MXPA06009113A - Watermark detection - Google Patents

Abstract

An information signal includes a plurality of watermarks (Wi) which together define a payload of data, such as a rights information. A detector (100) detects the presence (60-62) of each of the plurality of watermarks in the information signal and provides an output (101-103) which can be used to determine (70, 75) the payload represented by the watermarks. A measure of confidence in the accuracy of the payload represented by the watermarks is calculated (110) using information (104-106) from the detection stages (60-62). This provides a measure of the quality of the payload to any equipment which relies on the payload results, such as a Digital Rights Management (DRM) system. Information about the shape of correlation peaks obtained in the detection stages (60-62) can be used to derive the measure of confidence in the accuracy of the payload.

Description

DETECTION OF WATER MARKS Description of the invention This invention relates to the detection of a watermark in an information signal. Watermarking is a technique in which a label of a certain type is added to an information signal. The information signal to which the watermark is added may represent a data file, a still image, video, audio or any other type of media content. The tag is inserted into the information signal before the information signal is distributed. The tag is usually added in a way that is imperceptible under normal conditions, so that it does not degrade the information signal, for example, a watermark added to an audio file should not be audible under normal listening conditions. However, the watermark must be robust enough to remain detectable even after the information signal has undergone normal processes during transmission, such as coding or compression, modulation and so on. A simple watermarking scheme can incorporate a single watermark in a content article, with a detection scheme that verifies the presence of the individual watermark. In this case, REP .: 173751 watermark transports only a bit of information: its presence, or its absence. In a development of watermarking technology, it is known to insert several watermarks into an information signal, the combination of watermarks being used to represent a code, known as a payload. The payload may represent, for example, a code such as "copy", "do not copy" or a content identity number. A scheme of this type is described in the document "A Video atermaking System for Broadcast Monitoring", Ton Kalker et al. , Proceedings of the SPIE, Bellingham, Virginia vol. 3657, January 25, 1999, p. 103- 112. In this scheme the payload is coded by inserting several (for example, four) basic watermark patterns with spatial shifts in relation to one another. The signal under test is individually correlated with each of the basic watermark patterns to produce a volatile memory of correlation results. The presence of each watermark is indicated by a peak in the correlation results. A watermark is declared present if the four basic watermark patterns produce a correlation peak with a height greater than a threshold value of 5s (five times the standard deviation of the set of correlation results in the volatile result memory) . This threshold value is selected to achieve an acceptably low probability of content without watermarks that is misreported with watermarks (a 'false positive'). If a watermark is found then the payload is decoded by examining the shifts between the basic patterns. It is typically assumed that if the watermark can be detected reliably, then the payload can also be reliably extracted. However, in practice it is possible that the presence of a watermark is detected while the extracted payload is in error. In many applications the content with watermarks will undergo several processing operations between the point at which a watermark is inserted into the content and the point at which the presence of the watermark is detected. A common example of content processing is lossy compression, such as MPEG encoding. Typically, the effects of processing are to reduce the correlation peaks that would normally be expected to occur during the watermark detection process. In this way, the performance of a watermark detection technique based on finding correlation peaks is considerably reduced when trying to detect watermarks in content that has undergone these processes. The present invention seeks to provide an improved way to extract the payload carried by a watermark in an information signal. In consecuense, a first aspect of the present invention provides a method for processing an information signal in which a plurality of watermarks are present, the plurality of watermarks -defined together a payload, the method comprises: detecting the presence of each of the plurality of watermarks in the information signal; Determine the payload represented by the watermarks and calculate a confidence measure in the accuracy of the payload represented by the watermarks. This has the advantage of providing a measure of the quality of the payload to any equipment that is based on payload results (such as a Digital Rights Management (DRM) system). This can prevent, for example, incorrect rights from being assumed in content management / copy protection applications. Moreover, it can make it possible for new actions to be taken; A single response can be defined for cases where a watermark is found (possibly indicating protected audio / video content) but no payload can be extracted (so that exact rights can not be determined). In a preferred embodiment, the information signal is correlated with each expected watermark pattern to derive sets of correlation results. The information about the shape of the correlation peak can be used to derive the confidence measure in the accuracy of the payload. The functionality described here can be implemented in software, hardware or a combination thereof. Accordingly, another aspect of the invention provides software to carry out the method. It will be appreciated that the software can be installed on the host apparatus at any point during the life of the equipment. The software can be stored in an electronic memory device, hard disk, optical disk or other machine-readable storage medium. The software can be supplied as a computer program product in a machine-readable carrier or can be downloaded directly to the device via a network connection. Additional aspects of the invention provide an arrangement for processing an information signal that