EP3170154B1 - Procédé et dispositif de vérification de conformité de documents de valeur - Google Patents

Procédé et dispositif de vérification de conformité de documents de valeur Download PDF

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Publication number
EP3170154B1
EP3170154B1 EP15737987.6A EP15737987A EP3170154B1 EP 3170154 B1 EP3170154 B1 EP 3170154B1 EP 15737987 A EP15737987 A EP 15737987A EP 3170154 B1 EP3170154 B1 EP 3170154B1
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Prior art keywords
unfit
fitness
value
documents
function
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German (de)
English (en)
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EP3170154A1 (fr
Inventor
Alfred Schmidt
Marcus Schmeisser
Dieter Stein
Friedemann Löffler
Sergii Kruglyk
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Giesecke and Devrient Currency Technology GmbH
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Giesecke and Devrient Currency Technology GmbH
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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/181—Testing mechanical properties or condition, e.g. wear or tear
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency

Definitions

  • the invention relates to a method and a device for testing the fitness of documents of value, such as banknotes, checks, tickets, ....
  • fitness testing is understood to mean, on the one hand, checking the fitness of used documents of value, e.g. banknotes in circulation, on the other hand also the quality check of new documents of value after their production before they go into circulation, for example the quality check of banknotes freshly printed.
  • US2002 / 0043560A discloses an assessment system for banknotes using a neural network and fuzzy logic. Also the EP0706698B deals with the assessment of banknotes. With the help of measurement parameters, it is decided whether the banknote is suitable for reuse.
  • the US2008 / 0034313A generally refers to the use of fuzzy logic to replace threshold values and Boolean logic.
  • the US7978899B discloses a bank note processing system in which a fitness type and / or a fitness level is assigned to a bank note.
  • a disadvantage of the known methods is that it is complicated for the user to define suitable threshold values for the sensors. In this case, for example, by the manufacturer of a value document processing device already predetermined threshold values, which are rigidly predetermined, assumed. Problems arise B. by aging or soiling of the value document processing device or due to changes, for example aging, of the value documents to be processed over time. If one or more of the threshold values is set by the user even just slightly too high, value documents which are actually no longer suitable for circulation are classified as fit by the value document processing device. However, if one or more of the threshold values is set by the user even just slightly too low, value documents which are actually suitable for circulation are classified as unfit by the value document processing device. Thus, the value documents to be processed are not sorted into fit and unfit value documents in the manner desired by the user.
  • the object of the present invention is therefore to improve the fitness check of documents of value.
  • At least two different fitness criteria of the value documents are selected for the state the documents of value are characteristic.
  • the value documents are checked by recording measurement data, a fitness measurement value for the respective value document being determined from the recorded measurement data for each of the selected fitness criteria.
  • a degree of unfit of the respective value document is then determined from the respective measured fitness value for each of the selected fitness criteria.
  • the unfit degree is determined with the help of an unfit function, which uniquely assigns an unfit degree to each fitness measurement value.
  • Each unfit function is characterized by a first threshold value, a second threshold value and an uncertainty range lying between the first and the second threshold value, in which the respective unfit function either has a monotonically decreasing or a monotonically increasing profile.
  • the unfit degrees of the various fitness criteria are then combined to form an unfit probability that is specific for the respective value document.
  • a fitness classification of the respective value document is carried out, in which the respective value document is classified as fit or unfit.
  • one or more further fitness classes can also be provided, for example ATM-fit for documents of value with particularly great fitness.
  • Unfit degree of the respective fitness criterion is a quantitative measure for the fitness of the value document in relation to the respective fitness criterion.
  • the same value document is assigned its own unfit degree (only valid for the respective fitness criterion) for each of the fitness criteria.
  • the unfit function according to the invention introduces a fuzzy distinction between fit and unfit with regard to the respective fitness criterion.
  • the fitness test is based on the perception of a human observer.
  • a common unfit probability is determined for several fitness criteria.
  • the fitness test is therefore easier to oversee for the user of the device. If the user wants to change the severity of the fitness test, e.g. tighten it, he can do this simply by changing the one threshold value with which the unfit probability is compared. The unfit functions of the various fitness criteria do not need to be changed. In contrast, up to now, to tighten the fitness test, all threshold values have to be tightened individually, with the size of the shift in the threshold value also having to be specified for each fitness criterion.
  • the invention allows an intuitively understandable procedure, since firstly the uncertainty areas are based on actual, comprehensible fitness measurement values can be established, and secondly, a single unfit probability is derived for the respective value document.
  • the method according to the invention is also stable with respect to small changes in the fitness of the documents of value examined.
  • the results of the fitness classification can be used to observe and thus monitor the development of the fitness of a large number of value documents over time. If the fitness of the value documents on average no longer corresponds to the specifications made for them, measures can be taken to meet the specifications again in the future. For example, the fitness of used documents of value that are in circulation can thus be monitored and controlled, but also the fitness of new, freshly printed documents of value in the course of the quality check before the documents of value go into circulation.
  • the number or the proportion of the value documents classified in a certain fitness class e.g. as fit or unfit
  • the unfit proportion, the fit proportion, etc. can be used or an average value of the unfit Probability over the multitude of documents of value.
  • the fitness classification of the same or different types of value-document processing devices can be compared with one another or of value-document processing devices that are located at different installation locations or the value documents of different regions can be checked.
  • individual threshold values can be used for each type of value document, since each value document type has its own physical properties which can differ greatly from one another.
  • individual threshold values can be used for each denomination and / or issue of the respective currency.
  • the same threshold values can also be used for similarly created value documents, e.g. for bank notes of different denominations but the same currency.
  • the threshold values can be established for the respective value documents or optimized if necessary in advance of the fitness test, e.g. when adapting the respective value document type.
  • the first and / or second threshold value of the unfit function of a fitness criterion can be derived from the hitherto customary (single) threshold value that was previously used for the fitness test on the basis of this fitness criterion.
  • the previous threshold value is used as the upper threshold value of the unfit function and the lower threshold value of the unfit function is selected below it.
  • the first and second threshold values can be placed symmetrically around the previous threshold value.
  • the selection of the fitness criteria of the various fitness criteria can be carried out manually or automatically.
