Fingerprint image enhancement using Gabor filter
Fingerprints are the oldest and most widely used form of biometric identification. Despite the widespread use of fingerprints, there is little statistical theory on the uniqueness of fingerprint minutiae. A critical step in studying the statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images. However, fingerprint images are rarely of perfect quality. They may be degraded and corrupted due to variations in skin and impression conditions. Thus, image enhancement techniques are employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations. In this paper fingerprint image enhancement method, a refined Gabor filter, is presented. This enhancement method can connect the ridge breaks, ensures the maximal gray values located at the ridge center and has the ability to compensate for the nonlinear deformations. The result shows it can improve the performance of image enhancement
Recently model order reduction techniques for second-order systems have obtained many research interests for the simulation of RCS interconnect circuits employing susceptance elements. In this paper, we propose a Block SAPOR (Block Second-order Arnoldi method for Passive Order Reduction) for multi-input multi-output RCS circuits. The proposed Block SAPOR algorithm can simultaneously guarantee passivity and achieve higher accuracy than the first order reduction technique PRIMA. Most importantly, the reduced system matrices obtained by the proposed method can preserve the structure of the original system matrices. Such a nice property makes it possible to construct an equivalent RCS circuit for the reduced system.