CN105608661B - Based on the robust QR shearing wave zone audio frequency watermark insertion decomposed and detection method - Google Patents
Based on the robust QR shearing wave zone audio frequency watermark insertion decomposed and detection method Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 6
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
- G06T1/005—Robust watermarking, e.g. average attack or collusion attack resistant
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract
The present invention discloses a kind of insertion of shearing wave zone audio frequency watermark and detection method decomposed based on robust QR, utilize the good frequency localization feature of non-lower sampling shearing wave conversion, multidirectional, translation invariance and close to optimal rarefaction representation ability, and each sub-band audio and original audio length having the same after decomposing, in addition QR decomposes good numerical stability, it is a upper stable triangular matrix that it, which decomposes obtained R matrix, it embeds a watermark in the upper triangle of R matrix, in conjunction with synchronous code technology.The results showed that the present invention can either resist conventional signal processing, and it is effective against desynchronization attack, there is good not sentience and robustness.In addition, also having many advantages, such as that design is simple, being easily achieved.
Description
Technical Field
The invention belongs to the technical field of digital audio watermarking, and particularly relates to a shear wave domain audio watermarking embedding and detecting method based on robust QR decomposition, which can resist conventional signal processing and effectively resist desynchronization attack.
Background
Digital Watermarking (Digital Watermarking) is a new technology that can protect copyright and authenticate origin and integrity in an open network environment. The audio watermarking technology is that a mark (watermark) with specific significance is hidden in a digital audio product by using a data embedding method to prove the ownership of a creator to the work, and the mark is used as a basis for identifying and claiming illegal infringement, and the detection and analysis of the watermark ensure the integrity and reliability of digital information, so that the audio watermarking technology becomes an effective means for intellectual property protection and digital multimedia anti-counterfeiting. Digital audio watermarking is bound to be attacked in various forms, and attacks on a watermarking system are divided into conventional attacks and desynchronization attacks. Conventional attacks include adding noise, resampling, filtering, MP3 compression, etc., which results in a reduction in the energy of the watermark signal; the desynchronization attack comprises jitter attack, amplitude change, tone change, shearing, time scale scaling and the like, and the attack operation can cause the original watermark and the extracted watermark to generate synchronization error, so that the accurate watermark cannot be detected.
The existing digital audio watermarking methods can be roughly divided into two categories of time domain and transform domain. The time domain is embedded with the watermark by modifying the time domain sampling value of the host audio signal, and the method has poor anti-attack capability and small watermark capacity. The transformation domain is embedded by modifying the transformation domain coefficient of the host audio signal, the common transformation comprises Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Lifting Wavelet Transform (LWT) and the like, and the method has strong anti-attack capability and large watermark capacity and is compatible with the data compression standard. Shear wave transformation in a transformation domain is constructed by Guo et al in 2007, the method can generate optimal approximation and realize discretization, and certain research results are achieved in the fields of image denoising, image fusion, target edge detection and the like. However, most existing audio watermarking algorithms can only resist conventional signal processing, and cannot effectively resist desynchronization attacks.
Disclosure of Invention
The invention aims to solve the technical problems in the prior art, and provides a shear wave domain audio watermark embedding and detecting method based on robust QR decomposition, which can resist conventional signal processing and effectively resist desynchronization attack.
The technical solution of the invention is as follows: a shear wave domain audio watermark embedding method based on robust QR decomposition is characterized by comprising the following steps:
step 11: watermark coding: two-value watermark imageScrambling and encrypting into a secure watermark matrixWherein
And then, performing dimension reduction treatment on the watermark image, namely converting the two-dimensional watermark image into a one-dimensional binary watermark sequence:
finally, according to the following formula, toBPSK modulation mapping is carried out to obtain a one-dimensional reversed phase sequence of { -1,1 { (R) }：
；
Step 12: segmenting an original audio carrier according to the size of the digital watermark and the size of the synchronous code, and then embedding the synchronous code by utilizing the statistical characteristic of the time domain audio sample, wherein the method specifically comprises the following steps:
step 121: will be provided withAccording to the length of the synchronization codeIs divided intoSegments of eachComprisesAn audio sample, i.e.
