strokes is similar to another, that may produce different stability regions for the set of signatures.

K. Chung. Using geometric extrema for segment-to-segment characteristics comparison in online signature verification. Pat. , 37, pp. 93–103 (2004). T. Qu, A. E. Saddik and A. Adler. A stroke based algorithm for dynamic signature verification. In Proc. Can. Conf. Ele. Comp. Eng. (CCECE), pp. 461–464 (2004). B. Berret. Integration de la force gravitaire dans la planification motrice et le contrôle des mouvements du bras et du corps. PhD thesis, Bourgogne University, Dijon, France (2008). M. J. E.

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Advances in Digital Handwritten Signature Processing: A Human Artefact for e-Society by Giuseppe Pirlo, Donato Impedovo, Michael Fairhurst


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