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Finger vein verification has developed a lot since its first proposal, butthere is still not a perfect algorithm. It is proved that algorithms with thesame overall accuracy may have different misclassified patterns. We could makeuse of this complementation to fuse individual algorithms together for moreprecise result. According to our observation, algorithm has differentconfidence on its decisions but it is seldom considered in fusion methods. Ourwork is first to define decision reliability ratio to quantify this confidence,and then propose the Maximum Decision Reliability Ratio (MDRR) fusion methodincorporating Weighted Voting. Experiment conducted on a data set of 1000fingers and 5 images per finger proves the effectiveness of the method. Theclassifier obtained by MDRR method gets an accuracy of 99.42% while the maximumaccuracy of the original individual classifiers is 97.77%. The experimentresults also show the MDRR outperforms the traditional fusion methods asVoting, Weighted Voting, Sum and Weighted Sum.

A Fusion Method Based on Decision Reliability Ratio for Finger Vein Verification