；
Step 122: computingAverage value of (i), i.e.
；
Step 123: the synchronisation code is embedded by quantization, i.e. for each segmentModifying the mean value thereofWith the embedded one-bit sync code, the modification strategy is:
wherein,in order to modify the pre-audio sample values,is a modified audio sample value and has
=,
Wherein,in order to perform the operation of taking the modulus,is a quantization step size;
step 13: embedding of watermark signal:
step 131: mapping the rear half part of the audio frequency into a two-dimensional matrix form, and performing non-subsampled shear wave transformation to obtain a low-frequency sub-band;
step 132: partitioning the low-frequency sub-band according to the length of the watermark, and carrying out QR decomposition on each small block matrix to obtain an upper triangular matrix R;
step 133: selecting the first row of elements of the R matrix for watermark embedding and modifying the strengthAndis determined by the size of the watermark information bitThe decision, the formula is as follows:
whereinIs a quantization step size;
step 134: byAndcalculating a quantization resultAndthe formula is as follows:
wherein，floor(.) is rounded down, ceil (.) is rounded up,c is the first row element coefficient of the R matrix for the quantization step;
step 135: the watermark is embedded in the first row of coefficients of the R matrix, as follows:
where C is the coefficient selected to embed the watermark,taking the absolute value of abs (.) for the modified coefficients;
step 136: by usingReplacing the first row element coefficient C of the R matrix, carrying out inverse QR decomposition to obtain sub-blocks containing watermarks, then reconstructing all the sub-blocks containing the watermarks back to obtain low-frequency sub-bands containing the watermarks, combining the low-frequency sub-band coefficients containing the watermarks with the high-frequency sub-band coefficients by utilizing non-subsampled inverse shear wave transformation to obtain two-dimensional form audio containing the watermarks, finally reducing the two-dimensional form audio into one-dimensional form audio, and reconstructing the one-dimensional form audio into the original audio data section to obtain digital audio containing the watermarks;
step 14: and repeating the step 2 to the step 3 to embed the synchronous codes and the watermark information into other audio data segments.
The shear wave domain audio watermark detection method based on robust QR decomposition corresponding to the embedding method is characterized by comprising the following steps
Step 21: searching a synchronous code by adopting a frame synchronous code bit-by-bit comparison mode in the communication field, and taking an audio data segment between two adjacent synchronous codes as a candidate audio data segment of the watermark to be extracted according to the detected synchronous code;
step 22: the extraction of the watermark signal is as follows:
step 221: mapping the obtained audio data segment containing the watermark into a two-dimensional form, performing non-subsampled shear wave transformation to obtain low-frequency sub-bands, partitioning the low-frequency sub-bands, and performing QR decomposition on each sub-block to obtain an upper triangular matrix；
Step 222: selectingThe first row of elements of the matrix is subjected to watermark extraction, and the formula is as follows:
whereinCeil (.) is rounding up,is a matrixThe coefficients of the first row of elements of (c),in order to quantize the step size,is a modulo arithmetic function;
step 23: repeating the steps 21 to 22, extracting the watermark of the audio watermark data section between each two adjacent synchronous codes, and solving the optimal watermark information by using a majority principle:
；
step 24: watermark decoding:
extracting optimal watermark information for allDemodulating BPSK modulation to obtain binary sequence：
；
To pairPerforming dimension increasing processing to obtain a watermark image matrixThen go right againInverse scrambling and decryption are carried out to obtain the extracted binary image watermark：
。
The shear wave domain audio watermark embedding and detecting method based on robust QR decomposition is designed by utilizing the frequency domain localization characteristic, the multi-directivity, the translation invariance and the approximate optimal sparse representation capability of the non-downsampling shear wave transformation, the decomposed sub-band audio frequency has the same length as the original audio frequency, the numerical stability of the QR decomposition is added, the R matrix obtained by the decomposition is an upper triangular stable matrix, the watermark is embedded in the upper triangle of the R matrix, and the synchronous code technology is combined. The experimental results show that: the invention can resist conventional signal processing and effectively resist desynchronization attack, and has good imperceptibility and robustness. In addition, the method has the advantages of simple design, easy realization and the like.