carries out any of the method steps and an apparatus for presenting an information signal that responds to the output of the arrangement. Although the described modality refers to the processing of an image or video signal (including digital cinema content), it will be appreciated that the information signal may be data representing audio or any other type of media content. The embodiments of the present invention will now be described, by way of example only, with reference to the following figures in which: Figure 1 shows a known way of inserting a watermark in a content article. Figure 2 shows an arrangement for detecting the presence of a watermark in a content article. Figures 3 and 4 show tables of correlation results to be used in the detector and method. "Figure 5 shows an exemplary set of correlation result data in graphical form, and Figure 6 shows an apparatus for presenting content incorporating the watermark detector. As an antecedent, and to understand the invention, it will be briefly described. a process for inserting a watermark, with reference to figure 1. A watermark pattern w (K) is constructed using one or more basic watermark patterns w.When a data payload is to be carried by the watermark, a number of basic watermark patterns are used.The watermark pattern w (K) is selected according to the payload - a K-code of several bits - to be inserted. The code is represented by selecting a number of the basic patterns w and by decentering them from each other by a particular distance and direction.The combined watermark pattern w (K) represents a noise pattern that can be added to the content. Watermark w (K) has a size of M x M bits and is typically much smaller than the content article. Consequently, the pattern M x M is repeated (grid) 14 in a larger pattern that matches the format of the content data. In the case of an image, the pattern w (K) is squared 14 in such a way that it equals the size of the image with which it will be combined. A content signal is received and stored in a volatile memory 16. A measure of local activity? (X) in the content signal is derived at each pixel position. This provides a measure for additive noise visibility and is used to scale the watermark pattern w (K). This prevents the watermark from being noticeable in the content, such as areas of equal brightness in an image. A general scaling factor s applies to the watermark in the multiplier 22 and this determines the overall resistance of the watermark. The choice of s is a compromise between the degree of robustness that is required and the requirement of how perceptible the watermark should be. Finally, the watermark signal (K) is added 24 to the content signal. The resulting signal, with the watermark inserted in it, will then be subjected to several processing steps as part of the normal distribution of that content. Figure 2 shows a schematic diagram of a watermark detector 100. The watermark detector receives content that may have watermarks. In the following description it is assumed that the content is content of images or video. The detection of watermarks can be carried out for individual tables or for groups of tables. The accumulated frames are divided into blocks of size -M x M (for example, M = 128) and then folded into a volatile memory of size M x M. These initial stages are shown as block 50. The data in the memory The volatile memory is then subjected to a Fast Fourier Transformation 52. The next step in the detection process determines the presence of watermarks in the data contained in the volatile memory 64. To detect whether the volatile memory includes a mark pattern or not. of water W, the contents of the volatile memory and the expected watermark pattern are correlated. Since the content data may include various watermark patterns, a number of parallel branches 60, 61, 62 are shown each performing the correlation with one of the basic watermark patterns W0, W1, W2. One of the branches is shown in more detail. The correlation values for all possible displacement vectors of a basic Wi-pattern are calculated simultaneously. The basic watermark pattern Wi (i = 0, 1, 2) undergoes a Fast Fourier Transformation (FFT) before its correlation with the data signal. The set of correlation values is then subjected to a Fast Fourier Transformation 63. Complete details of the correlation operation are described in US 6,505,223 Bl. . The Fourier coefficients used in the correlation are complex numbers, with a real part and an imaginary part, which represent a magnitude and a phase. It has been found that the reliability of the detector is significantly improved if the magnitude information is discarded and only the phase is considered. A magnitude normalization operation can be carried out after the multiplication by points and before the inverse Fourier Transformation 63. The operation of the normalization circuit comprises dividing by points, each coefficient between its magnitude. The global detection technique is known as Equalized Filtering Only Symmetric Phases (SPOMF). The set of correlation results from the previous processing is stored in a volatile memory 64. A small exemplary set of correlation results is shown in Figure 3. The content with watermarks is indicated by the presence of peaks in the data of correlation results. The set of correlation results is examined to identify peaks that could be due to the presence of a watermark in the content data. Low ideal conditions the presence of a watermark will be indicated by a pronounced and isolated peak of significant height, but earlier processing operations during the distribution of the content are more likely to cause a correlation peak to be smeared or marked over several adjacent positions in the correlation results. An initial processing step 65 identifies candidate groups of correlation results data which may represent correlation peaks. A technique for identifying candidate peaks is described in more detail below. Once the candidate peaks have been identified, an additional processing step 85 decides which is more likely to be due to a watermark. Once a valid peak has been identified in one or more correlation data sets, a vector recovery step 70 equals the different data sets to find a vector among the watermark patterns, that is, to identify the distance and direction in which the different patterns wO, wl, w2 are off center from each other. In a final step 75, the vectors identified in the previous step 70 are converted into a K code, which represents the payload of the watermark.

