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This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).
Index Terms- Biometrics, multimodal systems, hand-based identification, K-L transform, eigenpalms, eigenfingers.

I. Fratric and S. Ribaric, "A Biometric Identification System Based on Eigenpalm and Eigenfinger Features," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 27, no. , pp. 1698-1709, 2005.
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