Drawings
Fig. 1 is a waveform diagram of original audio according to an embodiment of the present invention.
Fig. 2 is a waveform diagram of audio after embedding a watermark according to an embodiment of the present invention.
Detailed Description
A shear wave domain audio watermark embedding method based on robust QR decomposition is characterized by comprising the following steps:
step 11: watermark coding: two-value watermark imageScrambling and encrypting into a secure watermark matrixWherein
In order to facilitate embedding the two-dimensional watermark image into the one-dimensional audio signal, dimension reduction processing is performed on the two-dimensional watermark image, that is, the two-dimensional watermark image is converted into a one-dimensional binary watermark sequence:
finally, according to the following formula, toBPSK modulation mapping is carried out to obtain a one-dimensional reversed phase sequence of { -1,1 { (R) }：
；
Step 12: segmenting an original audio carrier according to the size of the digital watermark and the size of the synchronous code, and then embedding the synchronous code by utilizing the statistical characteristic of the time domain audio sample, wherein the method specifically comprises the following steps:
step 121: will be provided withAccording to the length of the synchronization codeIs divided intoSegments of eachComprisesAn audio sample, i.e.
；
Step 122: computingAverage value of (i), i.e.
；
Step 123: the synchronisation code is embedded by quantization, i.e. for each segmentModifying the mean value thereofWith the embedded one-bit sync code, the modification strategy is:
wherein,in order to modify the pre-audio sample values,is a modified audio sample value and has
=,
Wherein,in order to perform the operation of taking the modulus,is a quantization step size;
step 13: embedding of watermark signal:
step 131: mapping the rear half part of the audio frequency into a two-dimensional matrix form, and performing non-subsampled shear wave transformation to obtain a low-frequency sub-band;
step 132: partitioning the low-frequency sub-band according to the length of the watermark, and carrying out QR decomposition on each small block matrix to obtain an upper triangular matrix R;
step 133: selecting the first row of elements of the R matrix for watermark embedding and modifying the strengthAndis determined by the size of the watermark information bitThe decision, the formula is as follows:
whereinIs a quantization step size;
step 134: byAndcalculating a quantization resultAndthe formula is as follows:
whereinFloor (. degree.) is rounded down, ceil (. degree.) is rounded up,c is the first row element coefficient of the R matrix for the quantization step;
step 135: the watermark is embedded in the first row of coefficients of the R matrix, as follows:
where C is the coefficient selected to embed the watermark,taking the absolute value of abs (.) for the modified coefficients;
step 136: by usingReplacing the first row element coefficient C of the R matrix, carrying out inverse QR decomposition to obtain sub-blocks containing watermarks, then reconstructing all the sub-blocks containing the watermarks back to obtain low-frequency sub-bands containing the watermarks, combining the low-frequency sub-band coefficients containing the watermarks with the high-frequency sub-band coefficients by utilizing non-subsampled inverse shear wave transformation to obtain two-dimensional form audio containing the watermarks, finally reducing the two-dimensional form audio into one-dimensional form audio, and reconstructing the one-dimensional form audio into the original audio data section to obtain digital audio containing the watermarks;
step 14: and repeating the step 2 to the step 3 to embed the synchronous codes and the watermark information into other audio data segments.
