EP1815444A1

EP1815444A1 - Device and method for the visual representation of measured values

Info

Publication number: EP1815444A1
Application number: EP05798830A
Authority: EP
Inventors: Thomas Giering; Wolfgang Rauscher; Wolfram Seidemann
Original assignee: Giesecke and Devrient GmbH
Current assignee: Giesecke and Devrient GmbH
Priority date: 2004-10-14
Filing date: 2005-10-11
Publication date: 2007-08-08
Anticipated expiration: 2025-10-11
Also published as: US8542866B2; US20090074229A1; WO2006042668A1; EP1815444B1; DE102004049998A1

Abstract

The invention relates to a device and a method for visually representing measured values. The aim of the invention is to mask the visual representation of authentic data or other measured values by visually representing camouflaged data rather than the measured values, said camouflaged data being formed by measured values that are modified using a mathematical algorithm.

Description

Device and method for the visual display of measured values

The invention relates to a device and a method for the visual representation of measured values.

Although not limited thereto, the invention also specifically relates to apparatus and methods for checking value documents, such as e.g. Systems for checking the authenticity and / or the nominal value of value documents in which measured values of the value documents are recorded and test results are displayed visually. Such value documents may e.g. Banknotes, checks, chip cards, ID cards, passports or the like.

For testing the luminescence radiation emanating from a value document, such as e.g. Of phosphorescence or fluorescence radiation, systems are usually used, as described by way of example in DE 23 66 274 C2. Thereafter, a banknote to be tested is irradiated with light and the remitted luminescent radiation is detected spectrally resolved in order to determine whether a luminescent feature substance is actually contained in the banknote to be tested.

A luminescent feature substance is understood as meaning a substance consisting of a single component or of a mixture of a plurality of components which exhibit a luminescence behavior. These feature substances, which may be present for example in the form of pigments, are contained in the value document itself and / or applied to it. The feature substances may, for example, also be applied in spatially coded form in order to be able to differentiate between different denominations of a monetary system. In order to make it more difficult for counterfeiters to create forged banknotes, it is attempted to keep information about the exact composition and the characteristic spectral properties of the luminescent feature substances, which are measured by the luminescence sensors, secret.

A proven concept for keeping this information secret is that also the associated luminescence sensors must be secured in such a way that they do not give any measured values to the outside.

For this purpose, e.g. the luminescence sensor mounted with its evaluation electronics in a secured against access closed housing. The evaluation electronics serve to evaluate the recorded measured values. Classify the banknote into one of the categories "genuine", "false", "counterfeit" or "unrecognized" banknote.

In this case, the housing has an interface for the transmission of data to an external unit, such as a control unit of an ATM or a B-node sorting device, in which or which of the luminescence sensor is integrated. The control unit is usually connected to a display at which the operator of the ATM or the banknote sorting device information about the result of the test are displayed, ie displayed visually. Of particular interest is the transmission of data to an external unit, such as a downstream data evaluation unit or the display of a quality control device which is used for quality control of the banknote during or after its manufacture. Especially in this case, it is of interest or even necessary to provide the user with additional information about the feature in addition to the intensity of the feature, so that the production can be performed within predetermined tolerances. Alternatively, downstream of the production, a check of predetermined tolerances can take place, which evaluates more than merely, for example, the intensity of the luminescent substance.

It is essential that no measurement data is transmitted to the external unit via the interface of the luminescence sensor. Only the classification results themselves (genuine, false, counterfeit suspect, unrecognized banknote) are passed on from the banknote sensor to the external unit and displayed.

Since an authorized or even unauthorized user of the luminescence sensor thus receives no information about the actual measured values of the bank notes in principle, no conclusions can be drawn about the luminescent feature substances. In this way, a secrecy of information about the luminescent feature substances can be reliably ensured.

However, luminescence sensors for bank notes, which are equipped with an analog interface for forwarding measured values of the measured luminescence radiation to an external unit, have recently become available. For quality control in the case of paper or banknote production, graphical representations of the spectral curves themselves are then displayed on a screen of the external unit. Thus, persons who use the luminescence sensors can obtain information about the measured values themselves or variables derived therefrom, for example via the measured spectral curves of the luminescent feature substances, through the visual representation. This makes it possible to draw conclusions about the luminescent feature substances which, in principle, can also be used abusively to simulate the feature substances.

On this basis, it is the object of the present invention to provide a device and a method for the visual representation of measured values, in particular when testing documents of value, which avoid the disadvantages mentioned above.