  • the fitness criteria are automatically selected, for example at least two predefined fitness criteria are selected which were established in advance of the fitness test for the respective value documents, for example individually for the respective value document type.
  • the setting can also be carried out by an expert Based on empirical values.
  • the fitness criteria selected are preferably those in which the respective frequency distribution of the fit and unfit value documents are separated from one another as far as possible or overlap as little as possible. For example, those fitness criteria are selected in which the respective frequency distributions of the fit and unfit value documents have a maximum of 30% overlap.
  • the value-document processing device can propose to the user such fitness criteria for selection (e.g. display on the user interface of the value-document processing device) which are particularly well suited for distinguishing between fit and unfit value documents. For example, those fitness criteria are suggested whose fit and unfit frequency distribution show the smallest overlap.
  • the fitness criteria are displayed, for example, in the order of descending overlap of the frequency distributions on the user interface of the value document processing device.
  • the results of the fitness classification can be displayed on the user interface, e.g. the development of the fitness of a large number of value documents over time or in comparison with the results of the fitness classification of other value documents.
  • the selected fitness criteria relate in particular to one or more of the following properties of the value documents: soiling, wear and tear, damage, foreign bodies (for example adhesive strips) or limpness of the respective value document. At least two different of these fitness criteria are preferably selected. If the method according to the invention is used to check the quality of new value documents, one or more of the following fitness criteria can also be selected - in addition to or instead of these fitness criteria: quality of the print (color, error), position of the print image in relation to the value document edges, manufacturing quality of authenticity features (e.g. based on their optical or magnetic properties), position of authenticity features on the value document, etc.
  • the fitness measurement values in question can be determined quantitatively, for example, using the spatially resolved optical transmission, remission or luminescence intensity and, if necessary, suitable image processing.
  • the degree of wear of magnetic authenticity features can be determined quantitatively with the help of a magnetic sensor.
  • the dimensions of adhesive strips or the missing parts can also be determined using the ultrasonic transmission intensity.
  • the limpness, folds or creasing of the value document can be determined quantitatively on the basis of the ultrasound transmission or remission intensity in one or more ROIs or the entire value document and selected as a fitness criterion.
  • the combination of the unfit degrees of the selected fitness criteria is carried out, for example, in such a way that, for each selected fitness criterion, up to one certain fitness measurement value (e.g. up to the first threshold value) the respective fitness criterion does not influence the fitness classification (unfit probability) of the respective value document at all, but that the respective fitness criterion from a certain fitness measurement value (e.g. from the second threshold value) decides the fitness classification of the respective value document, and that the respective fitness criterion for fitness measured values in the uncertainty range only partially influences the fitness classification in interaction with the other selected fitness criteria.
  • This is achieved, for example, by the following formula (1).
  • the unfit degrees of the various fitness criteria can be multiplied - individually for each value document.
  • Combining the unfit degrees of the various fitness criteria to form the unfit probability P can, however, also be carried out by a linear combination of the unfit degrees G j of the various fitness criteria, in particular by adding up the unfit degrees, possibly with different weighting of the unfit degrees of various fitness criteria.
  • the two frequency distributions of the respective fitness measurement value are used to determine the first and / or the second threshold value of the respective unfit function for the respective fitness criterion and / or to determine / optimize the course of the unfit function in the uncertainty range.
  • This can be done manually, by a person, or automatically, by the device.
  • a value range of the respective fitness measurement value in which both fitness measurement values of fit value documents and fitness measurement values of unfit value documents are located is used as the uncertainty range of the unfit function of the respective fitness criterion.
  • the uncertainty range can encompass the entire range of values in which both fitness measurement values of fit documents of value and of unfit documents of value lie, or also just a section of this range of values.
  • the two frequency distributions of the respective fitness measurement value are used to select those fitness criteria for the fitness classification in which the frequency distribution of the fit value documents and the frequency distribution of the unfit value documents overlap as little as possible (e.g. a maximum of 30% overlap of the two frequency distributions).
  • the respective unfit function can be determined, for example, in such a way that a first threshold value of the unfit function is placed on a fitness measurement value for which the fit frequency is much greater than the unfit frequency, in particular at least one specific one Has ratio (eg 5: 1), and the second threshold value is placed on a fitness measurement value, in which the fit frequency is much smaller than the unfit frequency (see, for example, the threshold values X1 and Y1 in the histogram of the Fig. 2a ).
  • the accumulated frequency distribution (cumulative histogram) of the fitness measurement values can also be used to determine the first and second threshold values.
  • the first / second threshold value is placed on a fitness measurement value, in which the accumulated frequency of the fit value documents has a certain ratio to the accumulated frequency of the unfit value documents.
  • a course of the unfit function can be selected that was defined in advance of the fitness test for the respective fitness criterion, in particular on the basis of empirical values.
  • the two threshold values can also be determined manually by selecting the respective threshold value from a large number of predetermined threshold values.
  • the simulation has the advantage that the fitness classification can be optimized without renewed recording of measurement data from the value documents of the value documents to be checked. Thus, an additional mechanical stress on the value documents, which is repeated Recording of measurement data in a value document processing device would be avoided.
  • the simulation is carried out after the value document check on the basis of a large number of checked value documents (which may have been checked by several different value document processing devices), for example by the central bank, in order to control the quality of banknotes in circulation.
  • the unfit function of the respective fitness criterion in particular the position of the two threshold values (i.e. the position of the uncertainty area) and / or the course of the unfit function in the uncertainty area is changed for the respectively selected fitness criterion.
  • the unfit function of this fitness criterion depending on the result of the fitness classification of the value documents of the value document group, can be changed in such a way that the unfit portion in the repeated fitness classification, as desired, is either increased or decreased.
  • the unfit portion can be adapted to the unfit portion that was previously determined during manual presorting for this value document group.
  • the unfit portion can, however, also be adapted to a predetermined unfit portion that has resulted for the same value document group at one or more other value document processing devices.
  • the same value document stack is brought to a plurality of value document processing devices and there (with the same or also with different sensors) is subjected to a fitness test.