The shear wave domain audio watermark detection method based on robust QR decomposition corresponding to the embedding method is characterized by comprising the following steps
Step 21: searching a synchronous code by adopting a frame synchronous code bit-by-bit comparison mode in the communication field, and taking an audio data segment between two adjacent synchronous codes as a candidate audio data segment of the watermark to be extracted according to the detected synchronous code;
step 22: the extraction of the watermark signal is as follows:
step 221: mapping the obtained audio data segment containing the watermark into a two-dimensional form, performing non-subsampled shear wave transformation to obtain low-frequency sub-bands, partitioning the low-frequency sub-bands, and performing QR decomposition on each sub-block to obtain an upper triangular matrix；
Step 222: selectingFirst of the matrixOne line of elements is subjected to watermark extraction, and the formula is as follows:
whereinCeil (.) is rounding up,is a matrixThe coefficients of the first row of elements of (c),in order to quantize the step size,is a modulo arithmetic function;
step 23: repeating the steps 21 to 22, extracting the watermark of the audio watermark data section between each two adjacent synchronous codes, and solving the optimal watermark information by using a majority principle:
；
step 24: watermark decoding:
extracting optimal watermark information for allDemodulating BPSK modulation to obtain binary sequence：
；
To pairPerforming dimension increasing processing to obtain a watermark image matrixThen go right againInverse scrambling and decryption are carried out to obtain the extracted binary image watermark：
。
The waveform diagram of the original audio in the embodiment of the invention is shown in fig. 1, and the waveform diagram of the audio with the embedded watermark in the embodiment of the invention is shown in fig. 2, so that the difference between the audio with the embedded watermark in the embodiment of the invention and the original audio is very small, namely the invention has very good perception transparency.
The resistance of embodiments of the present invention to conventional signal processing is compared to prior art digital watermarks in table 1.
The resistance of the embodiment of the invention and the digital watermark in the prior art to desynchronization attack is shown in table 2.
TABLE 1 resistance of digital watermarks to conventional signal processing
TABLE 2 resistance of digital watermarks to desynchronization attacks
The results show that: the embodiment of the invention can resist conventional signal processing and effectively resist desynchronization attack, and has good robustness.
Claims (2)
1. A shear wave domain audio watermark embedding method based on robust QR decomposition is characterized by comprising the following steps:
step 11: watermark coding: two-value watermark imageScrambling and encrypting into a secure watermark matrixWherein
And then, performing dimension reduction treatment on the watermark image, namely converting the two-dimensional watermark image into a one-dimensional binary watermark sequence:
finally, according to the following formula, toBPSK modulation mapping is carried out to obtain a one-dimensional reversed phase sequence of { -1,1 { (R) }：
；
Step 12: according to the digital watermark and the size of the synchronous code, an original audio carrier is divided into A, B sections, and then the synchronous code is embedded by utilizing the statistical characteristics of the time domain audio samples, which is as follows:
step 121: the audio frequency sub-section A is according to the length of the synchronous codeIs divided intoSegments of eachComprisesAn audio sample, i.e.
；
Step 122: computingAverage value of (i), i.e.
；
Step 123: the synchronisation code is embedded by quantization, i.e. for each segmentModifying the mean value thereofBy embedding a one-bit synchronization codeThe modification strategy is:
wherein,in order to modify the pre-audio sample values,is a modified audio sample value and has
=,
Wherein,in order to perform the operation of taking the modulus,is a quantization step size;
step 13: embedding of watermark signal:
step 131: mapping the audio sub-segment B into a two-dimensional matrix form, and performing non-subsampled shear wave transformation to obtain a low-frequency sub-band;
step 132: partitioning the low-frequency sub-band according to the length of the watermark, and carrying out QR decomposition on each small block matrix to obtain an upper triangular matrix R;
step 133: selecting the first row of elements of the R matrix for watermark embedding and modifying the strengthAndis determined by the size of the watermark information bitThe decision, the formula is as follows:
whereinIs a quantization step size;
step 134: byAndcalculating a quantization resultAndthe formula is as follows:
whereinFloor (. degree.) is rounded down, ceil (. degree.) is rounded up,c is the first row element coefficient of the R matrix for the quantization step;
step 135: the watermark is embedded in the first row of coefficients of the R matrix, as follows:
whereinTaking the absolute value of abs (.) for the modified coefficients;
step 136: by usingReplacing the first row element coefficient C of the R matrix, carrying out inverse QR decomposition to obtain sub-blocks containing watermarks, then reconstructing all the sub-blocks containing the watermarks back to obtain low-frequency sub-bands containing the watermarks, combining the low-frequency sub-band coefficients containing the watermarks with the high-frequency sub-band coefficients by utilizing non-subsampled inverse shear wave transformation to obtain two-dimensional form audio containing the watermarks, finally reducing the two-dimensional form audio into one-dimensional form audio, and reconstructing the one-dimensional form audio into the original audio data section to obtain digital audio containing the watermarks;
step 14: and repeating the step 12 to the step 13 to embed the synchronous codes and the watermark information into other audio data segments.