This object is solved by the independent claims. The dependent claims and the following description explain preferred embodiments.

The present invention thus proceeds from the idea of visually rendering the visual representation of authenticity data or other measured values by not visually displaying the measured values themselves, but invisibility data which is modified by means of a mathematical algorithm Measured values are formed.

The advantages of this camouflage concept are particularly evident in the preferred application of the examination of value documents, in particular in the examination of the luminescence radiation of security paper or banknotes. O

As mentioned, in the known sensor concept described last, measured values are transmitted to an external monitoring station by means of an analog interface, at which point, for example, the measured spectral curves of the luminescent feature substances are displayed.

In contrast, according to the present invention, e.g. Only camouflage data are displayed, which are caused by a change in the measured values and vary with the actual measured values. If the actually measured spectral curves are displayed in the prior art, modified spectral curves with altered intensity ratios are displayed according to the present invention, for example.

As will be explained, although a quality control or the like can also be facilitated by an analysis of the visual representation of the cover data, it is not possible to draw any direct conclusions about the luminescent feature substances of the banknotes causing the luminescent radiation.

In other words, the inventive concept of camouflage of the measured values thus enables secrecy of the luminescent feature substances much better than the known sensor concept with analog interface, although the user of the sensor simultaneously also receives a certain amount of information about the measurements which he, for example, receives can use for quality assurance. Depending on the application, the camouflage can be done differently. That is, for example, when it comes to checking the spectral amplitudes in the quality check, these are to be displayed in such a way that the conclusions as to the amplitudes necessary for the quality assessment are still possible. However, the shape of the individual spectral curves, the order of the spectral amplitudes or their distance from one another, etc. can be alienated as desired.

If, on the other hand, in another application, e.g. primarily to check whether certain substances, e.g. in a value document, it is important to emphasize this fact, i. to show an associated curve for each substance. In this view, the amplitudes may be e.g. even though they are different in reality. As a result, conclusions about the intensity can be avoided.

Depending on the application, therefore, only necessary data for this application are displayed, while other data are not displayed.

Preferably also different Tarndarstellungen can be selected to test the same substances for different applications. This leads to the fact that a person who has access to different applications can not benefit from it. In other words, in different applications, the mathematical algorithms will vary so that, for different measurements, the cover data for the same test object also varies with identical measured values. Further advantages of the present invention will become apparent from the dependent claims and the following description of Ausführungs¬ examples with reference to the accompanying figures.

It should be particularly emphasized that the features of the dependent claims and the embodiments mentioned in the following description can be used advantageously in combination or independently of one another and from the subject matter of the main claims.

The show

Figure 1 is a schematic view of a test device for banknotes;

FIG. 2 shows a detail of a spectral curve measured with the test device;

FIG. 3 shows a first visual representation of camouflage data for the spectral curve of FIG. 2;

FIG. 4 shows a second visual representation of camouflage data for the spectral curve of FIG. 2;

FIG. 5 shows a third visual representation of camouflage data for the spectral curve of FIG

Figure 2;

Figure 6 shows a section of another measured with the tester

spectral; FIG. 7 shows a visual representation of camouflage data for the spectral curve of FIG. 6;

FIG. 8 shows a detail of two spectral curves of two codings of a currency system measured with the test device;

FIG. 9 a visual representation of two camouflage curves for the two spectral curves of FIG. 8;

FIG. 10 shows a detail of three spectral curves of a genuine banknote and two counterfeits measured by the testing device;

Figure 11 is a visual representation of three camouflage curves to the three spectral curves of Figure 10;

FIG. 12 shows a detail of the tolerance range of spectral curves measured as truly classified with the testing device and of a spectral curve of a counterfeiting;

Figure 13 is a visual representation of camouflage curves to the spectral curves of Figure 12;

FIG. 14 shows a detail of a plurality of spectral curves of bank note feature substances measured by the test device and of not in FIG

Banknotes contain other substances; Figure 15 is a visual representation of camouflage curves to the spectral curves of Figure 14;

Figure 16 is another visual representation of camouflage curves to the spectral curves of Figure 14;

FIG. 17 shows a visual representation of information bars for quality testing in the production of value documents and

FIG. 17 shows a visual representation of the formation of the cover data from the measured values.

