Multimodal biometric identification system based on finger geometry, knuckle print and palm print
This paper presents a multimodal biometric identification system based on finger geometry, knuckle print and palm print features of the human hand. The hand image captured from digital camera was first preprocessed to get the finger ROI (Region Of Interest) and palm ROI. Finger geometry features and knuckle print features of index, middle, ring and little fingers were extracted from the finger ROI; palm print features represented with keypoints and their local descriptors were extracted from palm ROI. A coarse-to-fine hierarchical method was employed to match multiple features for efficient hand recognition in a large database. The decision level AND rule fusion was adopted which has shown the improvement of the combined scheme. Our experimental results demonstrate the feasibility and effectiveness of the proposed method.
multimodal biometric finger geometry knuckle print palm print decision level fusion hierarchical matching