Abstract：
The development of automated fingerprint identification systems (AFIS) revolutionized casework in the friction ridge community. Through the evolution of AFIS development, algorithms have become increasingly sensitive and specific. Internal validation studies conducted by the Federal Bureau of Investigation Laboratory Division\'s Latent Print Units (LPU) assessed the performance of the Next Generation Identification (NGI) system\'s latent print matching algorithm under the various encoding methods of the Multi-Biometric Identification System (MBIS) platform for the purpose of casework implementation. Based on the results of these studies, casework practices in the LPU have become more streamlined and efficient. The increase in accuracy of the latent print matching algorithm has reduced the number of candidates compared per search. For fingerprints, the results showed the best indicator for the correct mate being the number one candidate was the difference in score between the first and second candidate. When the score difference was 1200 or higher, the first candidate was mated in 99.3% of the trials. This understanding may allow for additional quality assurance measures to be implemented in casework.
摘要：
自动指纹识别系统（AFIS）的开发彻底改变了摩擦岭社区的案例工作。通过AFIS发展的演变，算法变得越来越敏感和具体。由联邦调查局实验室部门的潜在打印单位（LPU）进行的内部验证研究评估了下一代识别（NGI）系统的潜在打印匹配算法在多生物识别系统（MBIS）平台的各种编码方法下的性能。根据这些研究的结果,LPU的案例工作实践变得更加精简和高效。潜在打印匹配算法的准确性的提高减少了每次搜索比较的候选的数量。对于指纹，结果显示，正确伴侣是头号候选人的最佳指标是第一和第二候选人之间的得分差异。当分数差异为1200或更高时，第一个候选人在99.3%的试验中交配。这种理解可能允许在个案工作中实施额外的质量保证措施。
