WO2011082792A1 - Procédé pour vérifier des documents de valeur - Google Patents

Procédé pour vérifier des documents de valeur Download PDF

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Publication number
WO2011082792A1
WO2011082792A1 PCT/EP2010/007687 EP2010007687W WO2011082792A1 WO 2011082792 A1 WO2011082792 A1 WO 2011082792A1 EP 2010007687 W EP2010007687 W EP 2010007687W WO 2011082792 A1 WO2011082792 A1 WO 2011082792A1
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WIPO (PCT)
Prior art keywords
value
determined
value documents
classes
data
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PCT/EP2010/007687
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German (de)
English (en)
Inventor
Shanchuan Su
Dieter Stein
Original Assignee
Giesecke & Devrient Gmbh
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Publication date
Application filed by Giesecke & Devrient Gmbh filed Critical Giesecke & Devrient Gmbh
Publication of WO2011082792A1 publication Critical patent/WO2011082792A1/fr

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Classifications

    • 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
    • G07D7/06—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 using wave or particle radiation
    • G07D7/12—Visible light, infrared or ultraviolet radiation
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D11/00—Devices accepting coins; Devices accepting, dispensing, sorting or counting valuable papers
    • G07D11/50—Sorting or counting valuable papers

Definitions

  • the present invention relates to a method for checking value documents and a method for providing data for the examination method.
  • value documents are understood card and preferably sheet-shaped objects that represent, for example, a monetary value or an authorization and therefore should not be arbitrarily produced by unauthorized persons. They therefore have features which are not easy to manufacture, in particular to be copied, whose presence is an indication of the authenticity, i. the manufacture by an authorized agency.
  • Important examples of such value documents are chip cards, coupons, vouchers, checks and in particular banknotes.
  • Value documents must be checked to see if they are genuine. As counterfeit documents become better and better over time, it is necessary to continue to improve the authenticity of value documents.
  • banknotes can be so badly damaged or soiled by heavy and / or careless use that they are no longer usable. This condition of banknotes is often called "unfit for circulation.” Banknotes are therefore also checked for their condition in order to withdraw out-of-circulation banknotes and, if necessary, replace them with new ones. Here, too, the demands on the quality of the condition test increase.
  • the present invention is therefore based on the object of specifying a method for checking value documents, which allows a precise examination of value documents
  • the object is achieved by a method for checking value documents of the same predetermined type in which property data are determined for one of the value documents which describe predefined properties of the value document for which a value class document determines a class from a number n of classes specified for value documents of the specified type is, where n is greater than 1 and the classes are specified so that each value documents are assigned to them, which were produced in the same production batches, and for testing the value document at least depending on the determined class a predetermined criterion that the Property data or processing data determined from these concerns, checked and a signal describing the result of the test is formed.
  • Value documents of the same predetermined type are understood to mean value documents which are considered to be of the same type in relation to the criterion used for the test.
  • Value documents of the same predetermined type are, in particular, value documents which have predefined properties which must lie within tolerances specified for the respective type. In principle, they can have other properties in which they differ more.
  • banknotes of the same predetermined type may have predetermined picture elements that are characteristic of that type. If features determined only from the recorded property data are used for the check, for example for the checking of the quality, then all value documents which have these features in a predetermined tolerance range can be considered to be of the same type.
  • the value documents of the same predetermined type can be banknotes of the same currency and denomination.
  • the predetermined type may additionally be given by the fact that the banknotes in a given area have substantially the same properties, ie variable characteristics which are only given in one, for example by a central bank, permissible fluctuations.
  • the pressure on the banknotes can be the same except for predetermined areas.
  • property data in principle any data can be used which describe predetermined properties, in particular predetermined physical properties, of at least parts of a value document to be checked. This can be raw data from sensor elements or from these calculated data.
  • value documents of this same type each have a classification, i. perform an assignment to one of a number n of classes, in particular to one of at least two predetermined classes, or a determination of one of these classes for a respective value document, whereby value documents of the same type are distinguished.
  • the classes may be predetermined to reflect possible systematic deviations of the property data, so that property data of value documents of one of the classes will systematically differ from the property data of value documents of the other classes.
  • these property data are at least partially directly or indirectly included in the criterion used for the test.
  • the classes are specified in such a way that they are each assigned value documents are produced in equal production batches.
  • a batch is understood to mean value documents that are produced during the same production process.
  • Value documents from different batches can, for example, be distinguished by differences in the materials used therein, in particular for example the paper or printing inks, which are also produced in batches and not in continuous processes, and / or the means used in the production, for example the printing plates , and / or the manufacturing process parameters used in the manufacture.
