Off-line signature verification using artificial immune recognition system

In various pattern recognition applications, artificial immune systems achieve comparable and commonly higher performance than other classification schemes such as SVM. In this paper, we investigate their applicability for handwritten signature verification. Specifically, Ridgelet transform and grid features are used to extract pertinent characteristics. Performance assessment is conducted on the CEDAR dataset comparatively to SVM classifiers. The results in terms of average error rate highlight the high performance of artificial immune recognition algorithm.