The detection stage peaks 85 of each branch 60, 61, 62. sends a respective signal 101, 102, 103 which represents whether a watermark pattern has been found in that branch. In addition, the information 104, 105, 106 from each branch 60, 61, 62 is applied to a payload trust calculation unit 110. The confidence calculation unit 110 carries out a calculation to determine a measure of what So reliable is the payload K extracted. The confidence measure is applied to a comparator 112, which compares the confidence measure with a threshold value 111 representing an acceptable confidence level. The threshold value 111 can be set to any desired value, depending on the application. A final stage 115 receives the watermark detection signals and provides an output 225 which depends on the watermark detection signals 101, 102, 103 and the confidence value 113. There are three possible outcomes: (a) that no watermark is found (one or more of the watermark detection signals 101, 102, 103 indicate that no watermarks are present); (b) a watermark is found and the payload is removed (all watermark detection signals 101, 102, 103 indicate that a watermark was found and the confidence value 113 is high); (c) a watermark is found, but the payload can not be easily determined (all watermark detection signals 101, 102, 103 indicate that a watermark was found and the confidence value 113 is low ). The output 225 can be used by a digital rights management system to provide adequate action. For example, when the payload indicates copying restrictions (for example, "copy", "copy only once", "copy freely") and output 225 indicate condition (c) above, the digital rights management system You can allow the content to be presented but not allow the content to be copied. There are several ways in which the detector 100 can operate. In a very simple form, the correlation results in the volatile memory 64 are compared to a threshold value to identify a significant peak. Typically the threshold is set to a value of 5s (five times the standard deviation of the set of correlation results in the volatile result memory). In a more elaborate scheme, correlation peaks that are 'stained' can be detected by setting a lower threshold and identifying groups of significant value correlation results. When there are several peaks, these are evaluated to identify the peak that most likely represents the actual peak. A technique to accomplish this is described below.

In a further elaboration, the shape of the correlation peak can be compared with information stored about an expected way, such as by cross-correlation. A good match in the form can indicate the presence of a correlation peak, even if it has been significantly stained. Different processes that a signal-; of content suffers during its distribution may have each one a characteristic effect, and in this way or recognizable, in the form of peak correlation. The peak size can be better understood by viewing the correlation results in the form of a graph, with the correlation value being plotted as height on a base line of the graph, as shown in Figure 5. Information about the shape of the peak is supplied 104, 105, 106 to the confidence calculation unit 110. From this, it will be understood that it is possible to detect the presence of watermarks even when the correlation results are less than ideal. However, the spotting of a correlation peak introduces some uncertainty in the calculation of the payload. Taking the example of a scheme where the relative position of correlation peaks determines the payload, a spotted or flattened beak introduces ambiguity in the actual position of a beak. The payload confidence calculation unit 110 bases the confidence value on peak form information obtained from unit 85. Referring again to FIGS. 3 and 3, these show two sets of correlation result data of the type would be stored in the volatile memory 64. Figure 3 shows the type of data that could be collected when a pronounced and well-defined correlation peak 160 occurred. Table 1 shows the probability of error values for the results data of Figure 3. The odds of payload error are given by equation 8 (see Appendix) for various assumed peak sizes, all centered on the highest point in the volatile memory. The values of C represent the number of result values that are included in the group of correlation peaks. Three groups of different sizes are considered: C = 1 is only a single point; C = 9 is a 3x3 square centered on the correlation peak, and C = 25 is a 5x5 square centered on the correlation peak. For reasons of simplicity, it is assumed that all possible payload displacements are equally likely.