Although not restricted thereto, the following will focus in particular on the testing of banknotes or other documents of value provided with luminescent feature substances. The luminescent feature substances can e.g. be inserted and / or printed in the banknote paper itself. Sensors for measuring such feature substances may e.g. in papermaking, banknote printing, banknote counting, banknotes, bill dispensers, vending machines, or other banknote processing devices.

FIG. 1 shows, in a merely exemplary manner, a schematic view of an example of such a processing device 1 in which freshly printed banknotes BN are checked for their print quality. The processing device 1 in this case has a printing station 2 in which the banknote paper is printed with security ink. The printing ink contains lumi- nescent feature substances. The banknotes BN, which are still present in the sheet form or have already been cut into individual nips, are then transported in the transport direction T past a checking device 3, which checks the printing quality.

The test device 3 serves in particular for luminescence testing of luminescent feature substances contained in the printing ink and for this purpose comprises a lighting unit 4 to illuminate the banknotes BN to be tested, a spectrometer as sensor unit 5 for spectrally resolved detection of the Lumi emanating from the illuminated banknote BN ¬ Neszenzstrahlung and connected to the lighting unit 4 and the Sensor¬ unit 5 computer-assisted evaluation unit 6 to evaluate the detected by the sensor unit 5 signals.

The evaluation unit 6 is preferably attached to the sensor unit 5 in a common housing 7. The evaluation unit 6 can, however, also be a separate component that is connected via a data line to the illumination unit 4 and the sensor unit 5.

The housing 7 is secured against unauthorized access and has a Schnitt¬ point 9 to transmit data from the test device 3 to a control computer 8, the processing device 1 depending u.a. the evaluation results of the test device 3 controls and e.g. Banknotes BN marked or rejected with poor print quality.

The control computer 8 is connected to a screen 10 on the transmitted from the tester 3 data for each measurement are displayed (curve 11). The displayed data can be used by a user to control the device 1 by means of an input unit 12. However, this regulation can also be automatic. The regulation may be, for example, that the dosage of the luminescent feature substances in the printing ink is changed in the printing station 2.

Excellent is the device 1 by the type of data which are transmitted via the interface 9 of the test device 3 and the evaluation unit 6 for display on the screen 10. Via the interface 9, no measured values, but camouflage data are transmitted. The cover data are formed by the fact that the actual measured values are changed in the evaluation unit 6 with the aid of a mathematical algorithm. Based on the following figures, this concept will be explained in more detail using several examples, whereby the individual examples can also be combined with one another.

Example 1:

FIG. 2 shows, in a simplified manner, a section of a spectral curve of a luminescent banknote BN actually measured by the test device 3, ie the dependence of the intensity I on the frequency f of the luminescence radiation. This spectral curve is formed by a larger number of measured values, not shown, and is characterized by two different sized maxima at frequencies f1 and f2. The maximum at the frequency fl is caused by a first substance "a" and the second maximum at the frequency f2 is caused by a second substance "b", both in Mixture the luminescent feature substance contained in the paper bil¬ the.

While in the prior art such a measurement curve would be displayed on the screen 10, the associated measurement values according to the invention are not forwarded for display on the screen 10. It is thus deliberately precluded that an actual measurement curve according to FIG. 2 can be displayed in order to prevent the secrecy about the exact composition of the measured feature substances being endangered. Instead, measured values altered by a mathematical algorithm are forwarded as disguised cover data via the interface 9 and displayed on the screen 10 as a fogged spectral curve 11.

Example 2:

FIG. 3 shows a very simple example of camouflage data being formed by changing the assignment of the measurement intensities to the frequencies. In this case, the camouflage data are of the same physical size as the measured values, ie the camouflage data, like the actual measured values, are also data on frequency-dependent intensity values. However, a concealment of the assignment of the intensity values to the frequencies ensues for concealment. In the specific case of FIG. 3, the position of the maxima of the substances a and b in the frequency spectrum considered is interchanged and the distance between the maxima is increased for camouflage. However, the measurement intensities and the frequencies could also be mixed much more complex. Thus, for example, the intensities measured at 50 frequencies fl, f2, f3, f4, ... f50 the frequency fl3, FL9, H ₁ (2 be allocated, etc., and suitable particularly for a large number of measured frequencies (in the example 50) Permutations, for example, at least partial aspects of the functional relationships obtained, the frequencies of a complete mixing are preferable.

