EP3001415A1 - Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist - Google Patents

Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist Download PDF

Info

Publication number
EP3001415A1
EP3001415A1 EP14306464.0A EP14306464A EP3001415A1 EP 3001415 A1 EP3001415 A1 EP 3001415A1 EP 14306464 A EP14306464 A EP 14306464A EP 3001415 A1 EP3001415 A1 EP 3001415A1
Authority
EP
European Patent Office
Prior art keywords
values
value
audio signal
candidate
watermark
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP14306464.0A
Other languages
English (en)
French (fr)
Inventor
Michael Arnold
Peter Georg Baum
Xiaoming Chen
Ulrich Gries
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Thomson Licensing SAS
Original Assignee
Thomson Licensing SAS
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Thomson Licensing SAS filed Critical Thomson Licensing SAS
Priority to EP14306464.0A priority Critical patent/EP3001415A1/de
Priority to PCT/EP2015/070685 priority patent/WO2016045977A1/en
Publication of EP3001415A1 publication Critical patent/EP3001415A1/de
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/018—Audio watermarking, i.e. embedding inaudible data in the audio signal

Definitions

  • the invention relates to a method and to an apparatus for determining from sets of correlation result values whether a specific watermark symbol out of one or more candidate watermark symbols is embedded in a current section of a received audio signal, or whether no watermark symbol is embedded in the current section of the received audio signal.
  • a watermark detector In a watermark detector cross correlations between a received signal and reference patterns are evaluated. Basically, the maximal correlation result value is compared to a threshold in order to determine whether watermark information has been embedded in the received signal. For acoustic path transmission, multiple correlation result peaks are employed for detection, in order to take a multi-path environment into account. Again, an appropriately defined metric aggregating multiple correlation result peaks is compared to a threshold for watermark detection.
  • a false positive probability defines the probability that a watermark is detected for unmarked content and is denoted as P fp , which is naturally dependent on the applied watermark detection processing.
  • a problem to be solved by the invention is to provide an improved watermark information detection. This problem is solved by the method disclosed in claim 1. An apparatus that utilises this method is disclosed in claim 2. Advantageous additional embodiments of the invention are disclosed in the respective dependent claims.
  • order statistics are used for watermark symbol detection from the correlation result values, where the joint probability distribution function (pdf) for one or more peaks of cross correlation values between a current section of the received audio signal and reference patterns is employed directly for watermark detection.
  • PDF joint probability distribution function
  • Monte Carlo or quasi-Monte Carlo simulations are used for evaluating the false positive probability corresponding to a pdf value threshold.
  • a pdf threshold look-up table (LUT) and an associated false positive probability look-up table can be constructed, which both are used for the watermark symbol detection. Using such LUTs significantly simplifies the complexity of watermark detection when taking more correlation result peaks for detection into account. Because the derived false positive probability has intuitive interpretation, it can be used for the design of watermarking systems employing correlation for watermark detection.
  • the inventive method is adapted for determining from sets of correlation result values whether a specific watermark symbol out of one or more candidate watermark symbols is embedded in a current section of a received audio signal, or whether no one of said candidate watermark symbols is embedded in said current section of said received audio signal, wherein said current section of said received audio signal was correlated with at least one candidate reference pattern, each one of which representing one of said one or more candidate watermark symbols, said method including:
  • the inventive apparatus is adapted for determining from sets of correlation result values whether a specific watermark symbol out of one or more candidate watermark symbols is embedded in a current section of a received audio signal, or whether no one of said candidate watermark symbols is embedded in said current section of said received audio signal, wherein said current section of said received audio signal was correlated with at least one candidate reference pattern, each one of which representing one of said one or more candidate watermark symbols, said apparatus including means configured to:
