Researchers at Michigan State University and the U.S. National Institute of Standards and Technology have developed an algorithm that automates the fingerprint-analysis process.
The researchers trained the machine-learning algorithm on data from 31 fingerprint experts who had analyzed 100 latent prints each, scoring the quality of each on a 1-to-5 scale. The prints and their scores were used to train the algorithm to determine how much information a latent print contains.
The researchers tested the algorithm by having it score a group of new latent prints. The team submitted those scored prints to Automated Fingerprint Identification System software connected to a database of more than 250,000 rolled prints. The researchers found the scoring algorithm performed slightly better than the average of human examiners involved in the study.
They next want to test the system on a larger dataset, which will enable them to improve the algorithm's performance and more accurately measure its error rate.
From U.S. National Institute of Standards and Technology
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