Appendix A 

ELFT-EFS [Evaluation #2]

NIST Evaluation of Latent Fingerprint Technologies: Extended Feature Sets 

Additional Results 

Contents 

A-1 Additional Rank-based results .........................................................................................................1

A-2 Proportion of hits at rank 1 .............................................................................................................13

A-1 Additional Rank-based results 

These are additional results not presented in the main report. 

Note: in this section and throughout the report, results from Evaluation #1 differ slightly from those reported in

NISTIR 7775, because these are based on the revised Baseline and Baseline-QA datasets. In general, the Evaluation

#1 results reported here are about 1 percentage point higher than those reported in NISTIR 7775. 

A-1.1 CMCs for Baseline-QA dataset 

The following CMCs compare the performance of the individual matchers for each latent feature subset for the

Baseline-QA dataset. In each case, the results for Evaluation #1 are on the left, and the results for Evaluation #2 are

on the right. 
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A-1.2 CMCs for Baseline Dataset 

The following CMCs compare the performance of individual latent feature subsets for each matcher on the Baseline

dataset. In each case, the results for Evaluation #1 are on the left, and the results for Evaluation #2 are on the right. 

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A-1.3 Rank-1 identification rates for MLDS dataset 

Evaluation 

#1 

Latent Feature Subset 

LA LB LC LD LE LF LG 

Matcher 

A 47.4 50.0 50.0 55.3 55.3 55.3 36.8 

B 42.1 42.1 42.1 44.7 44.7 47.4 36.8 

C 36.8 39.5 36.8 47.4 47.4 55.3 36.8 

D 21.1 n/a n/a 18.4 n/a 15.8 21.1 

E 31.6 42.1 42.1 39.5 36.8 26.3 28.9 

Evaluation 

#2 

Latent Feature Subset 

LA LB LC LD LE LF LG 

Matcher 

A 52.6 52.6 52.6 55.3 55.3 57.9 36.8 

B 47.4 55.3 55.3 55.3 55.3 60.5 31.6 

C 52.6 52.6 50.0 52.6 55.3 n/a 39.5 

D 23.7 13.2 n/a n/a n/a n/a n/a 

E 34.2 36.8 36.8 36.8 36.8 36.8 0.0 

A-1.4 Rank-1 Identification Rate by Baseline Dataset Source 

The following charts show, for the matchers tested in Evaluation #1 with respect to the Baseline dataset used in

Evaluation #2, the difference in the rank-1 identification rate between the latents of differing sources. 

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A-1.5 Rank-1 Identification Rate by Minutiae Count 

The following charts show, for the matchers tested in Evaluation #1 with respect to the Baseline dataset used in

Evaluation #2, the rank-1 identification rate for different ranges of minutiae count. 

A-1.6 Rank-1 Identification Rate by Latent Orientation 

The following charts show, for the matchers tested in Evaluation #1 with respect to the Baseline dataset used in

Evaluation #2, the rank-1 identification rate for different ranges of latent orientation. 

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A-1.7 Rank-1 Identification Rate by Latent Value Determination 

The following charts show, for the matchers tested in Evaluation #1 with respect to the Baseline dataset used in

Evaluation #2, the rank-1 identification rate for different examiner-assigned Value, Limited Value, and No Value

determinations. 

All No 

Value 

Limited Value Value 

Count 1066* 25 113 917 

LA 

A 63.3% 20.0% 27.4% 68.9% 

B 62.5% 4.0% 19.5% 69.3% 

C 49.2% 0.0% 14.2% 54.9% 

D 25.5% 0.0% 2.7% 29.1% 

E 48.2% 0.0% 14.2% 53.5% 

LE 

A 67.7% 20.0% 31.0% 73.6% 

B 64.5% 8.0% 21.2% 71.4% 

C 63.1% 8.0% 19.5% 69.9% 

D 16.7% 0.0% 2.7% 19.0% 

E 51.2% 8.0% 12.4% 57.3% 

LG 

A 44.7% 0.0% 5.3% 50.6% 

B 49.2% 4.0% 2.7% 56.2% 

C 48.6% 4.0% 7.1% 54.9% 

D 11.7% 0.0% 0.9% 13.4% 

E 29.6% 0.0% 1.8% 34.0% 

All No Value Limited Value Value 

Count 1066 25 113 917 

LA 

A 56.4% 8.0% 21.2% 63.6% 

B 43.4% 4.0% 5.3% 50.4% 

C 42.4% 0.0% 9.7% 48.8% 

D 18.0% 0.0% 0.9% 11.5% 

E - - - -

LE 

A 59.4% 8.0% 25.7% 66.9% 

B 47.1% 0.0% 8.0% 54.9% 

C 53.0% 4.0% 13.3% 60.2% 

D - - - -

E - - - -

LG 

A 36.1% 0.0% 0.9% 43.4% 

B 34.3% 0.0% 1.8% 39.6% 

C 38.8% 0.0% 2.7% 45.4% 

D - - - -

E - - - -

* Note: 11 latents (out of 1066) in Baseline, and 5 latents (out of 418) in Baseline-QA did not have value determinations. 

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A-1.8 Rank-1 Identification Rate by Good / Bad / Ugly Quality Classifications 

The following charts show, for the matchers tested in Evaluation #1 with respect to the Baseline dataset used in

Evaluation #2, the rank-1 identification rate for different examiner-assigned Excellent, Good, Bad, Ugly, and No

Value quality determinations. 

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A-2 Proportion of hits at rank 1 

The following tables show, for Evaluation #2, the proportion of the total hits made by a matcher at any rank (rank ≤

100) that were rank 1.* 

Table 1 Proportion of hits at rank 1 for the Baseline-QA dataset (418 latents, subset of Baseline) 

Latent Subset 

LA LB LC LD LE LF LG 

Image only Image +

ROI 

Image +

ROI + 

Pattern 

Class + 

Qual map 

Image +

Minutiae 

Image +

EFS 

Image +

EFS + 

Skeleton 

Minutiae 

only 

A 89% 91% 91% 90% 90% 89% 80% 

B 85% 89% 88% 88% 90% 92% 82% 

C 91% 90% 90% 90% 92% NA 82% 

D 84% 82% NA NA NA NA NA 

E 82% 81% 83% 81% 83% 83% 0% 

Table 2: Proportion of hits at rank 1 for the Baseline dataset (1066 latents) 

Latent Subset 

LA LE LG 

Image only Image + EFS Minutiae only 

A 92% 93% 83% 

B 90% 91% 81% 

C 92% 94% 84% 

D 87% NA NA 

E 84% 86% 0% 

* This is sometimes known as the “Ray Moore statistic”. AFIS pioneer Ray Moore observed that this tended to be about 83% at

the time. 

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