  • a watermark detector In a watermark detector, cross correlations between a received signal and reference patterns are evaluated. Usually, the maximal correlation result value is compared to a threshold in order to determine whether a watermark is embedded in the received signal.
  • multiple correlation result value peaks are employed for watermark detection, in order to take a resulting multi-path environment due to echoes and reverberation into account.
  • An appropriately defined metric aggregating multiple correlation result value peaks is compared to a threshold for watermark detection.
  • a false positive probability defines the probability that a watermark is detected for unmarked content and is denoted as P fp . It is naturally dependent on the applied detection method.
  • the smallest P fp among all watermark symbols is compared to a threshold in order to decide whether watermark information is present in the received signal. If the smallest P fp is smaller than the threshold, a watermark is assumed to be present. The symbol associated with the smallest P fp is taken as the embedded watermark symbol. Otherwise, if the smallest P fp is higher than the threshold, it is declared that no watermark data is present.
  • P fp is defined as the probability that n p or more correlation result values for a random correlation array subject to Gaussian distribution are larger than or equal to the actual n p peaks under consideration.
  • detection is based on comparison of multiple peaks.
  • the number of disjoint complementary cases exponentially increases with increased n p , which limits its application, especially for environments with severe reflections and/or reverberations. Another issue is associated with the interpretation of the defined P fp .
  • watermark detection is carried out by comparing evaluated P fp values. Given a P fp threshold, it is not straightforward to determine the probability of evaluated P fp values for unmarked content watermark being smaller than the given P fp threshold. For single peak cases, the probability of evaluated P fp values for unmarked content watermark being smaller than the given P fp threshold is equal to the given P fp threshold. However, for n p > 1 that is not the case, as illustrated in Fig.
  • P fp values delivered from the detector described in WO 2011/141292 A1 and PCT/EP2014/066063 are compared to P fp thresholds shown on the x-axis.
  • the probability for P fp values being lower than a threshold is estimated by dividing the number of P fp values lower than the threshold by the total number of delivered P fp values.
  • the probability of evaluated P fp values for unmarked content watermark being smaller than the given P fp threshold is higher than the given P fp threshold for n p > 1. With increased n p the deviation between both becomes larger.
  • order statistics are used for watermark detection.
  • two look-up tables are employed for P fp function evaluation.
  • order statistics as decision metric provides a nice interpretation of evaluated P fp function values, namely, the probability of evaluated P fp function values for unmarked content watermark being smaller than the given P fp threshold is exactly equal to the given P fp threshold for any n p value.
  • the probability distribution function denoted pdf of peaks resulting from unmarked content can be employed for watermark detection.
  • the decision criterion is to minimise the likelihood pdf. That is, the higher the pdf value for multiple peaks, the more likely it is that these peaks are generated from unmarked content. Conversely, the lower the pdf value, the more likely it is that these peaks are generated from marked content.
  • the constraint v 0 ⁇ v 1 ⁇ ⁇ ⁇ v n p -1 is referred to as peak constraint.
  • watermark detection can be carried out by comparing the pdf values of normalised peak vectors in correlation arrays corresponding to different watermark symbols, and the symbol resulting in the smallest pdf value is selected as embedded watermark symbol.
  • a threshold should be used to avoid a high false positive probability, or in other words, the resulting P fp using that threshold should be below the target P fp . That is, only when the smallest pdf value g ( w ) is sufficiently low, it is decided that a watermark is present in the received signal. Otherwise, if the threshold is not low enough, for unmarked content, a watermark will be detected with a high probability. Consequently, the corresponding P fp becomes high. Therefore it is necessary to evaluate P fp for a specific threshold for pdf values g ( w ).