Table 1: Pr (error) for Figure 3 In contrast, Figure 4 shows correlation results data for a lower and widely stained (flattened) correlation peak, and Table 2 shows the probability of values of 'error for these dates.

Table 2: Pr (error) for Figure 4 It is clear that the peak shape in the volatile memory of Figure 3 leads to a much higher confidence in the accuracy of the load. useful extracted (Table 1) compared to the flattened peak of Figure 4 (Table 2). In these examples the group of correlation results that are taken to form the peak are a grid grid of results centered on the correlation result that has the highest value. For example, when looking at figure 4, this could be the result square around result 130 with the value 4.9190. When a more efficient technique is used to identify groups (such as the one described below), the group identified by that detection technique can be used. Results groups do not have to be square, as in the previous examples. Referring again to Figure 2, the output 113 from the comparator 112 may be applied to the payload calculation unit 75, as shown by line 116.

If the confidence value of the payload is less than the confidence value threshold 111, then the payload calculation unit 75 can be instructed not to calculate the payload K. Thus, in situations where it is likely that the payload is incorrect, it is not sent at all. A process for identifying candidate correlation peaks in correlation results will now be described for use in unit 65 of FIG. 2. The grouping algorithm forms a number of groups of points, some of which. which may correspond to the peak of real correlation. The probabilities of these groups are compared, and the group with the lowest probability is assumed to be the desired correlation peak. The algorithm comprises the following steps: 1. Establish a threshold value and find all the points in the correlation data that are above this threshold value. All points that meet these criteria are stored in a list -ptsAboveThresh. A suggested threshold value is 3.3s (s = standard deviation of results in volatile memory) although this can be set to any preferred value. A preferred scale is 2.5 - 4s. If the threshold value is set too low under a large number of points, which do not correspond to the presence of a watermark, it will be stored in the list. Conversely, if the value is set too high, there is a risk that the points corresponding to a valid but spotted peak will not be added to the list. 2. Find the point with the highest absolute value. 3. Form candidate groups, that is, groups of correlation points. Candidate groups are formed by collecting points that not only have a 'significant' value (a value greater than the threshold), but also are located very close to at least some other point of significant value. This is accomplished as follows: (i) The first point of the ptsAboveThresh list is removed and entered as the first p point of a new group; (ii) Points in ptsAboveThresh that are within a distance d from point p are searched. All those points are removed from the ptsAboveThresh list and added to the group; (iii) The next point in the group is taken as the current p point. Step (ii) is repeated to add to the group all points in ptsAboveThresh that are within the distance d of the new point p. (iv) Stage (iii) is repeated until ptsAboveThresh has been processed for all points in the group; (v) If the resulting group consists of only a single point and that point is not equal to the highest peak found in stage 2 above, then this group is discarded; (vi) Steps (i) to (v) are repeated until ptsAboveThresh is empty. At the end of this procedure, all points originally entered in ptsAboveThresh in stage 1 above have been either: - assigned to a group that contains other points in the ptsAboveThresh list that are close to it, or - discarded, since they do not have neighbors of similar height, and therefore they are not part of a group. A group is only allowed to understand a single point if that point has the greatest absolute height of all points in the volatile correlation memory. This prevents a pronounced and non-stained correlation peak from being discarded, but prevents other isolated peaks, representing real noise, from being used. Referring again to Figures 3 and 4, these show some exemplary sets of correlation data of the type that could be calculated by the detector. In the data set shown in Figure 4 the values vary between -3.8172 and 4.9190. Watermarks with negative value can be inserted, and consequently the negative values are also significant. The highest value of 4.9190 is shown within the box 130. Although this is below the typical detection threshold of 5, the highest value is surrounded by other correlation values of a similar value. This is indicative of a spike that has been spotted by processing during the distribution chain. Following the procedure described above, and establishing a threshold T of 3.3 and a distance of 1, it can be found that the correlation values within the ring 140 satisfy these criteria. Working through the process, the results of significant value are all located along each other. Looking at the data shown in Figure 3, the values vary between -3.7368 and 10.7652. When applying the same detection criteria, only one point 160 exceeds the threshold. The value of this point clearly exceeds the threshold and is thus considered to be a valid peak. From inspecting the adjacent values, it can be seen that this represents a pronounced correlation peak. The inserted information represented as payload code K can identify, for example, the owner of copyrights or a description of the content. In the protection of DVD copies, it allows the material to be labeled as 'one copy', 'never to be copied', 'no restrictions', 'no more copies', etc. Figure 10 shows an apparatus for removing and presenting a content signal that is stored in a storage medium 200, such as an optical disk, memory device or hard disk. The content signal is removed by a content removal unit 201. The content signal 202 is applied to a processing unit 205, which decodes the data and validates it for display 211, 213. The content signal 202 also it is applied to a watermark detection unit 220 of the previously described type. The processing unit 205 is arranged in such a way that it is only allowed to process the content signal if a predetermined watermark is detected in the signal. A control signal 225 sent from the watermark detection unit 220 informs the processing unit 205 whether the processing of the content should be allowed or denied, or informs the processing unit 205 of any copy restriction associated with the content. Alternatively, the processing unit 205 may be arranged such that it is only allowed to process the content signal if a predetermined watermark is not detected in the signal. In the above description, a set of three watermarks has been considered. However, it will be appreciated that the technique can be applied to find a correlation peak in content data carrying any number of watermarks.

