Improved Feature-Level Fusion-Based Biometric System for Genuine and Imposter Identification

Abstract

In this research work is divided into five sections: pre-processing, feature extraction, featurelevel fusion, imposter/ genuine classification, and male/female identification. The gathered raw data for palm print, dorsal vein, wrist vein, and palm vein are pre-processed with enhanced median filtering algorithms. The required features are then being extracted from the pre-processed images. Following that, an improved feature-level fusion technique is carried out based on the required security level. In the low security level, the certain image features are considered. Furthermore, if the medium security level is chosen, any two sets of attributes has been combined. If the high security level is chosen, all of the retrieved characteristics has been combined. Further, multiple classifications are carried out. It will determine whether the individual is genuine or an imposter. If it is an imposter, simply get rid of it. If the categorized result is genuine, it is reclassified as male or female.