  • the fitness test on several value document processing devices can be equated. This is because the unfit portion achieved at different value document processing devices has not always matched up to now, for example when the sensors of the value document processing devices are different, use different measuring principles or are not calibrated to match, or if the value-document transport takes place at different speeds or by different transport devices.
  • the first and / or the second threshold value is changed (e.g. one or both of them reduced) so that the rigor of the fitness test is increased when the fitness is re-classified.
  • the first and / or second threshold values are changed (e.g. one or both of them increased) in such a way that the severity of the fitness test is reduced when the fitness is re-classified.
  • fitness criteria in which the degree of unfit in the uncertainty area increases monotonically with increasing fitness measurement value (e.g.
  • one or both threshold values are increased in order to reduce the percentage of unfit, and if the percentage of unfit If the proportion is too low, one or both threshold values are reduced in order to increase the unfit proportion.
  • one or both threshold values are reduced in order to reduce the unfit portion, and if the unfit -Proportion is too low, one or both threshold values are increased in order to increase the unfit proportion.
  • an original unfit function can be used, which was determined, for example, in advance of the value document check or was automatically selected. Based on this original unfit function, the unfit function is changed when the simulation is repeated.
  • the unfit function clearly assigns a degree of unfit to each fitness measurement value.
  • the degree of unfit of the respectively selected fitness criterion is determined by inserting the respective measured fitness value of the respective value document into the unfit function of the respectively selected fitness criterion.
  • the respective unfit function is a rule by means of which a degree of unfit is assigned to the fitness measurement values that the value documents have in relation to the respective fitness criterion.
  • an individual unfit function is used for each fitness criterion. The degree of unfit is therefore specific to the respective fitness criterion.
  • the respective fitness measurement value is classified neither clearly as fit nor as unfit.
  • the unfit function is therefore not a simple sorting threshold.
  • the uncertainty range is limited by a first and a second threshold value. In the uncertainty range between the first and second threshold value, it assumes either a monotonically decreasing or a monotonically increasing, in particular linear or non-linear, course.
  • the unfit function assigns a degree of unfit that is greater than 0 and less than 1 to the measured fitness values in the uncertainty range. It assigns a degree of unfit of 0 to all fitness measurements lying beyond the first threshold value (i.e. those lying on the side of the first threshold value facing away from the uncertainty region) and all fitness measurements values lying beyond the second threshold value (i.e.
  • the unfit function assigns a fitness criterion-specific unfit degree of 1 to all those fitness measured values that are above the second (upper) threshold value, and a fitness criterion-specific unfit degree of 1, and to all those fitness measured values that are below the first (lower) threshold value Fitness criterion-specific unfit degree from 0 to.
  • the unfit functions of the selected fitness criteria differ from one another, in particular with regard to the position of the first and / or the second threshold value. However, you can also differentiate between the first and second threshold values with regard to the course of the unfit functions.
  • the same unfit function is used for all documents of value of a stack of documents of value to be checked for fitness to determine the degree of unfit of the respective fitness criterion.
  • the unfit probability of the respective value document determined by combining the unfit degrees provides a quantitative measure of the overall condition of the respective value document.
  • the unfit probability can also be determined by combining the unfit degrees of more than two different fitness criteria.
  • the unfit probability of the respective value document can be determined on the basis of the unfit degrees of at least five, preferably of at least 10, different fitness criteria.
  • At least one unfit grade can also flow into the combination of the unfit grade, which was obtained for a fitness criterion with the hitherto customary sharp distinction between fit and unfit (without uncertainty range), ie a fitness criterion for which either an unfit grade of 0 or a degree of unfit of 1, but no degrees of unfit between 0 and 1 are used, cf. Fig. 1 .
  • At least one of the fitness measurement values can be a combined fitness measurement value in which at least two different fitness measurement values are combined.
  • several ROIs can be defined on the bank note for a fitness criterion, the fitness measurement values of which are then combined into a single fitness measurement value.
  • At least one of the unfit degrees that is included in the unfit probability can be a group unfit degree that defines the fitness of the value document in relation to at least two different fitness criteria, the group unfit degree being determined with the aid of an unfit function that was set up for the combined fitness measurement value.
  • a first group unfit degree is determined for a first group of (at least two) fitness criteria, each relating to the soiling of the document of value, and a second group unfit degree is determined for a second group of (at least two) fitness criteria, each with the Affect damage to the value document.
  • a third group unfit degree is also formed for a third group of fitness criteria, for example for the wear and tear of the document of value or the limpness.
  • the unfit probability of the respective document of value is then determined by combining the first group unfit degree, which relates to the damage, with the second group unfit degree, which relates to the contamination of the banknote, and possibly with further unfit degrees, in particular further group unfit degrees.
  • the group unfit grades have the advantage that they reduce the number of fitness criteria and thus also reduce the complexity of the fitness test. The fine adjustment of the fitness test is therefore simplified for the user of the device.
  • the unfit probability determined for the document of value is compared, for example, with a single fitness threshold, the document of value being classified as unfit when the fitness threshold is exceeded and otherwise as fit.
  • the fitness classes fit and / or unfit can each also be divided into other fitness classes be divided, for example, the fitness class fit can be divided into the two fitness classes fit and ATM-fit.
  • the fitness threshold can be changed in order to control the unfit portion of the stack of value documents to be checked.
  • the fitness threshold can be changed for a user of the value document processing device.
  • the severity of the fitness test with regard to all fitness criteria can easily be controlled by selecting a single threshold without having to adjust further adjustments or further thresholds.
  • the unfit portion of the stack of value documents to be checked can be changed in this way easily.
  • a pre-calculation can be carried out in which the expected unfit portion of the respective value document group is determined for different values of the fitness threshold and the dependency of the unfit portion on the value of the Fitness threshold is determined.
  • This information can be communicated to the user, e.g. output at a user interface of the value document processing device.
  • the dependency of the unfit portion on the value of the fitness threshold can be shown as a look-up table. The user can then select the fitness threshold with which the unfit portion he wants is achieved in the fitness test.
  • Information about the general quality of the processed value documents can also be output at the user interface.
  • the control of the unfit portion can also be carried out from a central point which compares the unfit portions of several value document processing devices with one another and, in order to adjust them, accordingly changed fitness thresholds on these Adjusts value document processing devices. This can be carried out by remote access from the central point to the value document processing devices (for example connected in the network).
