Statistical Analysis for Engineers and Scientists: A Computer-Based Approach
Statistical Analysis for Engineers and Scientists: A Computer-Based Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Experimental Analysis of the Modified Direction Feature for Cursive Character Recognition
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Offline Geometric Parameters for Automatic Signature Verification Using Fixed-Point Arithmetic
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signature verification (SV) toolbox: Application of PSO-NN
Engineering Applications of Artificial Intelligence
IEEE Computational Intelligence Magazine
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Off-line Signature Verification (SV) is performed using Particle Swarm Optimisation Neural Network (PSO NN) algorithm. The technique is based on NN approach trained with PSO algorithm. The presented verification system includes image-processing techniques and other mathematical tools in its structure. To test the performance of the proposed algorithm, three types of forgeries, namely random, unskilled and skilled, are examined. A database with 1350 skilled and genuine signatures taken from 25 volunteers is used for testing the algorithm. The experimental results are presented with comparisons on verification accuracy and statistical figures.