Transient Biometric System Classification Using Fingernail Images based on Artificial Intelligence

In this research work, the growth of the fingernail plate does not affect the biometric authentication system. Now, the accuracy has been improved with FF-BPNN method and PCA algorithm. PCA algorithm is used for the extraction of the unique image features that depends on the valuable properties. The trained feature set forwards FF-BPNN model to train the feature set. If the feature set is true, then the transient finger nail is identified, if false, then transient fingernail is not found in the dataset. The performance metrics for each of the feature extraction method with Feed Forward-BPNN classifier is analyzed. The Comparison of Proposed works using Feed Forward-BPNN value is 98.4%. The existing algorithm used for comparison with Accuracy rate value is 90.2%.