Latent Palm Fused with Fingerprint to Improve Authentication Performance
Biometric authentication systems adopt a suitable image processing technique to manipulate the biometric images. It refers to verifying a person using their biometric traits that includes physiological, biological and/or behavioral traits like iris, face, fingerprint, voice, hand writing, etc., A biometric characteristic should be unique, universal, permanent and acceptable. In this paper, the texture feature of palm and finger print extracted using Gabor filter and fusion is done by concatenation. The high dimensionality of fused features is reduced using Ant Colony Optimization (ACO) algorithm and finally only the most significant features are used for classification of genuine and imposter users.