CN115985328A - Digital audio watermark blind detection method - Google Patents
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Abstract
The invention provides a blind detection method for a digital audio watermark, which is blind detection, and compared with an exhaustive search method, after frequency adjustment is introduced, the method can relatively quickly find out a corresponding frequency domain adjustment scale factor according to synchronous initial frame information and synchronous end frame information through the combination of coarse adjustment and fine adjustment, thereby accurately obtaining embedded watermark information. The blind detection method for the digital audio watermark obviously improves the attack resistance, can accurately and efficiently detect the watermark information particularly in resisting variable speed attack, and can be particularly applied to the condition of large modulation factor.
Description
Technical Field
The application relates to the technical field of digital audio frequency watermarks, in particular to a digital audio blind detection method.
Background
The audio digital watermark is a section of identification generated or embedded based on the audio digital content, and the identification can be used for identifying the copyright ownership of the audio digital content and also can be used for protecting the integrity of the audio digital content. When the audio watermark is used for identifying the copyright ownership of the audio digital content, the audio watermark is added to the audio digital content in an imperceptible and unpeelable manner in the whole life cycle of the generation, management, distribution and use of the audio digital content, and once copyright dispute occurs, the copyright ownership of the audio digital content can be proved only by extracting the embedded watermark information from the audio digital content. A trademark similar to a commercial product is indicative of a manufacturer of the commercial product, and an audio watermark is indicative of a copyright owner of audio digital content, but this is not a concept with the owner in general. When the audio watermark is used for protecting the integrity of the audio digital content, once the audio digital content is tampered, a certain part is changed, and the corresponding audio watermark information is also changed, so that the tampering can be detected and positioned.
The PSM (Pitch Scale Modification) attack refers to changing the Pitch of a speaker without changing the playing speed of the audio, and this attack does not change the overall playing duration of the audio, but the Pitch change also makes the watermark difficult to extract. Most audio watermarking algorithms, such as spread spectrum watermarking, are location based, i.e. the watermark is embedded in a specific location and detected from that location, whereas a shift caused by a synchronization attack will cause the watermark detection not to be performed at the embedded location, which requires that synchronization is restored before detection. Many algorithms have been developed in the field of image watermarking to combat geometric distortion, in contrast to the audio watermarking algorithm which is much less resistant to synchronization attacks. The synchronization mechanism is the primary problem that needs to be solved by the audio watermarking technology. The audio signal is a time-based one-dimensional signal, and a synchronization attack may cause the position and sequence of audio data to change, resulting in the watermark not being at a preset embedding position, which requires that synchronization be restored before detection. Several methods are currently used to combat synchronization attacks: exhaustive search, explicit synchronization, embedded redundant watermarks, constant watermarks, implicit synchronization, cyclic correlation, etc. Each synchronization mode has respective advantages and disadvantages, needs to be designed specifically according to a specific watermark embedding and extracting scheme as much as possible, and still has a great difficulty in the technical field of current audio watermarking for the problem of anti-modulation attack (the reason is that the destructiveness of the synchronization structure of the audio is extremely strong, but the influence on the auditory effect of the audio is very small).
The digital audio watermarking algorithm mainly needs to have the following characteristics: 1) The watermark must be embedded in the host audio data and cannot be stored in the header or in a separate file. 2) The watermark should not produce audible distortion to the sound quality of the original audio, i.e. should be transparent. 3) The watermark must be robust against common signal processing operations on the host audio signal, such as compression, filtering, resampling, requantization, cropping, and noise addition. 4) The watermark should be easy to embed and low computationally to extract and detect in order to facilitate its integration into a typical electronic product. 5) The watermarking algorithm must have some kind of synchronization mechanism to combat synchronization attacks in the time domain. 6) In principle the detection of the watermark should not require the original audio, i.e. a blind detection is achieved, since it is very difficult to find the original audio. The watermarking algorithm should be public and the security preferably relies on the key rather than the secrecy of the algorithm.
