Article ID Journal Published Year Pages File Type
381532 Engineering Applications of Artificial Intelligence 2009 7 Pages PDF
Abstract

Analysis of signature is a widely used and developed area of research for personal verification. A typical signature verification (SV) system generally consists of four components: data acquisition, pre-processing, feature extraction and verification. A reliable SV toolbox, based on the verification of off-line signatures is developed with the proposed algorithm. The technique is based on a neural network (NN) approach trained with particle swarm optimization (PSO) algorithm. To test the performance of the proposed PSO-NN algorithm two types of forgeries—unskilled and skilled—are examined. The experimental results are illustrated on the selected signature databases and presented herein.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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