In the previous embodiment, a correlation technique is used to detect the presence of a watermark in the content. There can be many other ways to detect the presence of a watermark, and the present invention can be applied to any of these in a manner that will be well understood by a skilled person. In the above description, and with reference to the figures, an information signal is described that includes a plurality of Wi watermarks that together define a data payload, such as rights information. A detector 100 detects the presence 60-62 of each of the plurality of watermarks in the information signal and provides an output 101-103 that can be used to determine 70, 75 the payload represented by the watermarks. A confidence measure in the accuracy of the payload represented by the watermarks is calculated 110 using information 104-106 that comes from the detection stages. This provides a measure of the quality of the payload to any equipment that is based on payload results, such as a Digital Rights Management (DRM) system. The information about the shape of correlation peaks obtained in detection stages 60-62 can be used to derive the confidence measure in the accuracy of the payload.

Appendix This section derives a confidence measure of the accuracy of a payload for a correlation based detection scheme such as JAWS, developed by Philips. The Maximum A Posteriori (MAP) calculation t of the displacement corresponding to the payload is: This says that, given a volatile memory of SPOMF results y, a correlation peak shape s and that the content is marked with water (Hw), the calculated payload displacement, ... is that with the highest probability. The watermark correlation peak can be assumed to comprise C adjacent points, such that the elements of the peak shape vector St are: c-i sT. { k) =? a¡d. { k-t-i) (!)! = 0 and the shape of the peak is controlled by the parameter vector = • •• c_, J. Assume that each possible payload displacement t ± has an earlier probability Pr [Ti], then: In some applications it may be possible to assume that all possible payload shifts have equal prior probabilities, and therefore do not influence the choice of. However, this will not be the case in all applications. For example, in protection against copies, only four possible payloads may be used that correspond to the messages 'Do not copy', 'Copy freely', 'Copy once' and 'Do not copy more'. Moreover, these four payloads do not necessarily have an equal probability whenever there can be much more content of 'Copy freely' than protected content, or vice versa. .A In the case of material without water marks \ HW), it has been shown that the N elements of y are approximately independent Gaussian white noise. In the case of being material with watermarks v ", the experiment shows that the SPOMF results are again approximately Gaussian noise, but there is also a peak.The PDF under Hw is therefore: Substitute this in equation 2 gives: t = ma Pr [r1] (2 / A-i JV-1? G-I t = maxPrf-r Cl) 2 expj? Y (fc) 2 ~ 2? Y (¿) s, (fc) +? * (/) A = o k = 0 i = 0 This equation can be further simplified by pulling all the terms that are constant with respect to the value of i. This includes both the first and the third summations in the previous expression, because the displacements are cyclic. The result is:? F -l t = maxPr [r1] ex? Y. { k) stí. { k) k = 0 (4) This shows that the best calculation of the displacement of the payload is governed by the previous probability of each displacement, and the cross-correlation between the contents of the volatile memory SPOMF y and the peak form s. Substitute the peak shape model of equation 1 for equation 4 gives: C-1 í = ma Pr [rj] ex? ß / JV (^ +) 1 = 0 (5) A confidence measure of the extracted payload can be derived from the probability of error in the choice of £. An error is made if at least one displacement ti has a higher probability PrtT ^ y, ^, ^] than that of displacement 7C that corresponds to the correct payload: Pr [Error] Using equation 5, pc, i can be written: If fc is the displacement corresponding to the correct payload, then from equation 1: Y. { tc + l) = stß) + n. { tc + l) C-1 =? amd. { l -m) + n. { tc + l) = at + n. { tc + 1) where n (.) is AWGN. Also: y (ti + I = sTt (tj + l) + n (tl + t) c-i =? Aad (l + -te-m) + «te + 0 -0 Substitute these two expressions in equation 7 gives: = Prpp; > 2]] where C-1 is zero standard deviation and standard equal to sw ~? -_,to? and the / = or threshold T ± is given by: The first sum is the total energy of the correlation peak. The larger this energy term is, the greater the value of pC? Í and therefore the smaller the probability of a payload error in equation 6. The second summation is the self-correlation of the form, peak for non-zero displacements. The larger this term is, that is, the more stained the correlation peak is, the greater the probability of error. The expression for pC? ± can now be written as: where F (Z) is the cumulative probability distribution of a Gaussian random variable of single standard deviation. Finally, substituting this in the expression for the error probability (equation 6) gives: This probability of making an error to determine the payload displacement gives a measure of the reliability of the payload with watermark extracted. It is noted that in relation to this date, the best method known to the applicant to carry out the aforementioned invention, is that which is clear from the present description of the invention.