Disclosure of Invention
The invention aims to solve at least the problems of the prior digital audio watermark detection and provides a digital audio watermark blind detection method, which comprises the following steps: s101: setting a threshold value T value (ii) a S102: performing frame-dividing FFT on the audio signal to be tested to obtain F t (N), wherein the framing length is set to be N, N is more than or equal to 1 and less than or equal to N, and the watermark information of the signal to be detected is composed of a synchronous start frame AA + a watermark + a synchronous end frame BB; s103: setting a frequency adjustment value, setting a starting adjustment value and a frequency adjustment interval by using-10% of the attack range of the PSM, calculating a corresponding cycle length, and converting a corresponding frequency value into alpha; s104: calculating an adjustment scaling factor beta, wherein beta = 1/alpha; s105: roughly adjusting the frequency, calculating corresponding synchronous initial frame information AA ' and synchronous end frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB '; s106: judging whether circulation is finished, namely whether calculation in the whole PSM attack range is finished, if circulation is not finished, increasing and adjusting a scale factor according to a frequency adjustment interval, jumping to the step S104, and if circulation is finished, continuing the next step; s107: rank CC 'and find the CC' minimum, and the corresponding scale factor beta 1 A value; s108: the first stage detects the watermark and judges whether the minimum value of CC' is less than or equal toAt a predetermined threshold, if the minimum value of CC' is less than or equal to a predetermined threshold T value According to the obtained beta 1 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is larger than the set threshold value T value Then the next operation is carried out; s109: recalculating to obtain an adjusted scale factor beta, wherein the initial parameter of the beta is based on the beta 1 The value, the number taking interval is 1/10 of the original value, the new cycle number is determined according to the interval, and the adjusting range is also beta 1 Taking the value as the center, and taking 1/10 of the original value; s110: fine adjusting frequency, calculating corresponding synchronous initial frame information AA ' and synchronous end frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB '; s111: judging whether circulation is completed or not, namely whether calculation in the whole PSM attack range is completed or not, if circulation is not completed, increasing an adjustment scale factor according to a frequency adjustment interval, skipping to the step S109, and if circulation is completed, continuing the next step; s112: rank CC' to find the minimum value and the corresponding scale factor beta 2 A value; s113: the second stage detects the watermark and judges whether the minimum value of CC' is less than or equal to the set threshold value T value If the minimum value of CC' is less than or equal to the set threshold value T value Directly from the beta obtained 2 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is greater than the set threshold value T value Then adjust the threshold value T value Restarting to step S102 until the last CC 'or CC' is less than or equal to the predetermined threshold T value 。
Further, the step S104 and the step S109 calculate the adjustment scale factor β as: first using a vector i F Is indexed, wherein i F N = 1; another index vector i X Is obtained by mixing i F The result of/β is calculated by rounding to the nearest integer; i all right angle X Is determined by the value ofThe latter vector D t (ii) a Then judging the relation between beta and 1, if beta is more than 1, calculating corresponding i X If i is X Element n is a unique value m, then D t (m)＝F t (n); when i is X When the element median has repetition (assuming that x +1 element repetition), i.e. the value of the n-th, n + 1-th to n + x-th elements is equal, then
If β < 1, then i X Is not continuous; if i is X Is n, then D t (n)＝F t (n); if i X Has a value of m, and m ≠ n, then D t (n)＝F t (n), the other elements of the vector may be obtained by interpolation.
Further, the step S105 of calculating the value CC ' corresponding to the adjusted frequency according to the AA ' and the BB ' specifically includes: performing XOR on AA and BB' and AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC' after this frequency adjustment.
Further, the step S110 of calculating the value CC corresponding to the adjusted frequency according to the AA "and the BB" specifically includes: performing XOR on AA and BB and each bit of AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC "after this frequency adjustment.
Further, the threshold T is adjusted in step S113 value The method specifically comprises the following steps: will threshold value T value The threshold is adjusted to 1.5 to 2 times the set threshold.
Further, F in step S102 t (n) is the positive frequency part, i.e. F t (1:N/2)。
The blind detection method of the digital audio frequency provided by the invention has the following beneficial effects:
(1) The invention has obviously improved anti-attack performance, can more accurately and efficiently detect the watermark information especially in resisting variable speed attack, and can be particularly applied to the condition of larger tone variation factor.
(2) After frequency adjustment is introduced, compared with an exhaustive search method, the method can relatively quickly find out the corresponding frequency domain adjustment scale factor according to the synchronous starting frame information and the synchronous ending frame information through the combination of coarse adjustment and fine adjustment, so that the embedded watermark information can be accurately obtained.
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FIG. 1 is a flow chart of a method for blind detection of digital audio watermarks in accordance with the present invention;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The main difference of the invention lies in the watermark detecting part of the digital audio, and the embedding part of the digital audio watermark is basically similar to the existing method, and the difference is that a watermark starting frame and a watermark ending frame are respectively added in front of and behind the original watermark. The specific way for embedding in the time domain is as follows: spread spectrum modulation is carried out on a Pseudo-random noise (PN) sequence by using watermark information bits, namely, exclusive or multiplication operation is carried out on one watermark information bit and the whole binary PN sequence to form a watermark signal, then addition operation is adopted to embed the watermark signal into an audio signal sampling value, and the watermark signal is shaped by utilizing the masking effect of HAS before embedding so as to ensure that the watermark signal is not perceived. The watermark information is composed of a synchronous start frame, watermark information and a synchronous end frame, namely AA (synchronous start frame) + normal watermark + BB (synchronous end frame), wherein AA is synchronous start frame information, and BB is synchronous end frame information.
