Measurements were carried out in 0.1 M CBS (pH 5.0) used as supporting-electrolyte solution. The pH of buffer solutions was monitored by using a 713 pH meter (Metrohm, Switzerland).Hydrodynamic VoltammetryAmperometric measurements at the poly(Ani-co-m-FcAni)/GCE were selleck chem carried out at the potential of +0.25 V (vs. Ag/AgCl). The amperometric response of AA was shown in the amperogram. The current steps were associated with successive additions of 20 ��L of 0.1 M AA standard solution into a stirred batch system using a 10 mL volume glass cell.Electron MicroscopyThe SEM images were recorded employing a JEOL JSM-5910 field emission scanning electron microscope (FESEM) by accelerating at a voltage of 15.0 kV.
The surface of the poly(Ani-co-m-FcAni)/GCE was analy
At present, trends in biometrics are inclined to provided human identification and verification without requiring any contact with acquisition devices. The point of aiming contact-less approaches for biometrics regards the upward concerns with hygiene and final user acceptability.Concretely, hand biometrics usually have made use of a flat platform to place the hand, facilitating not only the acquisition procedure but also the segmentation and posterior feature extraction. Consequently, hand biometrics is evolving to contact-less, platform-free scenarios where hand images are acquired in free air, increasing the user acceptability and usability.However, this fact provokes an additional effort in segmentation, feature extraction, template creation and template matching, since these scenarios imply more variation in terms of distance to camera, hand rotation, hand pose and unconstrained environmental conditions.
In other words, the biometric system must be invariant to all these former changes.The presented method proposes a hand geometry biometric system oriented to contact-less scenarios. The main contribution of this paper is threefold: firstly, a feature extraction method is proposed, providing invariant hand measurements to previous changes; second contribution consists of providing a template creation based on hand geometric distances, requiring information from only one individual, without considering data from the rest of individuals within Batimastat the database; finally, a proposal for template matching is proposed, minimizing the intra-class similarity and maximizing the inter-class likeliness.
The proposed method is evaluated using three publicly available contact-less, platform-free databases. In addition, the results obtained with these databases will be compared to the results provided by two competitive pattern Vorinostat FDA recognition techniques, namely Support Vector Machines (SVM) and k-Nearest Neighbour, often employed within the literature.Finally, the layout of this paper remains as follows: First of all, a literature review is carried out in Section 2. Secondly, the feature extraction method is described in Section 3.
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