https://run.unl.pt/bitstream/10362/59127/1/Time_Alignment_Measurement_for_Time_Series.pdf

Time Alignment Measurement for Time Series

Offline writer independent (WI) signature verification is conceivably a challenging task in the domain of handwritten biometrics. This work addresses it by introducing a feature extraction scheme that relies on the detection of first order transitions between asymmetrical lattice arrangements of simple pixel structures. The experiments are conducted with a decision stumps committee, accompanied with boosting feature selection, by employing only unrelated or blind training and testing datasets, all derived from four widely used signature databases. In addition, a fifth signature dataset which contains disguised signatures, originating from a signature verification contest, is also used for testing purposes. The impact of the preprocessing stage per dataset is exploited by allowing various pruning levels of the raw binary signature. In addition to standard training protocols, we introduce the use of the applicability domain (AD) in WI signature verification and examine its effectiveness in providing reliable classifier predictions by quantifying subregions of the input distance space that have been sufficiently covered by training examples. The derived experimental results expressed by means of equal error rate, along with best average error rate, are considered to be very competitive to those provided from state of the art WI methods.

Writer independent offline signature verification based on asymmetric pixel relations and unrelated training-testing datasets

Online signature verification has been widely applied in biometrics and forensics. Due to the recent demand on high-speed systems in this era of big data, to simultaneously improve its performance and calculation complexity, this study focuses on a single-template strategy that uses dynamic time warping (DTW) with dependent warping for online signature verification, and attempts to construct a novel time-series averaging method called Euclidean barycenter-based DTW barycenter averaging (EB-DBA). Specifically, this study proposes a single-template strategy using a mean template created by the EB-DBA to achieve higher performance at lower calculation complexity for online signature verification. The method's discriminative power is enhanced upon the exploration of two DTW warping types, where it is found that the DTW with dependent warping exhibits better performance. The popular MCYT-100 dataset is utilized in the experiments, which confirms the effectiveness of the proposed method in simultaneously achieving lower error rate and lower calculation complexity, for online signature verification.

/pdf/template-matching-using-time-series-averaging-and-dtw-with-3bzlljbzaf.pdf

Template Matching Using Time-Series Averaging and DTW With Dependent Warping for Online Signature Verification

Online signature verification using single-template matching with time-series averaging and gradient boosting

The paper presents an efficient on-line signature verification method based on the dynamic features of a given signature. In the proposed approach, curvature and torsion feature are associated with Hausdorff distance measure which can be used in the verification process. In the feature extraction step, the signature trajectory is approximated as a spatial curve. A set of curvature and torsion value of extreme point is computed from both x coordinate, y coordinate and pressure feature so that the dimension of the curve is reduced. Therefore, a new composed signature feature is created for each person. For the obtained feature data, the most distinctive Hausdorff distance is further proposed to calculate the distances of the eight-dimensional feature vector between the test signature and corresponding template signatures for the verification of the test sample. Comprehensive experiments are implemented on three publicly available databases: the SVC2004, SUSIG and MCYT-100 database. A comparison of our results with some recent signature verification methods available in the literature is provided with equal error rate, and the results indicate that the proposed method would better recognize genuine signatures, random and skilled forgeries.

Online handwritten signature verification based on association of curvature and torsion feature with Hausdorff distance

Discriminative feature selection for on-line signature verification

This article uses 3D Max, Vitriols and other software tools to design and develop junior high school physics simulation experiments based on the above-mentioned curriculum design. The development process, key technologies and module architecture are introduced in more detail. Finally, the article tests, evaluates and improves the simulation experiment developed.

Research on Application of Computer Big Data Technology in Physical Electricity Experiment

A generalized synchronous chaotic system is constructed by using discrete generalized chaotic synchronization theory and 2D-CS. The improved chaotic system consists of three continuous chaotic systems. The control sequence is used to switch according to certain rules. Through the analysis of phase diagram, bifurcation diagram and maximum Lyapunov exponent, it is found that compared with the subsystem, the system parameter interval, traversal range and maximum Lyapunov exponent increase. Convert the sampled results to IEEE Binary floating-point Arithmetic Standard (IEEE754) format. The final random number is then generated by sequentially truncation, S-box transformation and XOR operation. The result of testing the generated random number sequence shows that the generated random number can pass all the tests.

Research on the Motion Model of Chaotic Phenomena Based on Computer Artificial Intelligence Simulation

The article first establishes an inverse filter and reconstructs the phase space from its output, and then uses the duffing equation to minimize the relative singular value of the output signal in the embedded space for local singular value decomposition to realize parameter estimation. Finally, the article establishes a chaotic system based on Duffing oscillator to detect weak sinusoidal signals under the background of colored noise. The simulation results of the model parameters and the frequency estimation of the sinusoidal signal verify the effectiveness of the method.

Jungang Zheng

Papers

Discriminative feature selection for on-line signature verification

Research on Application of Computer Big Data Technology in Physical Electricity Experiment

Research on the Motion Model of Chaotic Phenomena Based on Computer Artificial Intelligence Simulation

Research on the Application of Signal in Chaotic Background in Physical Inverse Filter