US 9,499,006 B2Granted

Anti-counterfeiting feature generation method for valuable document and authentication method and device therefor

AssigneeGRG Banking Equipment Co., Ltd.

InventorsTiancai Liang, Yuanchao Yu, Weifeng Wang, Xiaoliang Wang

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Abstract

An anti-counterfeiting feature generation method for a valuable document and an authentication method and device therefor. The anti-counterfeiting feature generation method for a valuable document uses the anti-counterfeiting feature information redundancy to hide accurate information about an anti-counterfeiting feature. In the generation method, the anti-counterfeiting feature of a valuable document has little change on the human perception, but a valuable document authentication device in a financial self-service equipment can effectively extract the hidden accurate information about an anti-counterfeiting feature from signals obtained by a sensor and conduct quantitative detection and authentication, thereby effectively authenticating whether the valuable document is counterfeit or not. A new anti-counterfeiting feature which facilitates machine recognition is loaded to the valuable document, and a corresponding valuable document authentication device is configured to a financial self-service equipment, so that the financial self-service equipment can read the anti-counterfeiting feature of the valuable document by facilitating machine recognition, thereby improving the authentication accuracy of the financial self-service equipment to the valuable document.

Claims3

Dependent claims

A method for generating an anti-counterfeiting feature for a valuable document, comprising:

step one, scanning an original anti-counterfeiting feature M on the valuable document by a sensor, to obtain M1 composed of partial information M10 sensitive for human perception and partial information M11 insensitive for human perception, and setting M2 to denote accurate anti-counterfeiting characteristic information of the original anti-counterfeiting feature M that is not obtainable by the sensor, M2 being composed of partial information M20 sensitive for human perception and partial information M21 insensitive for human perception, wherein M is an image of a number in optically variable ink showing a denomination, M1 is a pixel matrix f1(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by a human eye when the valuable document is viewed at a right angle, and M2 is a pixel matrix f2(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by the human eye when the valuable document is viewed at a non-right angle;
step two,
performing a wavelet transform W on the pixel matrixes for frequency-domain transform:
W[f1]=R1,
W[f2]=R2
where
R
1
=
[
H
1
⁢
H
1
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
⁢
⁢
and
⁢
⁢
R
2
=
[
H
2
⁢
H
2
H
2
⁢
L
2
H
2
⁢
L
2
L
2
⁢
L
2
]
,
R1 and R2 represent frequency-domain coefficient matrixes obtained from the wavelet transform on f1(x, y) and f2(x, y) respectively, H1H1 in R1 represents a highest-frequency coefficient and L2L2 in R2 represents a lowest-frequency coefficient;
step three, substituting L2L2 in R2 for H1H1 in R1, and obtaining the following equation:
R
1
′
=
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
and performing an inverse M of the wavelet transform W on R1′:
M
R
=
M
⁡
(
R
1
′
)
=
M
⁡
(
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
)
,
so as to inverse the wavelet coefficient matrix R1′ to a pixel matrix MR in the spatial domain;
and
step four, adding the pixel matrix MR in the spatial domain onto the valuable document and generating the anti-counterfeiting feature.

129 more elements

A method for identifying an anti-counterfeiting feature for a valuable document, comprising:

extracting a hidden anti-counterfeiting characteristic of the valuable document and performing accurate identification on the anti-counterfeiting feature of the valuable document, wherein
a wavelet transform W is performed on a pixel matrix f3(x, y) in the spatial domain of an image of a number in a region of the anti-counterfeiting feature, W[f3]=R3, and the following equation is obtained:
R
3
=
[
H
3
⁢
H
3
H
3
⁢
L
3
H
3
⁢
L
3
L
3
⁢
L
3
]
(
Equation
⁢
⁢
2
)
wherein
an original anti-counterfeiting feature M on a real valuable document is scanned by a sensor, to obtain M1 composed of partial information M10 sensitive for human perception and partial information M11 insensitive for human perception, and M2 is set to denote accurate anti-counterfeiting characteristic information of the original anti-counterfeiting feature M that is not obtainable by the sensor, M2 being composed of partial information M20 sensitive for human perception and partial information M21 insensitive for human perception, wherein M is an image of a number in optically variable ink showing a denomination, M1 is a pixel matrix f1(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by a human eye when the real valuable document is viewed at a right angle, and M2 is a pixel matrix f2(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by the human eye when the real valuable document is viewed at a non-right angle;
the wavelet transform W is performed on the pixel matrixes f1(x, y) and f2(x, y) for frequency-domain transform:
W[f1]=R1,
W[f2]=R2
wherein
R
1
=
[
H
1
⁢
H
1
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
⁢
⁢
and
⁢
⁢
R
2
=
[
H
2
⁢
H
2
H
2
⁢
L
2
H
2
⁢
L
2
L
2
⁢
L
2
]
,
R1 and R2 represent frequency-domain coefficient matrixes obtained from the wavelet transform on f1(x, y) and f2(x, y) respectively, H1H1 in R1 represents a highest-frequency coefficient and L2L2 in R2 represents a lowest-frequency coefficient;
L2L2 in R2 substitutes for H1H1 in R1, and the following equation is obtained:
R
1
′
=
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
and an inverse M of the wavelet transform W is performed on R1′:
M
R
=
M
⁡
(
R
1
′
)
=
M
⁡
(
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
)
,
so as to inverse the wavelet coefficient matrix R1′ to a pixel matrix MR in the spatial domain;
and
the pixel matrix MR in the spatial domain is added onto the real valuable document;
coefficients contained in the coefficient matrix H3H3 present a strong similarity to those coefficients contained in the coefficient matrix L2L2,
the coefficients contained in H3H3 are arranged as a one-dimensional data sequence:
h=[h1, h2, . . . , hn];
and the coefficients contained in L2L2 are arranged as a one-dimensional data sequence:
l=[l1, l2, . . . , ln],
similarity K1 between the data sequences h=[h1, h2, . . . , hn] and l=[l1, l2, . . . , ln] is detected based on a similarity determining criterion, and if K1 is greater than a predetermined threshold K, the valuable document is identified to be real;
otherwise, the valuable document is identified to be false and is rejected.

