Research on the Evaluation Method for Likelihood Ratio of Fingerprint Evidence Based on the Distribution Law of Entire Data
The distribution law of the entire data is necessary to be explored to construct a scientific and effective likelihood ratio model of fingerprint evidence for solving the problem of difficult access to the en-tire data of the comparison score of automatic fingerprint identification system in the ten-million-people database.Taking the fingerprint comparison scores as the data base,the data fitting and error calculation of four parameter estimation of distribution functions,including Beta,Norm,Weibull and Gamma,are carried out through the mathematical statistical method in R language using moment estimation and maxi-mum likelihood estimation,so as to determine the optimal method of parameter estimation.The entire da-ta is simulated by the best-fit parameter method,the likelihood ratio model is constructed and logarithmic values of same-source and different-source likelihood ratios are calculated to assess its performance in his-tograms.Experimental results show that Beta distribution has the smallest error value and the best fitting effect in the distribution law of the number of different minutiae for both single and multiple fingerprints.The models constructed by sectional and overall analysis of the number of minutiae are similar.As the number of minutiae increases from 5 to 16,the separation degree of probability density function curves for same-source and different-source score data increases,and the performance of the models becomes bet-ter.Especially when the number of minutiae exceeds 12,the same-source and different-source curves are almost completely separated,showing excellent differentiation and recognition ability up to 16 minutiae.The three-segment model divided for single fingerprints is consistent with practical work in fingerprint i-dentification.However,when considering the number of all minutiae,the performance of the model would be degraded due to the large amount of integrated data.Beta distribution can better present the dis-tribution law of the entire fingerprint data under different-source conditions,and the likelihood ratio mod-el constructed by this way has strong identification ability,which has a great practical prospect,and helps to promote the evaluation of fingerprint evidence from experience to science.
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