New Method for Dynamic Signature Verification Based on Global Features

Self Cite

Abstract. Identity verification based on the dynamic signature is an important issue of biometrics. There are many effective methods to the signature verification which take into account the dynamic characteristics of the signature (e.g. velocity of the pen, the pen's pressure on the surface of the graphic tablet, etc.). Among these methods, the ones based on the so-called global features are very important. In our previous paper we have proposed new algorithm for evolutionary selection of the dynamic signature global features, which selects a subset of features individually for each user. Algorithm proposed in this paper is a faster version of the method proposed earlier. During development of the algorithm we resigned from using evolutionary selection of global features and standardized working of the classifier in the context of all users. The paper contains the simulation results for the BioSecure database of the dynamic signatures.

Section: Description Of the New Methods For Dynamic Signature Verificamentioning

confidence: 99%

“…Approach based on global features may be found in many research papers (see e.g. [14,37,39,79,75]). Functions based methods.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New Fast Algorithm for the Dynamic Signature Verification Using Global Features Values

Zalasiński

Cpałka

Hayashi

2015

Self Cite

“…[8,10,12,13,22,26,40,44,48]) and pattern recognition issues (see e.g. [43,45,55,57,58,59]). This paper is organized into 4 sections.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Controller Structure Using Evolutionary Algorithm

Przybył

Szczypta

Wang

2015

Abstract. PID-based controller structures are typically used in industrial control systems. However, in different areas the controller structures are slightly different. The differences are due to the modifications introduced by the expert. Expert, based on his experience and on trial-anderror method, adjusts the initial controller structure in order to obtain a better quality of control. In this paper a method based on an evolutionary algorithm is proposed. Usage of the proposed method makes this difficult and time consuming task easier and faster.

“…In particular we propose: (a) a new approach for construction and tuning of neuro-fuzzy systems (including flexible neurofuzzy systems, see e.g. [19,22,23,103,108,109]) (b) a new interpretability criteria for increasing interpretability of expert knowledge taking into account not only the complexity of the system but also semantics of the rules.…”

Section: Introductionmentioning

confidence: 99%

A New Interpretability Criteria for Neuro-Fuzzy Systems for Nonlinear Classification

Łapa

Cpałka

Galushkin

2015

Self Cite

Abstract. In this paper a new approach for construction of neuro-fuzzy systems for nonlinear classification is introduced. In particular, we concentrate on the flexible neuro-fuzzy systems which allow us to extend notation of rules with weights of fuzzy sets. The proposed approach uses possibilities of hybrid evolutionary algorithm and interpretability criteria of expert knowledge. These criteria include not only complexity of the system, but also semantics of the rules. The approach presented in our paper was tested on typical nonlinear classification simulation problems.