169 more elements

An apparatus for identifying an anti-counterfeiting feature for a valuable document, comprising at least one processor and a memory having processor-executable instructions stored therein, and the instructions when executed by the at least one processor, configure the apparatus to

extract a hidden anti-counterfeiting characteristic of the valuable document and perform accurate identification on the anti-counterfeiting feature of the valuable document, wherein
a wavelet transform W is performed on a pixel matrix f3(x, y) in the spatial domain of an image of a number in a region of the anti-counterfeiting feature, W[f3]=R3, and the following equation is obtained:
R
3
=
[
H
3
⁢
H
3
H
3
⁢
L
3
H
3
⁢
L
3
L
3
⁢
L
3
]
,
wherein
an original anti-counterfeiting feature M on a real valuable document is scanned by a sensor, to obtain M1 composed of partial information M10 sensitive for human perception and partial information M11 insensitive for human perception, and M2 is set to denote accurate anti-counterfeiting characteristic information of the original anti-counterfeiting feature M that is not obtainable by the sensor, M2 being composed of partial information M20 sensitive for human perception and partial information M21 insensitive for human perception, wherein M is an image of a number in optically variable ink showing a denomination, M1 is a pixel matrix f1(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by a human eye when the real valuable document is viewed at a right angle, and M2 is a pixel matrix f2(x, y) in the spatial domain representing the image of the number in optically variable ink showing the denomination as perceived by the human eye when the real valuable document is viewed at a non-right angle;
the wavelet transform W is performed on the pixel matrixes f1(x, y) and f2(x, y) for frequency-domain transform:
W[f1]=R1,
W[f2]=R2
wherein
R
1
=
[
H
1
⁢
H
1
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
,
⁢
and
⁢
⁢
R
2
=
[
H
2
⁢
H
2
H
2
⁢
L
2
H
2
⁢
L
2
L
2
⁢
L
2
]
,
R1 and R2 represent frequency-domain coefficient matrixes obtained from the wavelet transform on f1(x, y) and f2(x, y) respectively, H1H1 in R1 represents a highest-frequency coefficient and L2L2 in R2 represents a lowest-frequency coefficient;
L2L2 in R2 substitutes for H1H1 in R1, and the following equation is obtained:
R
1
′
=
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
and an inverse M of the wavelet transform W is performed on R1′:
M
R
=
M
⁡
(
R
1
′
)
=
M
⁡
(
[
L
2
⁢
L
2
H
1
⁢
L
1
H
1
⁢
L
1
L
1
⁢
L
1
]
)
,
so as to inverse the wavelet coefficient matrix R1′ to a pixel matrix MR in the spatial domain;
and
the pixel matrix MR in the spatial domain is added onto the real valuable document;
coefficients contained in the coefficient matrix H3H3 present a strong similarity to those coefficients contained in the coefficient matrix L2L2,
the coefficients contained in H3H3 are arranged as a one-dimensional data sequence:
h=[h1, h2, . . . , hn];
and the coefficients contained in L2L2 are arranged as a one-dimensional data sequence:
l=[l1, l2, . . . , ln],
similarity K1 between the data sequences h=[h1, h2, . . . , hn] and l=[l1, l2, . . . , ln] is detected based on a similarity determining criterion, and if K1 is greater than a predetermined threshold K, the valuable document is identified to be real;
otherwise, the valuable document is identified to be false and is rejected.

164 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/426,949Filed 19 Mar 2013
Priority: CN 2012 1 037665829 Sep 2012
Published: US 2015/0217591 A16 Aug 2015
Granted: 22 Nov 2016
Term ends: Not estimatedThe source records don’t support an estimate.

Classification9 codes

B42D 25/30
Information-bearing cards or sheet-like structures characterised by identification or security features; Manufacture thereof: identification or…
B42D 25/405
Manufacture: marking
G07D 7/0034
Using security elements: using watermarks
G07D 7/0053
Testing security markings invisible to the naked eye, e.g. verifying thickened lines or unobtrusive markings or alterations: involving markings…