Method for detecting a fake fingerprint

1. A method for detecting attempted fraud by using an artificial material during a biometric acquisition, comprising:

illuminating, with predefined, lighting under at least one wavelength, a surface of an individual subject to the biometric acquisition, said surface having a texture;

acquiring a first image of said surface at said at least one wavelength;

illuminating, with non-uniform lighting under at least one wavelength, said surface;

acquiring at least one second image of said surface under said non-uniform lighting, said non-uniform lighting causing light to diffuse within an illuminated material at an intensity that varies according to a law that is a function of a first position parameter (x; r) and is invariable along a second position parameter (y; θ);

computing, for a set of at least n locations each consolidating pixels with a same first position parameter (x; r) and different values for the second position parameter (y; θ) on the first image and the at least one second image,

a correction, varying along the first position parameter, that is to be locally applied to the first image to bring an amplitude of the texture on the first image substantially to a level of that on the second image at the same location, or

a correction that is to be locally applied to the at least one second image to bring an amplitude of a texture on the at least one second image substantially to the level of that on the first image at the same location; and

based on the correction thus computed, which represents said law, generating information relating to an artificial or non-artificial nature of the material on which the biometric acquisition is performed.

2. The method according to claim 1 , wherein:

the correction that is to be locally applied to the first image is obtained by computing a normalized scalar product Γ(x; r)

for a set of at least n vectors S b (x; r) of the first image, each vector S b (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ), and

for n vectors S a (x; r) of the at least one second image, each vector S a (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ),

according to the formula:

Γ( x;r )= S a ( x;r )· S b ( x;r )/ S b ( x;r )· S b ( x;r ), and

the information relating to the artificial or non-artificial nature of the material on which the biometric acquisition is performed is generated based on the normalized scalar product Γ(x; r) thus computed.

3. The method according to claim 1 , wherein:

the correction that is to be locally applied to the at least one second image is obtained by computing a normalized scalar product β(x; r)

for a set of at least n vectors S b (x; r) of the first image, each vector S b (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ), and

for n vectors S a (x; r) of the at least one second image, each vector S a (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ),

according to the formula:

β( x;r )= S a ( x;r )· S b ( x;r )/ S a ( x;r )· S a ( x;r ), and

the information relating to the artificial or non-artificial nature of the material on which the biometric acquisition is performed is generated based on the normalized scalar product β(x; r) thus computed.

4. The method according to claim 1 , wherein

the non-uniform lighting comprises one or more light patterns extending along the second position parameter (y) in order to generate a linear profile for diffusing light along the first position parameter (x).

5. The method according to claim 4 , wherein

the non-uniform lighting comprises a plurality of light strips parallel to each other and perpendicular to an axis defined by the first position parameter (x).

6. The method according to claim 1 , wherein

the non-uniform lighting comprises one or more patterns with rotational symmetry.

7. The method according to claim 1 , wherein

the acquisition of the first image and the acquisition of the at least one second image are synchronous.

8. The method according claim 1 , wherein

the acquisition of the first image and the acquisition of the at least one second image are asynchronous.

9. The method according to claim 8 , comprising

performing a spatial adjustment of the first image and the at least one second image prior to the computation of said correction.

10. The method according to claim 8 , wherein:

the at least one second image is reprocessed before the spatial adjustment by computing an approximation P(x; r) of a luminous intensity I(x; r) on the image along the first position parameter, and

by using this approximated intensity, a reprocessed image of the texture of the at least one second image is obtained, facilitating its comparison with the first image.

11. The method according to claim 10 , wherein the approximation is polynomial.

12. The method according to claim 1 , wherein:

the at least one second image is a plurality of second images, and

a plurality of acquisitions of the second images are completed at different wavelengths.

13. The method according to claim 1 , wherein

the acquisition of the first image is performed in a red range.

14. The method according to claim 1 , wherein

the biometric acquisition is performed by placing a finger or a hand in contact with a surface of a sensor.

15. The method according to claim 1 , wherein

the biometric acquisition is performed on a finger.

16. The method according to claim 1 , wherein

n is greater than or equal to 10.

17. A sensor for implementing the method according to claim 1 , comprising:

an imaging device acquiring the first image and the at least one second image;

at least one light source for illuminating the surface with the predefined lighting;

at least one light source for illuminating the surface with the non-uniform lighting; and

a computer configured to:

compute, for the set of at least n locations,

the correction that is to be locally applied to the first image, or

the correction that is to be locally applied to the at least one second image; and

based on the correction thus computed, generate the information relating to the artificial or non-artificial nature of the material on which the biometric acquisition is performed.

18. The sensor according to claim 17 , wherein

the computer is configured to:

compute the correction that is to be locally applied to the first image by computing a normalized scalar product Γ(x;r)

for a set of at least n vectors S b (x; r) of the first image, each vector S b (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ), and

for n vectors S a (x; r) of the at least one second image, each vector S a (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ),

according to the formula:

Γ( x;r )= S a ( x;r )· S b ( x;r )/ S b ( x;r )· S b ( x;r ); and

generate the information relating to the artificial or non-artificial nature of the material on which the biometric acquisition is performed based on the normalized scalar product Γ(x; r) thus computed.

19. The sensor according to claim 17 , wherein

the computer is configured to:

compute the correction that is to be locally applied to the at least one second image by computing a normalized scalar product β(x; r)

for a set of at least n vectors S b (x; r) of the first image, each vector S b (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ), and

for n vectors S a (x; r) of the at least one second image, each vector S a (x; r) having as components values of pixels that are identified on an image by a same value of the first position parameter (x; r) and occupying different respective positions along the second position parameter (y; θ),

according to the formula:

β( x;r )= S a ( x;r )· S b ( x;r )/ S a ( x;r )· S b ( x;r );

and

generate the information relating to the artificial or non-artificial nature of the material on which the biometric acquisition is performed based on the normalized scalar product β(x; r) thus computed.

20. A non-transitory computer readable medium comprising computer instructions, which, when executed by at least one processor, cause the at least one processor to perform the method according to claim 1 .