Example 3:

FIG. 4 shows a second example of a camouflage cam 11 belonging to the measurement according to FIG. 2, which is formed by camouflage data which are forwarded by the test device 3. In this case, the formation of the displayed camouflage data takes place by different scaling of different measured values. In the concrete example, the relative maxima of the

Stoffs "b" to the value of the absolute maximum of the spectral curve, caused by the substance "a" normalized. This concept makes it possible to check the principle presence of the substances a and b despite the display of the caravan.

Example 4:

FIG. 5 shows a third example of a camouflage curve 11 belonging to the measurement according to FIG. 2. This case is distinguished in that the camouflage data are formed by the spectral curves in the regions around the relative maxima of the substances a and b at the frequencies f 1 and f2 be superimposed. The course of the camouflage curve is exemplarily formed by the sum of the measured values scaled by the factor 4/5.

Example 5:

FIG. 6 shows a further example of a spectral curve measured by the test device 3, corresponding to FIG. In contrast to the prior art, the measured values of this spectral curve are again not transmitted from the test device 3 to the display on the screen 10. The spectral curve has three maxima for the substances a, b, c contained in the feature substance.

FIG. 7 shows an example of a camshaft 11 belonging to the measurement according to FIG. 6 for display on the screen 10. This camouflage curve 11 is a combination of the previous examples and characterized by a mixing, overlaying and different scaling of the measured values to form the illustrated camouflage curve ,

Example 6:

FIG. 8 shows two spectral curves actually measured by the test device 3. The solid line corresponds eg to a first coding a and the dashed line corresponds to a second coding b of a currency system. The different codes can for example consist in the use of different combinations of substances as feature substances and be used for example to denominate differentiation. The individual spectral However, curves a, b can also be on different substances contained in the tested banknote in combination.

In FIG. 9, two associated camouflage curves 11 are shown by way of example, as they can be displayed on the screen 10. In particular, the individual spectral curves a, b are mapped as a single peak, the distance of the individual peaks of the caricature being preferably constant. However, it is also possible that another type of display is selected, which indicates whether or not the coding or the substance a, b is contained in the checked banknotes, without indicating how the underlying spectrum of the codes or the substance a, b actually looks.

In addition, it can be provided that in the caricature display also an indication of the measured amplitudes of the individual codes or substances a, b is included. Thus, a change in the total intensity of the individual actually measured spectral curves a, b of FIG. 9, e.g. due to contamination in banknotes already in circulation, then e.g. result in a change in the size of the individual peaks of the camouflage curves 11.

In particular, in cases in which the testing device 3 is used, for example, in central banks, cash centers or cash deposit machines for checking already circulated bank notes, the checking device 3 will be designed to check the authenticity of the bank notes. In such a case, the evaluation unit 6 will perform a genuineness classification of the banknote. This can consist, for example, in that at least a distinction is made between genuine and false banknotes or between genuine, false, counterfeit, unrecognized banknotes. This classification can firstly be a preliminary classification, which is obtained only on the basis of the measured values of the test device 3 and, for example, only indicates whether the measured luminescence behavior corresponds to a genuine banknote. However, this classification may also be a final classification which also takes into account the measurements of other measurements made in the device 1, such as other optical, acoustic, magnetic and / or electrical measurements.

The evaluation is preferably carried out on the basis of the actually recorded measured values and not the camouflage data determined therefrom for display. However, the display of the stealth data can serve to provide certain information about the measurements of genuine and false banknotes, without at the same time promoting the secrecy of the actual spectral curves of genuine banknotes.

Example 7:

FIGS. 10 and 11 show a further comparison of actual measuring curves (in FIG. 10) and associated camouflage curves 11 (in FIG. 11). The spectral curve e in FIG. 10 corresponds to the actual measurement curve of a genuine banknote, while the spectral curves x1, x2 correspond to actual measurement curves of two different counterfeits.

In the associated Tarndarstellung of Figure 11, the entire Meß¬ curves or at least predetermined ranges of the traces are superimposed. This can be done, for example, by superimposing the measurement curves in such a way that the absolute maxima of all measurement curves, ie both the genuine banknotes and the counterfeits, are displayed one above the other. This is done sensibly by different colored representations. Optionally, in addition, the above-mentioned further Tarnvarianten eg the different scaling and mixing of the measured values can be used.

According to a further idea of the present invention, it can be provided that the mathematical algorithm varies for different measured values and consists for example of a plurality of different partial algorithms and measured values vary differently with different partial algorithms depending on whether the measured values fulfill at least one given criterion become.

