Periocular refers to the facial region in the eye vicinity. It can be easily obtained with existing face and iris setups, and it appears in iris images, so its fusion with the iris texture has a potential to improve the overall recognition. It is also suggested that iris is more suited to near-infrared (NIR) illumination, whereas the periocular modality is best for visible (VW) illumination. Here, we evaluate three periocular and three iris matchers based on different features. As experimental data, we use five databases, three acquired with a close-up NIR camera, and two in VW light with a webcam and a digital camera. We observe that the iris matchers perform better than the periocular matchers with NIR data, and the opposite with VW data. However, in both cases, their fusion can provide additional performance improvements. This is specially relevant with VW data, where the iris matchers perform significantly worse (due to low resolution), but they are still able to complement the periocular modality.
In forensic fingerprint studies annotated databases is important for evaluating the performance of matchers as well as for educating fingerprint experts. We have established ground truths of minutia level correspondences for the publicly available NIST SD27 data set, whose minutia have been extracted by forensic fingerprint experts. We performed verification tests with two publicly available minutia matchers, Bozorth3 and k-plet, yielding Equal Error Rates of 36% and 40% respectively, suggesting that they have similar (poor) ability to separate a client from an impostor in latent versus tenprint queries. However, in an identification scenario, we found performance advantage of k-plet over Bozorth3, suggesting that the former can rank the similarities of fingerprints better. Regardless of the matcher, the general poor performance is a confirmation of previous findings related to latent vs tenprint matching. A finding influencing future practice is that the minutia level matching errors in terms of FA and FR may not be balanced (not equally good) even if FA and FR have been chosen to be so at finger level.
Abstract-We present a new system for biometric recognition using periocular images. The feature extraction method employed describes neighborhoods around keypoints by projection onto harmonic functions which estimates the presence of a series of various symmetric curve families around such keypoints. The iso-curves of such functions are highly symmetric w.r.t. the keypoints and the estimated coefficients have well defined geometric interpretations. The descriptors used are referred to as Symmetry Assessment by Feature Expansion (SAFE). Extraction is done across a set of discrete points of the image, uniformly distributed in a rectangular-shaped grid positioned in the eye center. Experiments are done with two databases of iris data, one acquired with a close-up iris camera, and another in visible light with a webcam. The two databases have been annotated manually, meaning that the radius and center of the pupil and sclera circles are available, which are used as input for the experiments. Results show that this new system has a performance comparable with other periocular recognition approaches. We particularly carry out comparative experiments with another periocular system based on Gabor features extracted from the same set of grid points, with the fusion of the two systems resulting in an improved performance. We also evaluate an iris texture matcher, providing fusion results with the periocular systems as well.
We study the general model of self-financing trading strategies in illiquid markets introduced by Schönbucher and Wilmott, 2000. A hedging strategy in the framework of this model satisfies a nonlinear partial differential equation (PDE) which contains some function g(α). This function is deep connected to an utility function.We describe the Lie symmetry algebra of this PDE and provide a complete set of reductions of the PDE to ordinary differential equations (ODEs). In addition we are able to describe all types of functions g(α) for which the PDE admits an extended Lie group. Two of three special type functions lead to models introduced before by different authors, one is new. We clarify the connection between these three special models and the general model for trading strategies in illiquid markets. We study with the Lie group analysis the new special case of the PDE describing the self-financing strategies. In both, the general model and the new special model, we provide the optimal systems of subalgebras and study the complete set of reductions of the PDEs to different ODEs. In all cases we are able to provide explicit solutions to the new special model. In one of the cases the solutions describe power derivative products.
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