  • a further, lower fitness threshold is used for the ATM-fit fitness class, with which the unfit probability of the respective value document is compared. If the unfit probability is also below this further fitness threshold, the value document is classified as ATM-fit. If the unfit probability is below the (previously mentioned) fitness threshold but above this further fitness threshold, the value document is classified as fit. If the unfit probability is above the (previously mentioned) fitness threshold, the value document is classified as unfit.
  • the decision between the ATM-fit fitness class and the fit fitness class can also be proceeded in the same way as for the decision between the fit fitness class and the unfit fitness class described above.
  • an ATM-fit degree is used - analogously to the unfit degree - and for this - analogously to the unfit function - an ATM-fit function is set up, likewise with two threshold values and an uncertainty range in between, in which the ATM-fit -Function monotonically decreases or increases.
  • the ATM-fit grade is 0, for fitness measurements above a second threshold value, the ATM-fit grade is 1, and in the uncertainty range the ATM-fit grade is between 0 and 1.
  • the same or different fitness criteria can be selected. If one considers the same fitness criterion, the two threshold values for the decision fit to ATM-fit are different from those for the decision fit to unfit, namely in such a way that higher fitness requirements are placed for the ATM-fit fitness class than for the fitness class fit. Depending on the fitness criterion, higher fitness requirements are met either by higher threshold values or by lower threshold values.
  • the ATM-fit grades of the fitness criteria selected for this decision are combined - analogously to the unfit probability - to an ATM-fit probability of the respective value document. In the fitness classification of the value document, it is then decided on the basis of the ATM-fit probability whether the respective value document is ATM-fit or not, for example by comparing it with an ATM-fit threshold.
  • a banknote processing machine 1 which has an input compartment 20 into which banknotes 10 to be processed can be inserted, for example banknotes that are to be separated into fit and unfit banknotes.
  • the bank notes 10 are transferred individually from a singler 25 to a transport system 30.
  • the transport system 30 transports the individual banknotes through the banknote processing machine, past a measuring device 41 into one or more output compartments 32, 34.
  • the banknotes of different fitness can be sorted into different output compartments.
  • the measuring device 41 contains one or more sensors, the measurement data of which allow conclusions to be drawn about the state of the respective bank note in order to be able to assess and classify the bank note as fit or unfit.
  • the sensors of the measuring device 41 can be, for example, one or more optical sensors with suitable light sources, the sensors detecting light reflected by the respective bank note or light transmitted through the respective bank note, e.g. B. Light of a certain wavelength or a certain wavelength range. Further sensors can check, for example, acoustic (for example ultrasound) and / or mechanical (for example thickness measurement) and / or thermal and / or magnetic and / or electrical properties of the respective bank note.
  • statements can be made as to whether the respective banknote is soiled or damaged, or whether it has foreign objects such as clips or adhesive strips that affect the fitness of the respective banknote.
  • an evaluation device 40 determines the fitness of the respective banknote, e.g. whether the respective banknote is a fit or an unfit banknote.
  • the evaluation device 40 has, for. B. on a microprocessor that executes software for fitness testing, which is stored in an associated memory.
  • gates 31 and 33 are activated in the transport system 30 in order, for example, to store fit banknotes in a first output compartment 32 and unfit banknotes in a second output compartment 34. Further switches or output compartments can be provided in the transport system 30 of the bank note processing machine 1 and are indicated by a continuation 35.
  • the user interface can be accessed directly or by remote control.
  • a fitness measurement value M of the banknote has usually been included compared to a single threshold value X.
  • This threshold value is selected such that, in the case of a fitness measurement value, it lies between the frequency distribution for fit banknotes and the frequency distribution for unfit banknotes, cf. Fig. 1a . If the fitness measured value of the banknote is above the respective threshold value X, the respective banknote is classified as unfit, otherwise as fit, cf. Figure 1b .
  • such a comparison has been carried out for each fitness criterion and, if one (or more) of the fitness measurement values M of the bank note exceeds its respective threshold value X, the respective bank note is classified as unfit.
  • Fig. 2a the same two frequency distributions are shown for a fitness measurement value M1 of a fitness criterion K1 as in FIG Fig. 1a , but now an upper threshold value X1 and a lower threshold value Y1 are used, which limit an uncertainty range U1 in which the bank notes are neither clearly classified as fit nor clearly as unfit.
  • a large fitness measurement value M1 speaks for the presence of an unfit bank note. If the measured fitness value M1 is above the upper threshold value Y1, the banknote is clearly classified as unfit (unfit grade 1) with regard to the respective fitness criterion K1, and below the lower threshold value X1 unequivocally as fit (unfit grade 0).
  • the unfit degree is between 0 and 1.
  • the value of this unfit degree depends on the course of the selected unfit function F1.
  • a linear, monotonically increasing course of the unfit function was used for the fitness criterion K1.
  • the non-linearity can be advantageous, for example, if the frequency curves run non-linearly in the overlap area of the two frequency distributions.
  • FIGs 3a-b an example of another fitness criterion K2 is shown, in which a low fitness measurement value M2 speaks for the presence of an unfit banknote.
  • the frequency distribution of the unfit banknotes is with relatively low fitness measurement values M2 compared to the frequency distribution of the fit banknotes.
  • an unfit function with the opposite course is also used, that is to say it drops monotonically from 1 to 0 in the uncertainty range U2. If the measured fitness value M2 is above the upper threshold value Y2, the banknote is clearly classified as fit (unfit grade 0) with regard to the fitness criterion K2 - and below the lower threshold value X2 clearly as unfit (unfit grade 1).
  • the unfit function assumes a non-linear course in the uncertainty area.
  • FIG. 5a-c three unfit functions F2, F2, F3 for three different fitness criteria are shown by way of example, which are characterized by the uncertainty ranges U1, U2, U3 and the threshold values X1, Y1, X2, Y2, X3, Y3.
  • Figure 5a shows the unfit function F1 for a fitness criterion relating to the damage to the bank note, the damaged area of the bank note being used here as the fitness measurement value.