This means that e.g. In a genuineness or quality control of value documents, a distinction can be made as to whether the measured values lie within a predefined tolerance range to be expected or differ too greatly from the values of genuine banknotes.

In particular, in the case that the measured values are within the range typical for real bank notes, the measured values for forming the Tarnda¬ th will be changed by a locally continuous mathematical function. This local continuity means that small deviations in the measured values only lead to small deviations in the associated camouflage data. Thus, at least in this example, for real banknotes limited Meßwertbe- a certain traceability of the effects, for example of intensity fluctuations of the spectrum, on the illustrated camouflage curves is possible.

This range can also be set to be e.g. also realistically covers the fluctuations in the dosage of the feature substances which are customary in paper and banknote production.

However, if the readings outside the e.g. for genuine banknotes of the typical range, the measured values are preferably changed more strongly than within the range typical for genuine banknotes, and e.g. be changed by a locally discontinuous mathematical function.

Thus, no conclusions are possible to what extent the real and the false substances are related to one another.

Example 8:

An example of this is illustrated in FIGS. 12 and 13. Figure 12 again shows actually measured spectral curves. The hatched area illustrates the tolerance range for the measured values of a banknote with two feature substances a and b, which is identified by the reference symbol "e", and which is classified as "genuine" by evaluating, inter alia, these measured values. With "x" the spectral curve of a forgery is shown, which contains only the feature substance a.

In Figure 13 associated Tarnkurven 11 are shown. It can be seen that the counterfeit (x) classified as not "genuine" is due to another mathematical function is significantly more varied than the measured values within the tolerance for banknotes classified as "real" (e).

Since there is no similarity in the display of the two curves, it can not be concluded that the substances have a certain similarity.

Example 9:

Alternatively or additionally, it may also be provided that the mathematical function for forming the camouflage data is configured only for measured values which lie within a predetermined tolerance range such that no two measured values are mapped to the same camouflage value. Outside the tolerance range, this requirement can even be purposefully violated, i. that in particular different measured values are formed on the same camouflage value. Example 10:

It can also be provided that forwarding and / or presentation of the cover data takes place only when the associated measured values fulfill at least one predetermined criterion. In particular, if the stealth data is displayed only when the checked banknote BN belongs to a certain class, it is particularly advantageous to classify it as "real." In the example of Figures 12, 13, the stealth data is then classified as non-genuine Bank notes, such as the camouflage curve associated with the forgery x, are not forwarded or displayed by the checking device 3. Example 11:

Preferably, in the case that a luminescent feature to be tested contains several different substances and / or individual peaks, it can also be provided that different types of deviations of the spectral measured values from the spectral nominal values, the substances or the formation of the camouflage data Single peaks, determined and taken into account wer¬. Depending on the type of deviation, it is then preferable to carry out different changes of the measured values to form camouflage data.

This concept is illustrated in FIGS. 14 and 15. The reference symbols a and b in FIG. 14 illustrate the desired curves of the spectral curves of two different luminescent substances to be measured, which are combined in a banknote to be tested or separately, e.g. may be contained in different codings. With xla, x2a, xlb, x2b, the actually measured spectral curves of two other substances are shown, e.g. contained in counterfeits. The spectral curves xla and x2a or xlb and x2b differ by the measured intensity I of the luminescence radiation.

In FIG. 15, associated camouflage curves 11 are depicted, corresponding camouflage curves being identified by the same reference symbols. In the case of the formation of the camouflage curves 11, in this case, for example, it is taken into account whether the measured values of the counterfeits xla, x2a, xlb, x2b lie at larger or smaller frequencies f than the nearest adjacent individual peaks of the components a and b. While with measured values lying in the vicinity of the peak a, the associated camouflage data appear at larger values for larger frequencies, this relationship is reversed for measured values lying in the vicinity of the peak b and the camouflage data then appear in the case of smaller ones Values, ie left and not right of peak b.

Example 12:

FIG. 16 shows a further example of camouflage curves 11 for FIG. 14 and illustrates the concept that a change in a measured quantity (intensity) leads to a change in the camouflage data dependent on the magnitude of this change , In particular, the other way of changing the measured values to form the camouflage data is that, when there are deviations from the predetermined tolerance ranges, e.g. the tolerance ranges for real banknotes comes, shifts the position of the associated camouflage curves for changes in the measured intensities of the counterfeits classified as non-genuine xla, x2a, xlb, x2b.