  • the pdf values g ( w ) for different watermark symbols are compared to a threshold in order to decide whether or not a watermark is present. If g ( w ) is smaller than the threshold, it is decided that a watermark is present. And the watermark symbol resulting in the smallest pdf value is taken as the embedded one. If none of evaluated pdf values is smaller than the threshold, it is assumed that no watermark information data is present.
  • g ( z ) is interpreted as a threshold for determining the presence of watermark.
  • M a larger number of length- L correlation arrays, say M , can be generated according to the Gaussian distribution. Normalised peak vectors of these correlation arrays are denoted as ⁇ w ( i ) , 1 ⁇ i ⁇ M ⁇ and are used for evaluating g ( w ( i ) ).
  • the pdf values for extremely small or extremely large peak values are extremely small.
  • P fp is represented by the area below the distribution function where pdf values are smaller than the threshold. Therefore, the evaluation of P fp can be interpreted as one-dimensional integration for the single-peak case. For multi-peaks, it is a multi-dimensional integration.
  • Fig. 2 indicates that an increase of the threshold th also increases P fp .
  • a look-up table with K entries for pdf thresholds is defined, for example, linearly on the log-scale in the range [ ⁇ g max , ⁇ g max ], ⁇ ⁇ 1, ⁇ ⁇ 1, where g max denotes the maximal pdf value for all possible normalised peak vectors.
  • the false positive probability is determined numerically.
  • the evaluation of the false positive probability can be interpreted as multi-dimensional integration.
  • the convergence of Monte Carlo or quasi-Monte Carlo simulations is independent of dimension, while linear-grid based methods do depend on dimension and therefore do not converge well with increased dimension. Therefore the Monte Carlo simulation is used for the numerical evaluation of the false positive probability, whereby the Monte Carlo simulation is carried out according to the Monte Carlo method.
  • LUTs lookup tables
  • One LUT stores values of probability distribution function (pdf) for normalised peaks of correlation between non-watermarked content and reference patterns, and the other one stores values of false positive probability corresponding to entries in the pdf LUT. That is, each entry in the pdf LUT corresponds to a unique entry in the LUT for false positive probability. Different correlation lengths and different number of peaks result in different LUTs.
  • determined LUTs are stored in the memory unit of watermark detector, which is accessed during watermark detection. As mentioned above, for watermark detection, the detector performs correlation between received audio section and reference patterns corresponding to watermark symbols. Correlation values are sorted to find peaks, which are normalised by standard deviation.
  • the standard deviation is estimated either individually for each set of correlation result values corresponding to individual candidate watermark symbol, or by averaging over sets of correlation result values. Afterwards, the probability distribution function is evaluated for the normalised peaks. And the LUT for probability distribution is accessed to find the entry index which is nearest to the evaluated pdf value from the normalised peaks. This entry index is then used to access the second LUT for the false positive probability. And the false positive probability corresponding to the peaks found is then evaluated by means of interpolation or extrapolation.
  • n p -dimensional hypercube l w min w max n p is used for Monte Carlo simulation.
  • all volume outside the hypercube is ignored for the P fp evaluation.
  • the inventors have found that, by a careful choice of w min ,w max , the influence on the evaluated P fp values is negligible for relevant P fp values in practical applications.
  • Fig. 3 depicts the determination of w min , w max for the single-peak case.
  • the false positive probability can be reformulated as (see the definition in equation (2)):
  • a g ⁇ w d w were denotes the hyper-region subject to the peak constraint w 0 ⁇ w 1 ⁇ ... ⁇ w n p -1 and with pdf values g ( w ) less than the threshold th.
  • g '( w ) g ( w ) for w ⁇
  • g '( w ) 0 for w ⁇ and w ⁇
  • 1 A can be interpreted as the distribution function for an n p -dimensional random vector w uniformly distributed in the hypercube .
  • equation (3) is the expectation of g '( w ) with respect to a uniformly distributed random vector w :
  • the pdf value g ( w ) is evaluated and compared to the pdf threshold th. If g ( w ) ⁇ th, g ( w ) values are accumulated. The final result of accumulation is scaled by A M , which delivers an estimated false positive probability. Consequently, for each entry in the pdf threshold LUT, the corresponding false positive probability is determined numerically according to equation (4).