Claims (15)

CLAIMS Having described the invention as above, the content of the following claims is claimed as property:

1. A method for processing an information signal in which a plurality of watermarks are present, the plurality of watermarks together defining a payload, characterized in that it comprises: detecting the presence of each of the plurality of watermarks in the information signal; Determine the payload represented by the watermarks and calculate a confidence measure in the accuracy of the payload represented by the watermarks. The method according to any one of the preceding claims, characterized in that it further comprises comparing the confidence measure with a threshold confidence value, and providing an output based on the comparison with the threshold confidence value. 3. The method according to claim 2, characterized in that it further comprises not determining the payload represented by the plurality of watermarks if the output indicates that the confidence measure is below the threshold confidence value. The method according to any of the preceding claims, characterized in that the step of detecting the presence of each watermark comprises: deriving, for each watermark, a set of correlation results by correlating the information signal with a of more watermarks for each of a plurality of relative positions of the information signal with respect to the watermark and detecting a peak of correlation in the set of correlation results for each watermark. 5. The method of compliance with the claim 4, characterized in that the confidence measure in the payload is based on the correlation results in the region of the correlation peak. 6. The method of compliance with the claim 5, characterized in that the confidence measure is related to the total energy of the correlation peak. The method according to claim 5 or 6, characterized in that the confidence measure is related to the shape of the correlation peak. The method according to any of claims 4 to 7, characterized in that it further comprises identifying groups of correlation results that are likely to represent correlation peaks, and processing the groups to identify the group that is most likely to represent the peak of real correlation. 9. The method according to claim 8, characterized in that the step of identifying groups of correlation results comprises determining all the correlation results in the set that exceed the threshold value and then determining which of those correlation results are located within a predetermined distance from each other. The method according to any of claims 4 to 9, characterized in that the step of detecting the presence of watermarks comprises comparing at least part of the set of correlation results with information about an expected form of a correlation peak. in the results. 11. Software characterized in that it is for carrying out the method according to any of the preceding claims. 1

2. A provision for processing an information signal in which a plurality of watermarks are present, the plurality of watermarks together defining a payload, characterized in that it comprises: means for detecting the presence of each of the plurality of watermarks. watermarks in the information signal; means for determining the payload represented by the watermarks and means for calculating a measure of confidence in the accuracy of the payload represented by the watermarks. The arrangement according to claim 12, characterized in that it further comprises means for carrying out any of the steps of the method according to claims 2-10. 14. The arrangement according to claim 12 or 13, characterized in that the means for detecting, means for determining and means for calculating comprise a processor that is arranged to execute software to carry out those functions. 15. Apparatus for presenting an information signal comprising means for disabling the operation of the apparatus depending on the presence of a valid watermark in the information signal, characterized in that it comprises the arrangement according to any of claims 12-14.