Example 13:

FIG. 17 shows two bar-shaped displays for camouflage data, as can be displayed on the screen 10, for example, also in the case of FIGS. 15 or 16. This display can be used, for example, to control the introduction of a luminescent feature substance comprising a plurality of substances into the paper or the printing ink of the banknote in the printing station 2. As an example, the scale line M1 in the upper bar indicates whether the mixing ratio of two substances of the sample corresponds to the ideal value (100%) or deviates therefrom. The scale line M2 in the lower bar indicates how large the contamination of the sample is by additional substances. The position of the scale marks M1, M2 is obtained by evaluating the measured spectral curves, eg according to FIG. 14. Permitted tolerance ranges during production are indicated schematically by the hatched areas of the bars.

If such a display according to FIG. 17 has a representation of spectacular camouflaging curves, such as e.g. coupled according to Figures 15 or 16, e.g. then, if the contamination is outside the allowable tolerance range, the forwarding of the associated camouflage data or a graphical representation of the associated Tarnkurven also be omitted.

Example 14:

According to a further idea of the present invention, at least two different sets of camouflage data, which are intended for different target groups, are formed for a measurement. The one camouflage data wer¬ the eg the administrator of a set of test equipment 3 and the other camouflage data the respective users of the individual Prüfeinrichtun¬ 3 fed. The data transmission and / or the display of the different cover data for different target groups preferably takes place only after a corresponding authentication of the respective target group. The type of formation of the cover data will differ in both cases, for example by using different of the camouflage concepts previously explained with reference to the figures. As an example, it should be mentioned that, for example, an administrator displays the camouflage curves shown in FIG. 13 for all banknotes classified as genuine, while the usual user of the checking devices 3 displays only camouflage curves for a smaller tolerance range of all genuine banknotes. Thus, the information "real banknote" and only for a part of the genuinely classified banknotes the associated camouflage curves are preferably displayed to this user Thus, eg the camouflage data, which are still classified as genuine, whose measured values are greater deviations from the have ideal setpoints, not shown.

Example 15:

For example, in the latter case, it may also be provided that the displayed information e.g. The percentage will then indicate, for example, the extent to which the measured values, within the tolerance range permitted for authentically classified banknotes, deviate from the ideal values of a genuine banknote. For example, a 95% genuine banknote will still be classified in the "real" category, but will show deviations from a reference measurement of a genuine banknote.

Example 16: It can also be provided that the checking device 3, together with the camouflage data, forwards an individual checksum or another code which is formed, for example, on the basis of the parameters forming the mathematical algorithm and / or the associated measured values and based on the camouflage data calculates the corresponding measured values back. The algorithm for reproducing the measured values with the aid of the camouflage data and the code is preferably known only to the manufacturer of the testing devices 3, and can be used by the latter, for example, to check complaints of the customers because of possible incorrect evaluations or displays to be able to.

Example 17:

It should be emphasized that in the foregoing, while specifically directed to the measurement of spectral curves, i. has been received by frequency-dependent measurements. However, the same concepts of camouflage can also be used for other measurements, such as spatially or temporally variable measured values. Thus, e.g. time-resolved measured values for determining the decay times of the luminescence radiation are camouflaged in the same way.

Furthermore, according to this concept, other measured values, such as, for example, other optical, magnetic or electrical measured values can be camouflaged. Alternatively, according to this concept, for example, spatial codes can also be disguised. For example, the specific spatial arrangements of security features, eg a two-dimensional, ie in two directions varying bar code, as a one-dimensional, ie in only one direction varying bar code be camouflaged.

Example 18:

According to yet another idea of the present invention, it can also be provided that the checking device 3 evaluates only a part of all recorded measured values for classifying the bank notes.

If the test device 3 comprises e.g. a luminescence sensor for testing the luminescence radiation in the visible or infrared spectral range, the evaluation on the presence of the luminescent Merk¬ malsstoffs and the representation of the associated camouflage curves based only on the measured values in the visible or infrared spectral range.

However, by the same and / or another testing device, other measured values, such as e.g. Measurements on the Druck¬ image, the color behavior, electrical and / or magnetic properties of the bill won.

It can now be provided that when the further measured values do not fulfill given criteria and, e.g. suggest a falsification, the camouflage data generation and / or Tarndatendarstellung is modified.

For example, in the case of FIG. 13, the tolerance range for the cover data may be reduced or even completely forgiven for a visual representation of the cover data. If, for example, the color impression or another authenticity criterion is not met or the tested forgery already does not fulfill further criteria.