  • Figure 5b shows the unfit function for a fitness criterion F2, which relates to the soiling of the bank note, the remission intensity of the bank note in one or more ROIs being used here as the fitness measurement value.
  • Figure 5c shows the unfit function F3 for a fitness criterion that relates to the limpness of the banknote, the ultrasound intensity transmitted through the banknote being used here as the fitness measurement value.
  • the damaged area is, for example, the sum of all damaged areas of the respective bank note (damage such as holes, cracks, dog-ears, etc.), as can be seen from an image recorded by an optical sensor Bank note produced with the help of known image processing methods.
  • the remission is measured, for example, in one or more spectral channels in one or more ROIs on the bank note, in which the contamination of the respective bank note is checked.
  • the limp is determined, for example, with the help of an ultrasonic transmission measurement.
  • the respective unfit grades G1, G2 and G3 are entered for these three banknotes A, B and C.
  • the bank note A is assigned an unfit grade G1 of 0.80 due to its damaged surface
  • the bank note B a unfit grade G1 of 0.40
  • the bank note C a unfit grade G1 of 0.
  • an unfit grade G2 of 0 is assigned to the banknote B a unfit grade G2 of 0.75 and the banknote C a unfit grade G2 of 1.
  • the banknote A has an unfit grade G3 of 0 due to its ultrasonic measured value, 7 assigned, the bank note B an unfit grade G3 of 0 and the bank note C a unfit grade G3 of 0.
  • several fitness measured values can also flow into the unfit grades G1, G2 and G3, e.g. several ROIs can be defined on the banknote for the contamination check, whose fitness measured values are then combined into a single fitness measured value, e.g. by adding up, possibly with different weighting, or multiply, if necessary with exponent k ⁇ 1.
  • the respective unfit degrees G1, G2, G3 are now combined to form an unfit probability P for each individual bank note.
  • This multiplication ensures that a bank note which has an unfit grade of 1 in at least one fitness criterion will receive an overall unfit probability of 100%, regardless of the unfit grade that this bank note has in the other fitness criteria.
  • a further fitness threshold T ' can be used for the fitness class ATM-fit, which is below the fitness threshold T, ie for the classification as ATM-fit the banknotes require an even lower unfit probability. For example, the unfit probability P is compared with the further fitness threshold T '.
  • an unfit probability P is determined for each of these documents of value.
  • This unfit probability P is compared with a fitness threshold T that applies to the overall condition of the value documents.
  • This fitness threshold T can be specified by the user or in advance of the value document check, e.g. during the adaptation or also by remote access from a central point. With a fixed fitness threshold, the number of banknotes whose unfit probability P exceeds this fitness threshold T then results in a corresponding unfit proportion, e.g. 20%.
  • the user uses the user interface 45 to enter a desired unfit portion for the bank notes to be classified as unfit, e.g. B. in percent, indicates. If, for example, not 20%, but only 10% of the banknotes of the banknote stack 10 are to be classified as unfit, then the fitness threshold T is changed in such a way that only 10% of the banknotes exceed the fitness threshold. In order to achieve this, based on the fitness threshold T 20 , which led to a 20% unfit share, the evaluation device would then set the fitness threshold T correspondingly higher, taking into account the frequency of the unfit probabilities in this banknote stack (T 10 ). If necessary, the bank notes of the bank note stack 10 can then be checked again - with the fitness threshold T 10 - and sorted according to their fitness.
  • a desired unfit portion for the bank notes to be classified as unfit e.g. B. in percent
  • the following procedure can be used: In the run-up to the fitness check of a stack of banknotes to be checked, the user selects a first group of banknotes that he classifies as fit, ie these banknotes have e.g. B. at most a slight soiling and / or damage that is not perceived as annoying, and a second group of banknotes that he classifies as unfit, ie these banknotes have abnormalities such as soiling, damage, Clips, tape, etc.
  • the user selects a configuration operating mode of the banknote processing machine 1 in which parameters for the fitness test can be set, in particular which fitness criteria are to be used for the fitness test and / or in which the unfit functions and their threshold values are defined or changed can be.
  • the user is requested, for example, to first insert the banknotes which he has classified as unfit into the input compartment 20.
  • the bank notes classified as unfit are individually detected by the singler 25 and transferred to the transport system 30.
  • the measuring device 41 or the sensor or sensors contained therein, determines measurement data representative of the respective bank note, which are transmitted to the evaluation device 40.
  • the user is requested to insert the banknotes classified as fit into the input compartment 20, which are then processed analogously to the fit banknotes.
  • the unfit and fit banknotes can also be placed together in the input compartment 20 in the operating mode for determining the threshold value (s) if they can be clearly separated from one another by the banknote processing machine 1, for example by means of a separation card placed between the unfit - and the fit banknotes is inserted.
  • the separation card is recognized by the control device 40 on the basis of the measurement data from the measuring device 41, so that the control device 40 can perform the separation between unfit and fit banknotes.
  • the parameters for the fitness test are then set on the basis of the frequency distributions of the fitness measurement values of the fit and unfit banknotes. This can be done manually by the user (operator, adapter, service person), but also automatically by the evaluation device the value document processing device.
  • the first threshold value is placed on a fitness measurement value in which the fit frequency is much greater than the unfit frequency (e.g. have at least a certain ratio, e.g. 5: 1 or 10: 1) and the second threshold value is set on a fitness measurement value, in which the fit frequency is much smaller than the unfit frequency frequency, e.g. have at least a certain ratio (e.g. 1: 5 or 1:10).
  • the uncertainty area then lies accordingly in the overlap area of the two frequency distributions.
  • the damaged area can be used as the fitness criterion K3 and the length of the crack of the respective bank note can be used as the fitness criterion K4.
  • the result of the linear combination provides the combined fitness measurement value MK.
  • FIG. 7a the distributions of the two fitness measured values M3 and M4 can be seen for a group of unfit banknotes, each represented by a black circle, and for a group of fit banknotes, each represented by a white circle.
  • a two-dimensional area “clear fit” is drawn in, in which the group unfit degree is 0, and a two-dimensional area “clear unfit”, in which the group unfit degree is 1.
  • Figure 7b it is shown how the group unfit degree G can be determined for the combined fitness measurement value MK, which was combined from the group of fitness measurement values M3 and M4.
