Systems and methods for encoding randomly distributed features in an object
First Claim
Patent Images
1. A method comprising:
- determining randomly distributed features in an object;
determining a probability density function associated with the object;
compressing data representing the randomly distributed features, wherein the compressing is based in part on the probability density function;
encoding the compressed data with a signature; and
creating a label comprising the object and the encoded data;
determining vectors associated with the randomly distributed features based, at least in part, on the probability density function; and
encoding the vectors using an arithmetic coding algorithm, wherein the algorithm comprises;
set U as a list of all unit areas in S−
Si−
ulist of all marked units, M(u), is set to M(u)=Ø
dofind all unit areas V=argminν
⊂
U∥
Qν
−
Qu∥
dofind unit area w=argmaxν
ε
Vζ
(1, ν
)set AC range for w to γ
(w,u)set of nodes ordered before w is Mw(u)=M(u)M(u)=M(u)∪
w, V=V−
w, U=U−
wwhile V≠
Ø
while U≠
Ø
.
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Abstract
The described systems and methods described are directed at encoding randomly distributed features in an object. Randomly distributed features in an authentication object are determined. Data representing the randomly distributed features is compressed and encoded with a signature. A label is created and includes the authentication object and the encoded data. The data may be compressed by determining a probability density function associated with the authentication object. Vectors associated with the randomly distributed attributes are determined based, at least in part, on the probability density function. The vectors are encoded using an arithmetic coding algorithm.
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Citations
29 Claims
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1. A method comprising:
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determining randomly distributed features in an object; determining a probability density function associated with the object; compressing data representing the randomly distributed features, wherein the compressing is based in part on the probability density function; encoding the compressed data with a signature; and creating a label comprising the object and the encoded data; determining vectors associated with the randomly distributed features based, at least in part, on the probability density function; and encoding the vectors using an arithmetic coding algorithm, wherein the algorithm comprises; set U as a list of all unit areas in S−
Si−
ulist of all marked units, M(u), is set to M(u)=Ø do find all unit areas V=argminν
⊂
U∥
Qν
−
Qu∥do find unit area w=argmaxν
ε
Vζ
(1, ν
)set AC range for w to γ
(w,u)set of nodes ordered before w is Mw(u)=M(u) M(u)=M(u)∪
w, V=V−
w, U=U−
wwhile V≠
Øwhile U≠
Ø
. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A system comprising
an issuer configured to determine randomly distributed features in an authentication object and to compress data representing the randomly distributed features comprising fibers, the issuer being further configured to encode the compressed data with a signature and to create a label that includes the authentication object and the encoded data; wherein the issuer is further configured to determine a probability density function associated with the authentication object, wherein the probability density function is defined as the likelihood of finding a second end of a fiber at a given location within a non-illuminated area when a first end of the fiber is located within an illuminated area of the authentication object, to determine vectors associated with the randomly distributed attributes based, at least in part, on the probability density function, and to encode a portion of the vectors as a path by applying an arithmetic coding algorithm, wherein the algorithm comprises; set U as a list of all unit areas in S−
Si−
ulist of all marked units, M(u), is set to M(u)=Ø do find all unit areas V=argminν
⊂
U∥
Qν
−
Qu∥do find unit area w=argmaxν
ε
Vζ
(1, ν
)set AC range for w to γ
(w,u)set of nodes ordered before w is Mw(u)=M(u) M(u)=M(u)∪
w, V=V−
w, U=U−
wwhile V≠
Øwhile U≠
Ø
.- View Dependent Claims (15, 16, 17, 18, 19)
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20. A label comprising:
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an authentication object including randomly distributed features; and encoded information associated with the authentication object, the information being encoded with a signature and including compressed data representing the randomly distributed features in the authentication object, wherein the data in the encoded information is compressed by; determining a probability density function associated with the authentication object; determining vectors associated with the randomly distributed attributes based, at least in part, on the probability density function; and encoding the vectors using an arithmetic coding algorithm; wherein the label is self-authenticated by comparing the compressed data in the encoded information and the data representing the randomly distributed features obtained by analyzing the authentication object; and wherein the compressed data was compressed by; determining vectors associated with the randomly distributed features based, at least in part, on the probability density function; and encoding the vectors using an arithmetic coding algorithm, wherein the algorithm comprises; set U as a list of all unit areas in S−
Si−
u,list of all marked units, M(u), is set to M(u)=Ø
,do find all unit areas V=argminν
⊂
U∥
Qν
−
Qu∥
, dofind unit area w=argmaxν
ε
Vζ
(1, ν
),set AC range for w to γ
(w,u) (see Eqns. 17,
18),set of nodes ordered before w is Mw(u)=M(u), M(u)=M(u)∪
w, V=V−
w, U=U−
w,while V≠
Øwhile U≠
Ø
. - View Dependent Claims (21, 22, 23, 24)
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25. An apparatus comprising:
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means for determining randomly distributed features in an authentication object; means for determining a probability density function associated with the authentication object, wherein the probability density function defines a likelihood a point will contain an illuminated second end of a fiber and is conditioned on location of a first end of the fiber in an illuminated region; means for compressing data representing the randomly distributed features, wherein the compressing is based in part on the probability density function; means for encoding the data with a signature; and means for creating a label that includes the authentication object and the encoded data, means for determining vectors associated with the randomly distributed features based, at least in part, on the probability density function; and means for encoding the vectors using an arithmetic coding algorithm, wherein the algorithm comprises; set U as a list of all unit areas in S−
Si−
u,list of all marked units, M(u), is set to M(u)=Ø
,do find all unit areas V=argminν
⊂
U∥
Qν
−
Qu∥
,do find unit area w=argmaxν
ε
Vζ
(1, ν
),set AC range for w to γ
(w,u) (see Eqns. 17,
18),set of nodes ordered before w is Mw(u)=M(u), M(u)=M(u)∪
w, V=V−
w, U=U−
w,while V≠
Øwhile U≠
Ø
. - View Dependent Claims (26, 27, 28, 29)
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Specification