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A biometrics system for identifying individuals using the pattern of veins in a finger

BackgroundThe study aim was, for the first time, to conduct a multicenter randomized controlled trial to evaluate the effect of tonsillectomy in patients with IgA nephropathy (IgAN).MethodsPatients with biopsy-proven IgAN, proteinuria and low serum creatinine were randomly allocated to receive tonsillectomy combined with steroid pulses (Group A; n = 33) or steroid pulses alone (Group B; n = 39). The primary end points were urinary protein excretion and the disappearance of proteinuria and/or hematuria.ResultsDuring 12 months from baseline, the percentage decrease in urinary protein excretion was significantly larger in Group A than that in Group B (P < 0.05). However, the frequency of the disappearance of proteinuria, hematuria, or both (clinical remission) at 12 months was not statistically different between the groups. Logistic regression analyses revealed the assigned treatment was a significant, independent factor contributing to the disappearance of proteinuria (odds ratio 2.98, 95% CI 1.01–8.83, P = 0.049), but did not identify an independent factor in achieving the disappearance of hematuria or clinical remission.ConclusionsThe results indicate tonsillectomy combined with steroid pulse therapy has no beneficial effect over steroid pulses alone to attenuate hematuria and to increase the incidence of clinical remission. Although the antiproteinuric effect was significantly greater in combined therapy, the difference was marginal, and its impact on the renal functional outcome remains to be clarified.

SUMMARYThe research group of which the authors are members has proposed a scheme based on finger vein patterns as a scheme of biometric identification utilizing biological information. Since the finger vein images taken to obtain finger vein patterns are obtained by irradiating the fingers with infrared rays, fluctuations in brightness due to variations in the light power or the thickness of the finger occur. This paper proposes a scheme for extracting global finger vein patterns by iteratively tracking local lines from various positions to robustly extract finger vein patterns from such unclear images. The proposed scheme is robust against brightness fluctuations as compared with the conventional feature extraction schemes and the results of evaluating the proposed scheme by applying it to a personal identification system showed an effective error rate of 0.145%.

A novel method for finger-vein authentication based on feature-point matching is proposed and evaluated. A finger-vein image captured by infrared light contains artifacts such as irregular shading and vein posture deformation that can degrade accuracy of finger-vein authentication. Therefore, a method is proposed for extracting features from vein patterns and for matching feature points that is robust against irregular shading and vein deformation. In the proposed method, curvature of image-intensity profiles is used for feature point extraction because such image profiles are a robust feature against irregular shading. To increase the number of feature points, these points are extracted from any positions where vein shape is non-linear. Moreover, a finger-shape model and non-rigid registration method are proposed. Both the model and the registration method correct a deformation caused by the finger-posture change. It is experimentally shown that the proposed method achieves more robust matching than conventional methods. Furthermore, experiments on finger-vein identification show that the proposed method provides higher identification accuracy than conventional methods.