  • an unfit function F according to the invention with two threshold values X, Y and an uncertainty range U in between is set up for the combined fitness measurement value MK.
  • the result is the group unfit degree G.
  • the unfit probability P of the respective banknote is then obtained by combining the group unfit degree G, which relates, for example, to the damage, with one or more other unfit degrees of individual fitness criteria and / or with one or more other groups - Unfit degrees, for example with a group unfit degree, which concerns the soiling of the bank note.
  • the combination of all unfit degrees takes place, for example, by multiplying these unfit degrees according to formula (1) or by linear combination.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Inspection Of Paper Currency And Valuable Securities (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Claims (15)

  1. Procédé de vérification de l'aptitude à l'emploi de documents de valeur (A, B, C), comprenant les étapes suivantes :
    - sélection d'au moins deux différents critères d'aptitude à l'emploi (K1, K2) des documents de valeur qui sont caractéristiques de l'état des documents de valeur,
    - vérification des documents de valeur par enregistrement de données de mesure des documents de valeur, cependant que, à partir des données de mesure enregistrées, pour chacun des critères d'aptitude à l'emploi sélectionnés, une valeur de mesure d'aptitude à l'emploi (M1, M2) est déterminée pour le document de valeur respectif,
    - détermination de respectivement un degré de non aptitude à l'emploi (G1, G2) pour chacun des critères d'aptitude à l'emploi (K1, K2) sélectionnés, à partir de la valeur respective de mesure d'aptitude à l'emploi du document de valeur (A, B, C) respectif à l'aide d'une fonction de non aptitude à l'emploi (F1, F2) qui, à chacune valeur de mesure d'aptitude à l'emploi (M1, M2) , affecte univoquement un degré de non aptitude à l'emploi (G1, G2), cependant que chaque fonction de non aptitude à l'emploi est caractérisée par une première valeur seuil (X1, X2) , une deuxième valeur seuil (Y1, Y2) et une marge d'incertitude (U1, U2) située entre la première et la deuxième valeur seuil dans laquelle la fonction respective de non aptitude à l'emploi a un tracé soit décroissant de façon monotone, soit croissant de façon monotone, et
    - combinaison des degrés de non aptitude à l'emploi (G1, G2) des différents critères d'aptitude à l'emploi (K1, K2) de manière à obtenir une probabilité de non aptitude à l'emploi (P) spécifique au document de valeur (A, B, C) respectif, et
    - classification d'aptitude à l'emploi du document de valeur respectif, sur la base de la probabilité de non aptitude à l'emploi (P) qui a été déterminée pour le document de valeur respectif.
  2. Procédé selon la revendication 1, caractérisé en ce que la fonction de non aptitude à l'emploi (F1, F2) affecte respectivement aux valeurs de mesure d'aptitude à l'emploi (M1, M2) se trouvant dans la marge d'incertitude un degré de non aptitude à l'emploi (G1, G2) supérieur à 0 et inférieur à 1, et adopte entre la première et la deuxième valeur seuil un tracé soit décroissant de façon monotone, soit croissant de façon monotone, par exemple linéaire ou non linéaire, cependant que la fonction de non aptitude à l'emploi affecte en particulier un degré de non aptitude à l'emploi de 0 à toutes les valeurs de mesure d'aptitude à l'emploi situées au-delà de la première valeur seuil, et affecte un degré de non aptitude à l'emploi de 1 à toutes les valeurs de mesure d'aptitude à l'emploi situées au-delà de la deuxième valeur seuil.
  3. Procédé selon une des revendications précédentes, caractérisé en ce que les critères d'aptitude à l'emploi (K1, K2) sélectionnés concernent une ou plusieurs des propriétés suivantes des documents de valeur: encrassement, usure, endommagement, corps étrangers ou flaccidité du document de valeur respectif, cependant que les critères d'aptitude à l'emploi sélectionnés concernent de préférence au moins deux différentes de ces propriétés.
  4. Procédé selon une des revendications précédentes, caractérisé en ce qu'au moins deux critères d'aptitude à l'emploi dans lesquels la répartition de fréquence des documents de valeur aptes à l'emploi et la répartition de fréquence des documents de valeur non aptes à l'emploi se chevauchent aussi peu que possible entre elles sont sélectionnés, cependant que les deux répartitions de fréquence présentent de préférence un chevauchement maximal de 30 %.
  5. Procédé selon une des revendications précédentes, caractérisé en ce que, lors de la combinaison des degrés de non aptitude à l'emploi (G1, G2, ...) des différents critères d'aptitude à l'emploi (K1, K2) pour l'obtention de la probabilité de non aptitude à l'emploi (P), une multiplication des degrés de non aptitude à l'emploi des différents critères d'aptitude à l'emploi est effectuée, en particulier que la probabilité de non aptitude à l'emploi (P) est déterminée à partir des degrés de non aptitude à l'emploi (G1, G2) selon la formule suivante : P = 1 − ∏ j 1 − G j k j = 1 − 1 − G 1 k 1 ⋅ 1 − G 2 k 2 ⋅ ...
    Figure imgb0005
  6. Procédé selon une des revendications précédentes, caractérisé en ce que, lors de la combinaison des degrés de non aptitude à l'emploi (G1, G2, ...) des différents critères d'aptitude à l'emploi pour la probabilité de non aptitude à l'emploi (P), une combinaison linéaire des degrés de non aptitude à l'emploi des différents critères d'aptitude à l'emploi est constituée, en particulier par addition des degrés de non aptitude à l'emploi (G1, G2, ...) des différents critères d'aptitude à l'emploi, éventuellement avec pondération différente des degrés de non aptitude à l'emploi.
  7. Procédé selon une des revendications précédentes, caractérisé en ce que, pour la classification d'aptitude à l'emploi du document de valeur respectif, la probabilité de non aptitude à l'emploi (P) déterminée pour le document de valeur est comparée avec un seuil d'aptitude à l'emploi (T), et que le document de valeur est classifié comme non apte à l'emploi dans le cas où la probabilité de non aptitude à l'emploi (P) reste en-dessous du seuil d'aptitude à l'emploi (T).