The blind detection method of the digital audio watermark of the present invention is mainly described below.
Referring to fig. 1, an embodiment of the present invention discloses a flow chart of a digital audio blind detection method, and the specific operation steps are as follows.
S101: setting a threshold value T value ；
S102: framing F of audio signal to be testedFT conversion to F t And (N), wherein the framing length is set to be N, N is more than or equal to 1 and less than or equal to N, and the watermark information of the signal to be detected is composed of a synchronous start frame AA + a watermark + a synchronous end frame BB. It should be noted that, considering the conjugate symmetry of the spectrum, only F is processed here t Positive frequency part of (n), i.e. F t (1:N/2)。
S103: setting a frequency adjusting value, setting a starting adjusting value and a frequency adjusting interval by using the attack range of the PSM to be-10%, calculating a corresponding cycle length, and converting a corresponding frequency value into alpha.
S104: an adjustment scaling factor β is calculated, where β =1/α.
S105: and roughly adjusting the frequency, calculating corresponding synchronous initial frame information AA ' and synchronous ending frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB '.
S106: and judging whether the circulation is finished or not, namely whether the calculation in the whole PSM attack range is finished or not, if the circulation is not finished, increasing and adjusting a scale factor according to a frequency adjustment interval, jumping to the step S104, and if the circulation is finished, continuing to perform the next step.
S107: rank CC 'and find the CC' minimum, and the corresponding scale factor beta 1 The value is obtained.
S108: the first stage detects the watermark, judges whether the minimum value of CC 'is less than or equal to the set threshold value, if so, the minimum value of CC' is less than or equal to the set threshold value T value According to the obtained beta 1 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is larger than the set threshold value T value Then the next operation is performed.
S109: recalculating to obtain an adjusted scale factor beta, wherein the initial parameter of the beta is based on the beta 1 The value, the number taking interval is 1/10 of the original value, the new cycle number is determined according to the interval, and the adjusting range is also beta 1 The value is taken as the center, and 1/10 of the original value is taken.
S110: and finely adjusting the frequency, calculating corresponding synchronous initial frame information AA ' and synchronous end frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB '.
S111: and judging whether the circulation is finished or not, namely whether the calculation in the whole PSM attack range is finished or not, if the circulation is not finished, increasing the adjustment scale factor according to the frequency adjustment interval, jumping to the step S109, and if the circulation is finished, continuing the next step.
S112: rank CC' to find the minimum value and the corresponding scale factor beta 2 The value is obtained.
S113: the second stage detects the watermark and judges whether the minimum value of CC' is less than or equal to the set threshold value T value If the minimum value of CC' is less than or equal to the set threshold value T value Directly from the beta obtained 2 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is greater than the set threshold value T value Then adjust the threshold value T value Restarting to step S102 until the last CC 'or CC' is less than or equal to the set threshold T value . Note that, here, the threshold T is adjusted value In particular to a threshold value T value The threshold value is adjusted to be 1.5 to 2 times of the original set threshold value.
In this embodiment, the adjustment scale factor β calculated in step S104 and step S109 is specifically: first using a vector i F Is indexed, wherein i F N = 1; another index vector i X Is obtained by mixing i F The result of/β is calculated by rounding to the nearest integer; i.e. i X Determines the vector D after frequency adjustment t (ii) a Then judging the relation between beta and 1, if beta is more than 1, calculating corresponding i X If i is X Element n is a unique value m, then D t (m)＝F t (n); when i is X When there are repetitions of the element median (assuming x +1 repetitions of the element), i.e., the values of the nth, nth +1, up to the nth + x elements are equal
If β < 1, then i X Is not continuous; if i X Is n, then D t (n)＝F t (n); if i X Has a value of m, and m ≠ n, then D t (n)＝F t (n), other elements of the vector may be obtained by interpolation.
In this embodiment, the step S105 of calculating the value CC ' corresponding to the adjusted frequency according to the AA ' and the BB ' specifically includes: performing exclusive OR on AA and BB' and AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC' after this frequency adjustment.