  • Fig. 4 shows a flow diagram for the generation of the pdf threshold LUT and P fp LUT, which are used for the watermark detection.
  • step 41 the aim is stated to construct a pdf threshold LUT with K entries, given a pdf range [ p min , p max ].
  • Normalised peak vectors are generated in step 43: Generate M times normalised peak vectors using Monte Carlo or quasi-Monte Carlo processing.
  • Monte Carlo a random generator is used to generate normalised peak vectors uniformly distributed in the hyper-cube [ w min , w max ] n p , where [ w min , w max ] defines the range of generated random normalised peak values.
  • a low-discrepancy sequence like Sobol sequence is generated as normalised peak values, which also approximate the uniform distribution.
  • each generated normalised peak vector is sorted such that the peak constraint is fulfilled: w 0 ⁇ w 1 ⁇ ⁇ ⁇ w n p -1 , which is used to calculate pdf value g ( w ( m ) ) in step 45.
  • the calculated values g ( w ( m ) ) are compared with threshold entries th i in the pdf threshold LUT.
  • step 47 all P fp,i entries in the P fp LUT having a corresponding pdf threshold greater than g ( w ( m ) ) are increased by g ( w ( m ) ).
  • i is incremented and, as long as i ⁇ K in step 48, the i loop continues with step 46.
  • m is incremented and, as long as m ⁇ M in step 49, the m loop continues with step 43.
  • the final P fp values are estimated in step 40 by scaling the P fp LUT entries by w max - w min n p n p ! M .
  • FIG. 5 A first flow diagram for watermark detection is shown in Fig. 5 . There are nSymbols watermark symbols in the watermark symbol alphabet. Watermark detection is carried out as follows:
  • FIG. 7 A second flow diagram for watermark detection is shown in Fig. 7 . There are nSymbols watermark symbols in the watermark symbol alphabet. Watermark detection is carried out as follows:
  • step 77 the minimal P f p * value for all candidate watermark symbols is then compared to a second threshold T max > T min . If the minimal P f p * value is smaller than T max , the symbol resulting in the minimal P f p * value is determined to be the embedded one and is output in step 79. If the minimal P f p * value is not smaller than T max , it is decided in step 78 that no watermark is present in the received current signal section.
  • a received watermarked signal is re-sampled in an acquisition or receiving section step or stage 61, and thereafter may pass through a spectral shaping and/or whitening step or stage 62.
  • correlation step or stage 63 it is correlated section by section with the nSymbols reference patterns.
  • a symbol detection or decision step or stage 64 determines, whether or not a corresponding watermark symbol is present in the current signal section.
  • a secret key was used to generate pseudo-random phases, from which related reference pattern bit sequences or symbols were generated and used for watermarking the audio signal.
  • these pseudo-random phases are generated in the same way in a corresponding step or stage 65, based on the same secret key.
  • related candidate reference patterns or symbols are generated in a reference pattern generation step or stage 66 and are used in step/stage 63 for checking whether or not a related watermark symbol is present in the current signal section of the received audio signal.
  • a look-up table 67 for probability distribution function values and a look-up table 68 for false positive probabilities are used for the embedded watermark symbol determination as described above.
  • the described processing can be carried out by a single processor or electronic circuit, or by several processors or electronic circuits operating in parallel and/or operating on different parts of the complete processing.
  • the instructions for operating the processor or the processors according to the described processing can be stored in one or more memories.
  • the at least one processor is configured to carry out these instructions.
EP14306464.0A 2014-09-23 2014-09-23 Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist Withdrawn EP3001415A1 (de)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP14306464.0A EP3001415A1 (de) 2014-09-23 2014-09-23 Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist
PCT/EP2015/070685 WO2016045977A1 (en) 2014-09-23 2015-09-10 Method and apparatus for determining whether a specific watermark symbol out of one or more candidate watermark symbols is embedded in a current section of a received audio signal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP14306464.0A EP3001415A1 (de) 2014-09-23 2014-09-23 Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist

Publications (1)

Publication Number Publication Date
EP3001415A1 true EP3001415A1 (de) 2016-03-30

Family

ID=51726461

Family Applications (1)

Application Number Title Priority Date Filing Date
EP14306464.0A Withdrawn EP3001415A1 (de) 2014-09-23 2014-09-23 Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist

Country Status (2)

Country Link
EP (1) EP3001415A1 (de)
WO (1) WO2016045977A1 (de)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109299313A (zh) * 2018-08-03 2019-02-01 昆明理工大学 一种基于FP-growth的歌曲推荐方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2175443A1 (de) * 2008-10-10 2010-04-14 Thomson Licensing Verfahren und Vorrichtung zur Wiedererlangung von Wasserzeichendaten, die in einem ursprünglichen Signal eingebettet waren, durch Änderung von Abschnitten des genannten ursprünglichen Signals in Zusammenhang mit mindestens zwei verschiedenen Referenzdatensequenzen
EP2387033A1 (de) * 2010-05-11 2011-11-16 Thomson Licensing Verfahren und Vorrichtung zur Erkennung, welche Wasserzeichendatensymbole in einem empfangenen Signal eingebettet sind

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2175443A1 (de) * 2008-10-10 2010-04-14 Thomson Licensing Verfahren und Vorrichtung zur Wiedererlangung von Wasserzeichendaten, die in einem ursprünglichen Signal eingebettet waren, durch Änderung von Abschnitten des genannten ursprünglichen Signals in Zusammenhang mit mindestens zwei verschiedenen Referenzdatensequenzen
EP2387033A1 (de) * 2010-05-11 2011-11-16 Thomson Licensing Verfahren und Vorrichtung zur Erkennung, welche Wasserzeichendatensymbole in einem empfangenen Signal eingebettet sind
WO2011141292A1 (en) 2010-05-11 2011-11-17 Thomson Licensing Method and apparatus for detecting which one of symbols of watermark data is embedded in a received signal

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
H.A. DAVID; H.N. NAGARAJA: "Order statistics", 2003, JOHN WILEY & SONS
M. ARNOLD; X.M. CHEN; P. BAUM; U. GRIES; G. DOERR: "A phase-based audio watermarking system robust to acoustic path propagation", IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, vol. 9, no. 3, March 2014 (2014-03-01), pages 411 - 425, XP011538857, DOI: doi:10.1109/TIFS.2013.2293952
MICHAEL ARNOLD ET AL: "Robust detection of audio watermarks after acoustic path transmission", PROCEEDINGS OF THE 12TH ACM WORKSHOP ON MULTIMEDIA AND SECURITY, MM&SEC '10, 1 January 2010 (2010-01-01), New York, New York, USA, pages 117, XP055071121, ISBN: 978-1-45-030286-9, DOI: 10.1145/1854229.1854253 *
R.E. CAFLISCH: "Monte Carlo and quasi-Monte Carlo methods", ACTA NUMERICA, vol. 7, January 1998 (1998-01-01), pages 1 - 49

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109299313A (zh) * 2018-08-03 2019-02-01 昆明理工大学 一种基于FP-growth的歌曲推荐方法

Also Published As

Publication number Publication date
WO2016045977A1 (en) 2016-03-31

Similar Documents

Publication Publication Date Title
Ker Batch steganography and pooled steganalysis
US10296999B2 (en) Methods and apparatus for color image watermarking
Ker A capacity result for batch steganography
CN109102452B (zh) 一种基于拉丁方阵置乱和双向扩散的图像加密方法
Lerch-Hostalot et al. LSB matching steganalysis based on patterns of pixel differences and random embedding
Ahani et al. Colour image steganography method based on sparse representation
US8381290B2 (en) Intrusion detection systems and methods
Hanley et al. Unknown plaintext template attacks
Megalingam et al. A Comparative Study on Performance of Novel, Robust Spatial Domain Digital Image Watermarking with DCT Based Watermarking
EP3001415A1 (de) Verfahren und Vorrichtung zur Bestimmung, ob ein bestimmtes Wasserzeichensymbol aus einem oder mehreren Kandidatenwasserzeichensymbolen in einem gegenwärtigen Abschnitt eines empfangenen Audiosignals eingebettet ist
El-Sagheer et al. Assessing the lifetime performance index with digital inferences of power hazard function distribution using progressive type-II censoring scheme
Aittokallio et al. Improving the false nearest neighbors method with graphical analysis
Swaminathan et al. Security of feature extraction in image hashing
EP3674884A1 (de) Vorrichtung und verfahren zum testen einer von einem zufallszahlengenerator erzeugten sequenz
Bhattacharyya et al. Study and analysis of quality of service in different image based steganography using Pixel Mapping Method (PMM)
Chandramouli Data hiding capacity in the presence of an imperfectly known channel
Chen et al. Normalized Differential Power Analysis-for Ghost Peaks Mitigation
KR101737045B1 (ko) 유사중복 이미지 검출 장치 및 방법
Chhikara Performance evaluation of first and second order features for steganalysis
Xu Orderly random testing for both hardware and software
JPWO2007040111A1 (ja) 電子透かし検出装置
Zhang et al. Template Attack Assisted Linear Cryptanalysis on Outer Rounds Protected DES Implementations
El Choubassi et al. On the fundamental tradeoff between watermark detection performance and robustness against sensitivity analysis attacks
Sharifzadeh et al. Statistical and information-theoretic optimization and performance bounds of video steganography
US10277392B2 (en) Cracking devices and methods thereof

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN

18D Application deemed to be withdrawn

Effective date: 20161001