An automated multimodal biometric system and fusion

Abstract

This paper proposed an automated multimodal biometric system and fusion technique to eliminates the unimodal limitations. Unimodal biometric system has many problems like occlusion, illumination, pose variation. This proposed multimodal biometric system use face, left ear, left palm, right palmprint, left knuckleprint, right knuckleprint as biometric traits. This multimodal biometric system has auto positioning device for face and ear image acquisition. An another device is created for palmprint and knuckleprint acquisition. This proposed biometric system use an efficient image enhancement, SURF based feature extraction and SURF based feature matching techniques for all used biometric trait images. This system use two level fusion strategy. Feature level fusion is used to make more discriminative feature template for each biometric trait and score level fusion is used to make final fused score from all used biometric traits.