  8. Procédé selon une des revendications précédentes, caractérisé en ce que, lors de la classification d'aptitude à l'emploi des documents de valeur d'un groupe de documents de valeur à vérifier quant à leur aptitude à l'emploi, un calcul préalable est effectué, lors duquel, pour différentes valeurs du seuil d'aptitude à l'emploi (T), respectivement la proportion de non aptitude à l'emploi attendue parmi le groupe respectif de documents de valeur est déterminée, laquelle indique la proportion de documents de valeur qui, lors de la classification d'aptitude à l'emploi du groupe respectif de documents de valeur, sont classifiés comme non aptes à l'emploi, et des informations sur la façon dont la proportion de non aptitude à l'emploi dépend de la valeur du seuil d'aptitude à l'emploi (T) sont générées, cependant que ces informations sont communiquées en particulier à l'utilisateur d'un dispositif de traitement de documents de valeur qui effectue le procédé de vérification de l'aptitude à l'emploi, par exemple par sortie à une interface utilisateur du dispositif de traitement de documents de valeur.
  9. Procédé selon une des revendications précédentes, caractérisé en ce que, préalablement à la vérification de l'aptitude à l'emploi, les étapes suivantes sont effectuées :
    - mise à disposition d'un premier groupe de documents de valeur aptes à l'emploi et d'un deuxième groupe de documents de valeur non aptes à l'emploi, cependant que l'estimation des documents de valeur comme aptes à l'emploi ou non aptes à l'emploi a en particulier été effectuée par vérification manuelle par une personne ou par vérification des documents de valeur au moyen d'un système de mesure de référence,
    - vérification des documents de valeur aptes et des non aptes à l'emploi du premier et du deuxième groupe par enregistrement de données de mesure de ces documents de valeur à l'aide d'un dispositif de mesure,
    - détermination d'au moins une valeur de mesure d'aptitude à l'emploi (M1, M2) pour chacun des documents de valeur à partir des données de mesure du document de valeur respectif,
    - détermination d'une première répartition de fréquence de la valeur respective de mesure d'aptitude à l'emploi pour le premier groupe des documents de valeur aptes à l'emploi et d'une deuxième répartition de fréquence de la valeur respective de mesure d'aptitude à l'emploi pour le deuxième groupe des documents de valeur non aptes à l'emploi,
    - utilisation de la première et de la deuxième répartition de fréquence de la valeur respective de mesure d'aptitude à l'emploi (M1, M2) afin de sélectionner les critères d'aptitude à l'emploi (K1, K2) à utiliser lors de la vérification de l'aptitude à l'emploi des documents de valeur et/ou afin de déterminer la fonction de non aptitude à l'emploi (U1, U2) du critère respectif d'aptitude à l'emploi (K1, K2) .
  10. Procédé selon une des revendications précédentes, caractérisé en ce que, pour les documents de valeur d'au moins un groupe de documents de valeur à vérifier quant à leur aptitude à l'emploi, en fonction de la classification d'aptitude à l'emploi des documents de valeur du groupe de documents de valeur, les étapes suivantes sont effectuées :
    - établissement de la proportion de non aptitude à l'emploi parmi le groupe de documents de valeur, laquelle indique la proportion de documents de valeur qui, lors de la classification d'aptitude à l'emploi du groupe de documents de valeur, sont classifiés comme non aptes à l'emploi,
    - vérification de la proportion de non aptitude à l'emploi quant à au moins une exigence déterminée pour la proportion de non aptitude à l'emploi,
    - modification de la fonction de non aptitude à l'emploi (U1, U2) d'un ou de plusieurs des critères d'aptitude à l'emploi (K1, K2) utilisés, en fonction de la proportion établie de non aptitude à l'emploi du groupe de documents de valeur, cependant que, dans le cas où la proportion établie de non aptitude à l'emploi satisfait à l'exigence déterminée, la fonction de non aptitude à l'emploi est laissée inchangée, et, dans le cas où la proportion de non aptitude à l'emploi ne satisfait pas à l'exigence déterminée, la fonction de non aptitude à l'emploi est changée et les étapes suivantes de a) à f) sont effectuées dans le cadre d'une simulation en utilisant la fonction de non aptitude à l'emploi changée :
    a) nouvelle détermination des degrés de non aptitude à l'emploi (G1, G2) du document de valeur respectif pour les au moins deux différents critères d'aptitude à l'emploi (K1, K2) à partir de la valeur respective de mesure d'aptitude à l'emploi en utilisant la fonction de non aptitude à l'emploi changée du critère respectif d'aptitude à l'emploi,
    b) nouvelle combinaison des degrés de non aptitude à l'emploi des différents critères d'aptitude à l'emploi de manière à obtenir une probabilité de non aptitude à l'emploi (P) du document de valeur respectif, et
    c) nouvelle classification d'aptitude à l'emploi du document de valeur respectif à l'aide de la probabilité respective de non aptitude à l'emploi (P) ,
    d) nouvel établissement de la proportion de non aptitude à l'emploi parmi un ou plusieurs groupes de documents de valeur, laquelle indique la proportion de documents de valeur qui, lors de la classification d'aptitude à l'emploi du groupe respectif de documents de valeur, sont classifiés comme non aptes à l'emploi,
    e) nouvelle vérification de la proportion de non aptitude à l'emploi quant à l'exigence déterminée,
    f) nouvelle modification de la fonction de non aptitude à l'emploi d'un ou de plusieurs des critères d'aptitude à l'emploi utilisés, en fonction de la proportion établie de non aptitude à l'emploi du groupe de documents de valeur, cependant que, dans le cas où la proportion déterminée de non aptitude à l'emploi satisfait à l'exigence déterminée, la fonction de non aptitude à l'emploi est laissée inchangée, et, dans le cas où la proportion déterminée de non aptitude à l'emploi ne satisfait pas à l'exigence déterminée, la fonction de non aptitude à l'emploi est changée et les étapes suivantes de a) à f) sont répétées dans le cadre de la simulation.