2. A detection method corresponding to the method for embedding a shear-wave-domain audio watermark based on robust QR decomposition of claim 1, characterized by the following steps:
step 21: searching a synchronous code by adopting a frame synchronous code bit-by-bit comparison mode in the communication field, and taking an audio data segment between two adjacent synchronous codes as a candidate audio data segment of the watermark to be extracted according to the detected synchronous code;
step 22: the extraction of the watermark signal is as follows:
step 221: mapping the obtained audio data segment containing the watermark into a two-dimensional form, performing non-subsampled shear wave transformation to obtain low-frequency sub-bands, partitioning the low-frequency sub-bands, and performing QR decomposition on each sub-block to obtain an upper triangular matrix；
Step 222: selectingThe first row of elements of the matrix is subjected to watermark extraction, and the formula is as follows:
whereinCeil (.) is rounding up,is a matrixThe coefficients of the first row of elements of (c),in order to quantize the step size,is a modulo arithmetic function;
step 23: repeating the steps 21 to 22, extracting the watermark of the audio watermark data section between each two adjacent synchronous codes, and solving the optimal watermark information by using a majority principle:
；
step 24: watermark decoding:
extracting optimal watermark information for allDemodulating BPSK modulation to obtain binary sequence：
；
To pairPerforming dimension increasing processing to obtain a watermark image matrixThen go right againInverse scrambling and decryption are carried out to obtain the extracted binary image watermark：
。
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| CN106485641B (en) * | 2016-08-31 | 2019-10-01 | 南京师范大学 | A kind of tile data digital watermarking generation insertion and extracting method based on QR code |
| CN106847264A (en) * | 2017-01-19 | 2017-06-13 | 海尔优家智能科技（北京）有限公司 | The method and system that a kind of configuration equipment networks |
| CN108040190A (en) * | 2017-11-22 | 2018-05-15 | 明鉴方寸（北京）科技有限公司 | A kind of stealth watermark recognition methods, device and storage device |
| CN108062957B (en) * | 2017-12-18 | 2021-06-15 | 辽宁师范大学 | Strong robust digital watermark detection method based on steady local features |
| CN109102454B (en) * | 2018-08-13 | 2023-08-01 | 鲁东大学 | Color QR code digital blind watermarking method integrating fast Fourier transform |
| CN109493875B (en) * | 2018-10-12 | 2023-07-07 | 平安科技（深圳）有限公司 | Audio watermark adding and extracting method and terminal equipment |
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| CN103208288A (en) * | 2013-03-13 | 2013-07-17 | 漳州职业技术学院 | Dual encryption based discrete wavelet transform-discrete cosine transform (DWT-DCT) domain audio public watermarking algorithm |
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| CN101038771A (en) * | 2006-03-18 | 2007-09-19 | 辽宁师范大学 | Novel method of digital watermarking for protecting literary property of music works |
| CN103208288A (en) * | 2013-03-13 | 2013-07-17 | 漳州职业技术学院 | Dual encryption based discrete wavelet transform-discrete cosine transform (DWT-DCT) domain audio public watermarking algorithm |
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