Performance improvement of complex plane based feature vector for online signature recognition using soft biometric features

This paper proposes well-worn approach for verification of Online Signature which is one of the biometric entity. The signature will capture on digitizer the missing points of the signature are calculated from MDDA algorithm. This paper uses a notion to extract the feature vector generation based on CAL-SAL function. To extract the feature vector intermediate transform of row & col will be evaluated and distributed over complex Walsh plane. The mean value for each blocks will be calculated which separates the first and last row & col of mean & density of CAL-SAL components for other transforms. Lastly soft biometric features are added to improve the performance. The results for the unimodal & Multi Algorithmic features vectors are compared. Performance Index & Security Performance Index will be evaluated which delivers the performance of the system.