  11. Procédé selon la revendication 10, caractérisé en ce que, dès que la proportion de non aptitude à l'emploi satisfait à l'exigence déterminée, la fonction de non aptitude à l'emploi est laissée inchangée et la classification d'aptitude à l'emploi (étape c) effectuée en dernier lieu est utilisée comme classification définitive d'aptitude à l'emploi et/ou que, alors, la fonction de non aptitude à l'emploi utilisée en dernier lieu (pour la classification d'aptitude à l'emploi à l'étape c) est utilisée pour la classification future d'aptitude à l'emploi d'autres groupes de documents de valeur, en particulier pour d'autres groupes de documents de valeur de la même sorte de documents de valeur.
  12. Procédé selon une des revendications de 10 à 11, caractérisé en ce que, lors de la modification de la fonction de non aptitude à l'emploi (U1, U2) du critère respectif d'aptitude à l'emploi (K1, K2), la fonction de non aptitude à l'emploi de ce critère d'aptitude à l'emploi est changée de telle manière en fonction de la proportion de non aptitude à l'emploi du groupe de documents de valeur que la proportion de non aptitude à l'emploi est, lors de la nouvelle classification d'aptitude à l'emploi, changée en comparaison avec la proportion de non aptitude à l'emploi établie en dernier lieu, par exemple augmentée ou diminuée, cependant que les étapes de a) à f) selon la revendication 10 sont en particulier répétées jusqu'à ce que la proportion de non aptitude à l'emploi nouvellement établie corresponde au moins approximativement à la proportion de non aptitude à l'emploi auparavant constatée pour ce groupe de documents de valeur lors d'une vérification manuelle d'aptitude à l'emploi ou lors d'une vérification automatique d'aptitude à l'emploi à l'aide d'un dispositif de traitement de documents de valeur.
  13. Procédé selon une des revendications précédentes, caractérisé en ce qu'au moins une des valeurs de mesure d'aptitude à l'emploi (M1, M2) est une valeur de rassemblement de mesure d'aptitude à l'emploi (MK) dans laquelle au moins deux différentes valeurs de mesure d'aptitude à l'emploi (M3, M4) sont rassemblées, p.ex. par combinaison linéaire de ces valeurs de mesure d'aptitude à l'emploi (M1, M2), et qu'au moins un des degrés de non aptitude à l'emploi (G1, G2) est un degré de non aptitude à l'emploi de groupe (G) indiquant l'aptitude à l'emploi du document de valeur respectif quant à au moins deux différents critères d'aptitude à l'emploi, cependant que le degré de non aptitude à l'emploi de groupe (G) est déterminé à l'aide d'une fonction de non aptitude à l'emploi (F) qui a été introduite pour la valeur de rassemblement de mesure d'aptitude à l'emploi (MK) .
  14. Procédé selon la revendication 13, caractérisé en ce que, pour les documents de valeur, respectivement un premier degré de non aptitude à l'emploi de groupe (G) est déterminé pour un premier groupe d'au moins deux critères d'aptitude à l'emploi qui concernent respectivement l'encrassement du document de valeur respectif, et un deuxième degré de non aptitude à l'emploi de groupe est déterminé pour un deuxième groupe d'au moins deux critères d'aptitude à l'emploi qui concernent respectivement l'endommagement du document de valeur respectif, cependant que la probabilité de non aptitude à l'emploi (P) du document de valeur respectif est en particulier déterminée par la combinaison du premier degré de non aptitude à l'emploi de groupe (G), concernant l'endommagement, et du deuxième degré de non aptitude à l'emploi de groupe, concernant l'encrassement du billet de banque, et éventuellement d'un ou de plusieurs autres degrés de non aptitude à l'emploi et/ou degrés de non aptitude à l'emploi de groupe.
  15. Dispositif de vérification de l'aptitude à l'emploi de documents de valeur (A, B, C) par le procédé selon une des revendications précédentes, comprenant :
    - un dispositif de mesure (41) pour l'enregistrement de données de mesure des documents de valeur, et
    - un dispositif d'évaluation (40) pour la classification d'aptitude à l'emploi des documents de valeur sur la base des données enregistrées,
    caractérisé en ce que le dispositif d'évaluation est conçu pour
    - sélectionner au moins deux différents critères d'aptitude à l'emploi (K1, K2) des documents de valeur qui sont caractéristiques de l'état des documents de valeur,
    - à partir des données de mesure enregistrées, pour chacun des critères d'aptitude à l'emploi sélectionnés, déterminer une valeur de mesure d'aptitude à l'emploi (M1, M2) pour le document de valeur respectif,
    - pour chacun des critères d'aptitude à l'emploi sélectionnés à partir de la valeur respective de mesure d'aptitude à l'emploi du document de valeur respectif, déterminer à l'aide d'une fonction de non aptitude à l'emploi (F1, F2) respectivement un degré de non aptitude à l'emploi (G1, G2), cependant que la fonction de non aptitude à l'emploi (F1, F2) affecte univoquement à chaque valeur de mesure d'aptitude à l'emploi (M1, M2) un degré de non aptitude à l'emploi (G1, G2), et cependant que chaque fonction de non aptitude à l'emploi est caractérisée par une première valeur seuil (X1, X2), une deuxième valeur seuil (Y1, Y2) et une marge d'incertitude (U1, U2) située entre la première et la deuxième valeur seuil, dans laquelle la fonction respective de non aptitude à l'emploi a un tracé soit décroissant de façon monotone, soit croissant de façon monotone, et
    - combiner les degrés de non aptitude à l'emploi (G1, G2) des différents critères d'aptitude à l'emploi (K1, K2) du document de valeur respectif de manière à obtenir une probabilité de non aptitude à l'emploi (P) qui est spécifique au document de valeur (A, B, C) respectif, et
    - effectuer une classification d'aptitude à l'emploi du document de valeur (A, B, C) respectif, sur la base de la probabilité de non aptitude à l'emploi (P) qui a été déterminée pour le document de valeur respectif.
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RU2017104706A3 (fr) 2018-11-01
EP3170154A1 (fr) 2017-05-24
CN106663348A (zh) 2017-05-10
US20170161981A1 (en) 2017-06-08
CN106663348B (zh) 2020-07-28
RU2673998C2 (ru) 2018-12-03
WO2016015829A1 (fr) 2016-02-04
DE102014010466A1 (de) 2016-01-21
ES2900855T3 (es) 2022-03-18

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