Apparatus and method for inserting and detecting watermark based on stochastic model

1. An apparatus for inserting a watermark based on a stochastic model, said apparatus comprising:

means for generating a spread spectrum signal by using a user key from outside;

means for estimating an autocorrelation matrix of an original signal from outside as an object for inserting a watermark;

means for decomposing the autocorrelation matrix to an eigenvector matrix and an eigenvalue matrix;

means for shaping a watermark from the spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix; and

means for adding the watermark to the original signal.

2. The apparatus as recited in claim 1 , wherein said means for shaping a watermark uses a watermark transformation coefficient in the process of making a watermark from a spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix.

3. The apparatus as recited in claim 1 , wherein said means for shaping a watermark controls the strength of a watermark by using a scaling coefficient.

4. The apparatus as recited in claim 3 , wherein said means for shaping a watermark controls by a scaling coefficient the power of an watermark in order to get a desirable SNR, the diagonal elements of the eigenvlaue matrix are exponentially multiplied by the watermark transformation coefficient, and a spread spectrum signal is transformed to a watermark signal by using a transformation coefficient, a scaling coefficient, an eigenvector matrix and an eigenvalue matrix.

5. The apparatus as recited in claim 3 , wherein said means for estimating an autocorrelation determines in a time domain autocorrelation coefficients by using Ergodic theorem, and then a Toepliz autocorrelation matrix by using the autocorrelation coefficients.

6. An apparatus for detecting a watermark based on a stochastic model, said apparatus comprising:

means for generating a spread spectrum signal by using a user key inputted from outside;

means for estimating an autocorrelation matrix of an original signal from a watermark-inserted signal received;

means for decomposing the autocorrelation matrix to an eigenvector matrix and an eigenvalue matrix;

means for shaping a watermark from a spread spectrum signal in reference to the eigenvector matrix and the eigenvalue matrix;

in order to detect a watermark without using an original audio signal, means for filtering for whitening the watermark-inserted signal by using both the eigenvector matrix and the eigenvalue matrix from the means of decomposing;

means for measuring correlation to find correlation between a watermark signal from said means for shaping a watermark and a whitening-filtered signal from said means for filtering for whitening; and

means for determining whether there is a watermark by referring to a correlation value from said means for measuring correlation, whether or not a received signal includes a watermark.

7. The apparatus as set forth in claim 6 , wherein said means of shaping a watermark uses a watermark transformation coefficient in the process of making a watermark from a spread spectrum signal in reference to both the eigenvector matrix the eigenvalue matrix.

8. The apparatus as recited in claim 6 , wherein said means for shaping a watermark controls the strength of a watermark by using a scaling coefficient.

9. The apparatus as recited claim 8 , wherein said means for filtering for whitening performs filtering for whitening after calculating an inverse eigenvalue matrix and obtaining a whitening filter matrix by using a transforming coefficient, an error-tolerant coefficient, and diagonal elements of an inverse eigenvalue matrix.

10. A method for inserting a watermark based on a stochastic model, said method comprising the steps of:

a) generating a spread spectrum signal by using a user key inputted from outside;

b) estimating an autocorrelation matrix of an original signal from outside as an object for inserting a watermark;

c) decomposing an autocorrelation matrix to an eigenvector matrix and an eigenvalue matrix;

d) shaping a watermark from the spread spectrum signal produced in the step a) in reference to both the eigenvector matrix and the eigenvalue matrix; and

e) adding a watermark produced by said step d) to the original signal from outside.

11. The method as recited in claim 10 , wherein said step d) uses a watermark transformation coefficient in the process of making a watermark from a spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix.

12. The method as recited in either claim 10 , wherein said step d) controls the strength of a watermark by using a scaling coefficient.

13. The method as recited in claim 12 , wherein said step d) controls by a scaling coefficient the power of an watermark in order to get a desirable SNR, the diagonal elements of the eigenvlaue matrix are exponentially multiplied by the watermark transformation coefficient, the spread spectrum signal is transformed to a watermark signal by using a transformation coefficient, a scaling coefficient, an eigenvector matrix and an eigenvalue matrix.

14. The method as recited in claim 10 , wherein said step b) includes the steps of:

b1) determining in a time domain autocorrelation coefficients by using Ergodic theorem; and

b2) the seventh step to determine a Toepliz autocorrelation matrix by using the autocorrelation coefficients.

15. A method for detecting a watermark based on a stochastic model, said method comprising the steps of:

a) generating a spread spectrum signal by using a user key inputted from outside;

b) estimating an autocorrelation matrix of an original signal from a watermark-inserted signal received;

c) decomposing an autocorrelation matrix estimated at said step b) to both an eigenvector matrix and an eigenvalue matrix;

d) shaping a watermark from the spread spectrum signal produced in said step a) in reference to both the eigenvector matrix and the eigenvalue matrix;

e) in order to detect a watermark without using an original audio signal, filtering for whitening a watermark-inserted signal by using both the eigenvector matrix and the eigenvalue matrix from said step c);

f) measuring correlation between a watermark signal from said step d) and a whitening-filtered signal from said step e); and

g) determining, by referring to a correlation value from said step f), whether or not a received signal includes a watermark.

16. The method as recited in claim 15 , wherein said step d) to shape a watermark uses a watermark transformation coefficient in the process of making a watermark from a spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix.

17. The method as recited in claim 15 , wherein said step d) controls the strength of a watermark by using a scaling coefficient.

18. The method as recited in claim 17 , wherein said step e) performs filtering for whitening after calculating an inverse eigenvalue matrix and obtaining a whitening filter matrix by using a transforming coefficient, an error-tolerant coefficient, and diagonal elements of an inverse eigenvalue matrix.

19. A computer readable medium storing a program for executing method for inserting a watermark based on a stochastic model, wherein the computer readable medium is in apparatus for inserting a watermark having a processor, the program comprising the functions of:

a) generating a spread spectrum signal by using a user key inputted from outside;

b) estimating an autocorrelation matrix of an original signal from outside as an object for inserting a watermark;

c) decomposing an autocorrelation matrix estimated at the function b) to an eigenvector matrix and an eigenvalue matrix;

d) shaping a watermark from a spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix; and

e) adding the watermark to the original signal from outside.

20. A computer readable medium storing a program for executing method for detecting a watermark based on a stochastic model, wherein the computer readable medium is in apparatus for detecting a watermark having a processor, the program comprising the functions of:

a) generating a spread spectrum signal by using a user key inputted from outside;

b) estimating an autocorrelation matrix of an original signal from a watermark-inserted signal received from outside as an object for detecting a watermark;

c) decomposing an autocorrelation matrix estimated at said second function to an eigenvector matrix and an eigenvalue matrix;

d) shaping a watermark from a spread spectrum signal in reference to both the eigenvector matrix and the eigenvalue matrix;

e) in order to detect a watermark without using an original audio signal, filtering for whitening a watermark-inserted signal by using both the eigenvector matrix and the eigenvalue matrix from the function c);

f) measuring correlation between a watermark signal from the function d) and a whitening-filtered signal from the function e); and

g) determining whether or not a received signal includes a watermark by referring to a correlation value from the function f).