Juan Manuel Pascual-Gaspar

TL;DR: The objective of BSEC'2009 was to evaluate different online signature algorithms on two tasks: the first one aims at studying the influence of acquisition conditions (digitizing tablet or PDA) on systems' performance; the second one aims on studying the impact of information content in signatures on systems’ performance.

TL;DR: The proposed system outperforms the winner of SVC with a reduced computational requirement, which is around 47 times lower than DTW, and is more privacy-friendly as it is not possible to recover the original signature using the codebooks.

TL;DR: This paper proposes a multi-section vector quantization approach for on-line signature recognition that obtains similar results as the state-of-the-art online signature recognition algorithm, Dynamic Time Warping, with a reduced computational requirement, around 47 times lower.

TL;DR: The BioSecure Signature Evaluation Campaign (ESRA'2011) as discussed by the authors evaluated the resistance of different online signature systems to skilled forgeries categorized automatically according to their quality, and found that the best system in terms of performance on forgeries of “bad” quality is not necessarily the most resistant to an increased quality of skilled forgery.

TL;DR: It is concluded that, in general, it is impossible to use the same technologies that can be used to capture biometrics in PC platforms (i.e., Applet Java, ActiveX Control, JavaScript, or Flash); therefore, new solutions, as shown here, are needed.