In this embodiment, the step S110 of calculating the value CC corresponding to the adjusted frequency according to the AA "and the BB" specifically includes: performing XOR on AA and BB and each bit of AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC "after this frequency adjustment.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (6)
1. A blind detection method for digital audio watermark is characterized by comprising the following steps:
s101: setting a threshold T value ；
S102: performing frame-dividing FFT on the audio signal to be tested to obtain F t (N), wherein the framing length is set to be N, N is more than or equal to 1 and less than or equal to N, and the watermark information of the signal to be detected is composed of a synchronous start frame AA + a watermark + a synchronous end frame BB;
s103: setting a frequency adjustment value, setting a starting adjustment value and a frequency adjustment interval by using a PSM attack range of-10%, calculating a corresponding cycle length, and converting a corresponding frequency value into alpha;
s104: calculating an adjustment scaling factor beta, wherein beta = 1/alpha;
s105: roughly adjusting the frequency, calculating corresponding synchronous initial frame information AA ' and synchronous end frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB ';
s106: judging whether circulation is finished, namely whether calculation in the whole PSM attack range is finished, if circulation is not finished, increasing and adjusting a scale factor according to a frequency adjustment interval, jumping to the step S104, and if circulation is finished, continuing the next step;
s107: rank CC 'and find the CC' minimum, and the corresponding scale factor beta 1 A value;
s108: the first stage detects the watermark, judges whether the minimum value of CC 'is less than or equal to the set threshold value, if so, the minimum value of CC' is less than or equal to the set threshold value T value According to the obtained beta 1 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is larger than the set threshold value T value Then the next operation is carried out;
s109: recalculating to obtain an adjusted scale factor beta, wherein the initial parameter of the beta is based on the beta 1 The value, the number taking interval is 1/10 of the original value, the new cycle number is determined according to the interval, and the adjusting range is also beta 1 Taking the value as the center, and taking 1/10 of the original value;
s110: fine adjusting frequency, calculating corresponding synchronous initial frame information AA ' and synchronous end frame information BB ' by using linear correlation, and calculating a corresponding value CC ' after frequency adjustment according to the AA ' and the BB ';
s111: judging whether the circulation is finished, namely whether the calculation in the whole PSM attack range is finished, if the circulation is not finished, increasing and adjusting a scale factor according to a frequency adjustment interval, jumping to the step S109, and if the circulation is finished, continuing to perform the next step;
s112: rank CC' to find the minimum value and corresponding scale factor beta 2 A value;
s113: the second stage detects the watermark and judges whether the minimum value of CC' is less than or equal to the set threshold value T value If the minimum value of CC' is less than or equal to the set threshold value T value Directly from the beta obtained 2 Performing FFT inverse transformation on the frequency spectrum corresponding to the value, and calculating linear correlation information between corresponding initial frame information and ending frame information by using linear correlation to obtain the embedded watermark; if the minimum value of CC' is greater than the set threshold value T value Then adjust the threshold value T value Restarting to step S102 until the last CC 'or CC' is less than or equal to the predetermined threshold T value 。
2. The blind digital audio watermark detection method according to claim 1, wherein the scaling factor β calculated in step S104 and step S109 is specifically:
first using a vector i F Is indexed, wherein i F N = 1; another index vector i X Is obtained by mixing i F The result of/β is calculated by rounding to the nearest integer; i.e. i X Determines the vector D after frequency adjustment t ；
Then judging the relation between beta and 1, if beta is greater than 1, calculating corresponding i X If i is X Element n is a unique value m, then D t (m)＝F t (n); when i is X When the element median has repetition (assuming that x +1 element repetition), i.e. the value of the n-th, n + 1-th to n + x-th elements is equal, then
If β < 1, then i X Is not continuous; if i X Is n, then D t (n)＝F t (n); if i X N th element of (2)Is m, and m ≠ n, then D t (n)＝F t (n), the other elements of the vector may be obtained by interpolation.
3. The blind digital audio watermark detection method according to claim 1, wherein the step S105 of calculating the value CC ' corresponding to the adjusted frequency according to the AA ' and the BB ' specifically includes:
performing XOR on AA and BB' and AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC' for this frequency adjustment.
4. The blind digital audio watermark detection method according to claim 1, wherein the step S110 of calculating the value CC corresponding to the adjusted frequency according to the AA "and the BB" specifically includes:
performing XOR on AA and BB and each bit of AA and BB of the signal to be detected, namely
These values are then added together as the corresponding value CC "after this frequency adjustment.
5. The blind digital audio watermark detection method of claim 1, wherein the threshold T is adjusted in step S113 value The method specifically comprises the following steps:
will threshold value T value The threshold is adjusted to be 1.5 to 2 times of the set threshold.
6. The blind digital audio watermark detection method according to any one of claims 1 to 5, wherein F in step S102 t (n) is the positive frequency part, i.e. F t (1:N/2)。
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