PATENT CLAIM ANALYSIS

Application Number: 15973881
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["382", "115000"]

Abstract:
In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Claim (Index 1):
A method for setting a threshold in a biometric system using imposter match score data to derive a match threshold score that results in a desired false match rate and false non-match rate comprising:\n creating a database of match scores between all unique impostor biometric sample pairs; creating a cumulative histogram data table recording for each possible match score outcome a number of match scores observed greater than that value divided by the total number of samples; and selecting a desired false match rate and applying the threshold that will result in the desired false match rate.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 93.0
- Lexical Diversity: 1.84848
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14519431', '13959934', '12988056', '14052402', '15944547']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4232364637338976
- 35 USC 102 Novelty (BERT): 0.6117982320935242
- Combined Prediction Score: 0.4420926405698603
- Mean Citation Score: 538.1155379999999
- Max Citation Score: 538.1335
- Similarity Product: 516.6802215533853

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test