Score Normalization is a usual technique in pattern recognition to standardize the classifier output ranges so as to, for example, fuse these outputs. The use of score normalization in biometric recognition is a very important part of the system, specially in those based on behavioral traits, such as written signature or voice, conditioning the final system performance. Then, many works can be found that focus on the problem. A successful new approach for client threshold prediction, based on Multiple Linear Prediction, has been presented in recent works. Here, a new approach for score normalization, based on this proposal for biometric manuscript signature user verification, is shown. This proposal is compared with the state of the art methods, achieving an improvement of 19% and 16% for Equal Error Rate (EER) and 60% and 26% for Detection Cost Function (DCF) performance measures, for random and skilled forgeries, respectively.

In this study, an application that allows a mobile phone to be used as a biometric-capture device is shown. The main contribution of our proposal is that this capture, and later recognition, can be performed during a standard web session, using the same architecture that is used in a personal computer (PC), thus allowing a multiplatform (PC, personal digital assistant (PDA), mobile phone, etc.) biometric web access. The review, which is from both an academic and commercial point of view, of the biometry and mobile device state of the art shows that in other related works, the biometric capture and recognition is either performed locally in the mobile or remotely but using special communication protocols and/or connection ports with the server. The second main contribution of this study is an in-depth analysis of the present mobile web-browser limitations; thus, 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.

In this paper, we present the main results of the BioSecure Signature Evaluation Campaign (ESRA'2011). The objective of ESRA'2011 is to evaluate through two different tasks the resistance of different online signature systems to skilled forgeries categorized automatically according to their quality. Task 1 aims at studying with only coordinate time functions the influence of acquisition conditions (digitizing tablet vs. PDA) on systems' performance. The two BioSecure Data Sets DS2 and DS3 make this possible, since they contain data from the same 382 people, acquired respectively on a digitizer and on a PDA. Task 2 then aims at assessing the contribution of the five time functions available on a digitizer (coordinates, pressure, pen inclination) on systems' resistance to different qualities of skilled forgeries. Results of the 13 systems involved in this competition are reported and analyzed for both tasks in this paper. We observe 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 forgeries. Also, we note that mobile conditions are still threatening independently of the quality of forgeries. Finally, when adding pen inclination time functions to pressure and coordinates, we find that the gap between systems in terms of performance is wider than when only pen coordinates and pressure are considered.