Example 19:

It has been described above that, depending on predetermined criteria, the cover data is formed in another way and / or the camouflage data representation is prevented. For luminescence measurements, this criterion can be used e.g. Also include an examination of whether the Lumineszenzmeßwerte for predetermined substances have characteristic properties. These predetermined substances are preferably per se substances not contained in the tested banknotes, but such as are e.g. Usually used for counterfeiting. The mentioned characteristic properties can be determined, for example, by concern the spectral course or the decay times of these be¬ known counterfeiting materials.

It may be provided in such a case that the cover data are then formed in other, more concealing ways and / or the Tarndaten display is prevented when these characteristic properties are measured.

Example 20:

It is also possible that other authenticity data, such as the representation of measured values of biometric sensors, are camouflaged by the methods mentioned. For example, it can not be used when displaying fingerprints the actually measured fingerprint, but a camouflaged Fingerab¬ pressure are displayed, which emerges for example by a mathematical algorithm from the measured fingerprint or is taken according to an algorithm from a reference database.

The same applies, for example. also for the spectral representation of voice analysis, iris identification and other procedures.

Among other things, even in such a case, it may be provided that the cover data is provided to the measurement data as e.g. digital watermarks or as additional data of similar form.

Example 21:

It should be emphasized that in this and the other examples, not necessarily a curve, but only the discrete measured values underlying the curve can be graphically represented.

Example 22:

While above all purely graphical representations of the cover data were described, finally pure numerical data or combined graphical representations with number representations are also conceivable.

Example 23: Another example will now be described with reference to FIG. 18, which illustrates measured data on the left and the camouflage data derived therefrom on the right. In particular, the measured values represented as a measuring vector are present as data points in an n-dimensional space M, for example the IR ⁿ , and are transformed into an m-dimensional space for camouflage, where m can be greater, smaller or equal to n. Different algorithms for camouflage can be used in this space for different classes, for example, depending on which target class i, which is defined for example by a target vector Xi and an associated class area K, is assigned the measurement vector. It is possible that there are regions in which the measuring vector is not assigned to any target class at all, ie the space IR ⁿ need not be completely divided into target classes. In particular, there may additionally be a tolerance range Ti for each target class i, which lies within the class area Ki.

For the camouflage according to the invention, there are initially no restrictions on the function (s) fi, which are e.g. can also be defined only locally in M or the class areas Ki. Alternatively, a function f may be used that shows different behavior in different subranges of M.

However, for quality control in particular, it may be advantageous if the function f (or functions fi) meet certain conditions. For example, it is possible that only the target vector xi is formed on the camouflage value fω (xi). Alternatively, it is possible, for example, that the function (s) is (are) such that no points outside a tolerance range Ti are imaged in the associated camouflage area f (Ti).

Alternatively, it may be required that the function (s) be chosen so that in a sequence of measured measured values yi which converge to a desired value xi, the camouflage values f (yi) also converge to the camouflaged desired value f (xi) , and / or conversely, a sequence of camouflage values f (yi) converging against f (xi) also corresponds to a series of measured values yi converging to xi.

Alternatively, the functions f1 may be chosen such that these restrictions do not apply outside the tolerance ranges Ti, and e.g. Measured values in the space M that are not within a tolerance range, are displayed in an area of the camouflage space that consciously dispenses with an unambiguous assignment.

Claims

Patent claims

1. A method for camouflaging a visual representation of measured values of a test object (BN), comprising the following steps:

- recording of measured values,

- Forming camouflage data (11) from the recorded measured values using a mathematical algorithm for changing the measured values, - representing the camouflage data (11).

Method according to claim 1, characterized by a classification of the measured values into a number of classes, e.g. on the authenticity of the object to be measured (BN).

3. The method according to at least one of the preceding claims, characterized in that there are measured values and derived therefrom camouflage data which belong to the same and / or a different physical size.

4. The method according to at least one of the preceding claims, characterized in that the method for the examination of value documents (BN), in particular for the examination of luminescent value documents and / or for quality testing in the production of Wertdokumen- th is designed.

5. The method according to at least one of the preceding claims, characterized in that the measured values are used for checking the authenticity of the tested object (BN).

6. Method according to at least one of the preceding claims, characterized in that, when measuring a spatial and / or temporal and / or spectral dependence of a property of the value document, the cover data has a spatial, in comparison to the associated measured values, changed spatial, have temporal or spectral dependency.

