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 expertise 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 clever towns. Handwritten signatures are very complicated indicators; they're the results of an problematic method that is determined by the psychophysical country of the signer and the stipulations less than which the signature apposition procedure happens. although, fresh efforts from academies and industries now make attainable the combination of signature-based applied sciences into different regular gear to shape whole options which are in a position to aid the protection specifications of cutting-edge society.

Advances in electronic Handwritten Signature Processing essentially presents an replace at the so much attention-grabbing and helpful researches within the multifaceted box of handwritten signature research and processing. The chapters inside additionally introduce and speak about serious elements and valuable possibilities on the topic of using this know-how, in addition to spotlight basic theoretical and applicative elements of the sector.

This booklet includes papers through well-recognized and lively researchers and scientists, in addition to by way of engineers and advertisement managers operating for big foreign businesses within the box of signature-based platforms for quite a lot of functions and for the advance of e-society.

This e-book is dedicated to either researchers and specialists energetic within the box of biometrics and handwriting forensics, in addition to execs concerned about the improvement of signature-based suggestions for complex purposes in drugs, finance, trade, banking, private and non-private administrations, and so on. Handwritten Signature Processing can also be used as a sophisticated textbook through graduate scholars.

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

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

Example text

Eventually, the desired stability regions are the LSSS whose global similarity is greater than a threshold GSth, as shown in (Fig. 2). 2. Searching for stability regions in a set of signatures The procedure described in the previous Section computes the stability region between a pair of signatures. 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.

Fig. 3. Distribution of the global feature vectors (composed by the signature total time duration and the pen down duration) for the genuine and forged signatures of an author in the Training Set. It is important to note that the genuine and forged signatures are, in general, more overlapped when the global based features are considered individually than when they are combined in a unique feature vector. Note that, if the dimensionality of the feature vectors in Fig. 3 is reduced (by projecting them to one axis), the corresponding representations of the genuine and forged signatures will not be easily separable.

5 On the other hand, we use in our proposed methods the Minimum Jerk principle9 which to the authors’ knowledge has not yet been applied to signature analysis. Therefore, we now present a more detailed description of the Minimum Jerk principle. The Minimum Jerk Principle. This model belongs to the category of the quadratic derivative kinematic criteria, which have a general cost function defined as: 1 ் ݀௡ ‫ݔ‬ሺ‫ݐ‬ሻ ଶ ݀ ௡ ‫ݕ‬ሺ‫ݐ‬ሻ ଶ ‫ܥ‬ൌ න ൬ ൰ ൅ ൬ ൰ ݀‫ݐ‬ 2 ଴ ݀‫ ݐ‬௡ ݀‫ ݐ‬௡ (1) where ܶ is the movement duration, ‫ݔ‬ሺ‫ݐ‬ሻ and ‫ݕ‬ሺ‫ݐ‬ሻ are the horizontal and vertical position time series respectively.

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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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