Study And Experiment On The Fusion Theory Of Multi-biometrics

Multimodal biometrics fusion can effectively improve the performance of a unimodal biometric identification system. Fusion in multimodal biometric systems can take place at four major levels: sensor level, feature level, score level and decision level. From a statistical point of view, this thesis focuses on score level and its effect on system recognition.Herein a new score normalized modal, double uniform expectation modal (DUE), is proposed. Compared to other normalization modals, this modal can simplify the relation among score distributions from different features. Furthermore, based on this modal, four score level fusion strategies (Sum-Average, Weight-Sum, Max-Score and Min-Score) are studied. The study includes distribution after fusion, effect to recognition performance by score distribution before fusion, and selection of optimal fusion method under different conditions. During research, several conclusions are gained and are testified in experiments of multimodal fusion.To provide multimodal biometrics fusion samples, this thesis refers to palmprint and hand vein pattern. Regarding palmprint, extraction algorithm of palmprint-code feature and texture distribution feature are proposed; With regard to hand vein pattern, extraction algorithm of minutia structure feature and information code feature are proposed. Using above features, three experiments are performed. These experiments sufficiently prove that score fusion can improve system recognition effectively, and equal error rate (EER), an important parameter to describe system recognition performance, decreased distinctively. The conclusions from theoretical analyses are proved by these experiments, and accord with experiments results. By analyzing factors which induce errors, the modal and the theoretical deduction are proved to have strong feasibility and robusticity.Using the results of theory research on score level fusion, we can estimate the performance of multimodal biometrics fusion system by analyzing the distribution of unimodal biometric, and establish the optimal fusion strategy according to certain demand, therefore this thesis means much to the construction and application of multimodal biometrics system.