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combinations of 9 points from the I ranked candidate set ( ). For each combination,
we find one polynomial. Its coefficients are mapped back and concatenated in the
same order as encoding phase in order to obtain a 144-bit key K'. To check whether
the key K' is matched with the initial K or not, we hash K' and compare the result
with the hashed versions of the keys in the database. The authentication is success-
ful if and only if we can recover one key K' matched with K. It means that we do not
have to compute all the combinations. Otherwise, if no matched key from all the
combinations is found, the authentication is failed.
4
Evaluation
The proposed scheme with the original transformation (section 3.3) and new trans-
formation (section 3.4) is tested with the Face94 database 3 . In the training procedure,
we use 100 images of 50 people, i.e. 2 images per person, to construct 40 eigenfaces.
Then, we test the scheme with 152 people, including 50 people participated in the
training process and 102 new people. Each person has 5 images in which 1 is used to
create the vault and 4 are used to unlock the vault. We measure the performance of
this scheme, include: FAR (False Acceptance Rate) and FRR (False Rejection Rate) 4 .
The FAR defines the probability that the system incorrectly matches the input pat-
tern to a non-matching template in the database. It measures the percent of invalid
inputs which are incorrectly accepted.
By analogy, the FRR defines the probability that the system fails to detect a match
between the input pattern and a matching template in the database. It measures the
percent of valid inputs which are incorrectly rejected.
0.7
0.6
0.5
0.4
FRR
FAR
0.3
0.2
0.1
0
0.16 0.18 0.2 0.21 0.215 0.22 0.23 0.25 0.28 0.3
Fig. 6. FAR and FRR of proposed scheme with original transformation
3 Libor Spacek's Faces94 database: http://cswww.essex.ac.uk/mv/allfaces/faces94.html. (Oct
2014).
4 FAR and FRR from Wikipedia: http://en.wikipedia.org/wiki/Biometrics (Oct 2014).
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