7. Method according to at least one of the preceding claims, characterized in that a group of measured values is brought into a changed arrangement by the mathematical algorithm, as e.g. in the case of spectral measured values, the spectral assignment of the measured values to the frequencies is changed;

8. Method according to at least one of the preceding claims, characterized in that the mathematical algorithm alters different measured values or different groups of measured values with different mathematical functions, such as e.g. be scaled with different factors.

9. The method according to at least one of the preceding claims, characterized in that for the evaluation of a value document, such as for example to a classification of the value document, the measured values themselves are evaluated and the cover data are not taken into account.

10. The method according to at least one of the preceding claims, characterized in that a result of the evaluation, such. the classification of the value document is forwarded in addition to the cover data via a data line to an external unit (8).

11. The method according to at least one of the preceding claims, characterized in that camouflage data the measurement data as e.g. digital watermarks or as additional data of similar form.

12. The method according to at least one of the preceding claims, characterized in that the representation of the camouflage data comprises a representation of numbers and / or graphs (11), which depend on the camouflage data.

13. The method according to at least one of the preceding claims, characterized in that the representation of the camouflage data by a graphi¬ cal representation of altered spectral curves (11) of the tested value document (BN), wherein the changed spectral curves of the actually measured spectral curves of the tested Distinguish value document (BN).

14. The method according to at least one of the preceding claims, characterized in that a forwarding and / or presentation of Tarn¬ data only takes place when the associated measured values meet at least a predetermined criterion.

15. The method according to at least one of the preceding claims, characterized in that the mathematical algorithm for unterschiedli¬ che measured values varies.

16. Method according to at least one of the preceding claims, characterized in that the mathematical algorithm consists of a plurality of different subalgorithms and measurement values are varied differently with different subalgorithms depending on whether the measured values satisfy at least one predefined criterion.

17. Method according to at least one of the preceding claims, characterized in that the criterion for varying the measured values with different partial algorithms and / or the criterion for forwarding and / or displaying the camouflage data indicates whether the associated test object (FIG. BN) zu¬ least one of several predetermined classification categories is assigned.

18. Method according to at least one of the preceding claims, characterized in that the criterion for varying the measured values with different partial algorithms and / or the criterion for forwarding and / or displaying the camouflage data indicates whether the measured values for characteristic substances have characteristic properties ,

19. Method according to at least one of the preceding claims, characterized in that the deviation of the respective measured values from the associated camouflage data is greater if the measured values satisfy at least one predetermined criterion than if the measured values do not satisfy the at least one predetermined criterion.

20. Method according to at least one of the preceding claims, characterized in that the measured values are subdivided into at least two categories and, depending on whether the measured values are assigned to one of the two categories, continuous mathematical functions are used to form the camouflage data ,

21. Method according to at least one of the preceding claims, characterized in that the mathematical algorithm for forming the camouflage data is designed only for measured values which lie within a predetermined tolerance range such that no two measured values are mapped to the same camouflage value.

22. Method according to at least one of the preceding claims, characterized in that different types of deviations of spectral measured values from spectral nominal values are taken into account in the formation of the camouflage data.

23. The method according to at least one of the preceding claims, characterized in that at least two different measurements

Amount of camouflage data are formed, which are preferably intended for different target groups.

24. Method according to at least one of the preceding claims, characterized in that an individual checksum or another code is formed together with the camouflage data, which can be used to calculate back to the associated measured values with the Tarndata.

25. The method according to at least one of the preceding claims, characterized in that the method is designed for camouflaging the representation of biometric authenticity data.

26. The method according to at least one of the preceding claims, characterized in that predetermined measured values and / or camouflage data associated with these predetermined measured values are not displayed.

27. The method according to at least one of the preceding claims, characterized in that in an examination of the presence of one or more substances or codings (a, b) of a value document (BN) indicate the camouflage data only on the respective substance or the respective Codie¬ tion in the tested value document (BN) is present or not.

28 device (1) for camouflaging a visual representation of measured values with a sensor (3) for recording measured values,

- A unit (6) for forming Tarndaten (11) from the recorded measured values using a mathematical algorithm for

Change of measured values and an interface (9) for forwarding the stealth data (11) to a unit (10) for displaying the stealth data.

29. The device according to claim 28, characterized in that the device for carrying out the method according to at least one of

Claims 2 to 27 is designed.