  • the exact reasons for the occurrence of differences play no role in the context of the present invention.
  • a class only needs to comply with at least one production batch; however, value documents of the same type and of at least two different batches of a single class can also be assigned.
  • a predefined criterion relating to the property data or processing data determined therefrom is then checked to check the value document, at least as a function of the determined class, and a signal describing the result of the test is formed.
  • This approach is based on the idea that there can be systematic differences for value documents of the same given type, which on the one hand enable a division into classes and which, on the other hand, can express themselves in the property data.
  • a dependency of the property data on the determined class is therefore to be understood in particular that the value documents of this class have property data, in particular feature vectors, which differ systematically from those of value documents of other classes, but of the same type. Therefore, different criteria are used for testing value documents of the same type but different classes depending on the respective class.
  • the criteria may preferably differ only in parameters, but not in the sequence and nature of the test steps of the criteria.
  • the criteria are given by functions of the property or processing data and further parameters and by areas in which the values of the functions must lie for a positive result of the test, preferably only the parameters and / or the ranges are selected as class-dependent.
  • the parameters may in particular be given parameters describing reference data and permissible deviations from the reference data which are predetermined for the value documents of the specified type as a function of the class.
  • any data can be used to determine the class.
  • data may be used that describes other properties of the value document than the property data.
  • magnetic properties could be used to determine the class and optical properties to test the value document.
  • the determined property data are used to determine the class. This has the advantage that it is just the differences in the characteristic data that can be used for the classification which are compensated for the later testing.
  • feature vectors can be determined from the property data when the class is determined, and the feature vectors for the determination can be determined. class. Preferably, these feature vectors are also used in the later test.
  • Methods for determining the classes and for determining a method for determining one of the classes for a value document in the context of the present invention also referred to as classification of a value document, can in principle be determined arbitrarily.
  • the following method is used, which is also the subject of the present invention.
  • value documents of the same predetermined type and from different production batches are provided for which value documents are used to determine characteristic data which describe predetermined properties of the value documents by means of a sensor the property data determined by means of a data processing device values of predetermined feature vectors.
  • At least two classes are defined by means of the data processing unit, each of which is assigned value documents of the given type which are considered similar in relation to the values of the feature vectors according to the predetermined criterion, and the data processing device at least one classifier is defined, by means of which a value document of the given type can be assigned to one of the classes as a function of the property data determined for it, and thus a class can be determined for the value document.
  • a criterion for checking the value documents is then determined in each case, which relates to the resulting property data or processing data determined therefrom.
  • the classes thus defined can be defined as the predetermined classes for the method for testing documents of value of the same type, also referred to as test methods, can be used.
  • data for carrying out the test method data describing the classifier, ie the at least one classification function and its parameters, also referred to as classifier parameters in the context of the invention, and the data of the transformation, in particular a transformation function and its parameters , Understood.
  • the value documents of the same predetermined type are as defined above and in particular preferably banknotes of the same currency and denomination.
  • component analysis may be used in a space of feature vectors determined from the property data. The dependence of the feature vectors on the property data is the same as in the test method, if feature vectors are used in this case.
  • This method has the advantage of a very simple implementation.
  • a Karnene-Loeve transformation or a principal component analysis (PCA) can be used for this purpose.
  • a discriminant analysis in a space of feature vectors determined from the property data or in a subspace of the feature vectors for specifying the classes.
  • the advantage of this approach lies in the fact that a very good separation of the classes can be achieved.
  • one of the predetermined classes can be determined as desired.
  • a linear classifier is used as the classifier.
  • a classification function dependent on the property or feature vectors may be used with a functional form given by the linearity with respect to the feature vectors, for which in turn corresponding parameters defining the classifier are determined.
  • Such classifiers not only offer the advantage that they are easy to determine, but can also be evaluated quickly during the test.
  • the property data preferably describe spatially resolved optical properties of the value document, particularly preferably an image in reflection or transmission in different spectral ranges.
  • the property data describes a color image of the value document.
  • feature vectors they preferably describe color properties of given evaluation areas of the image.
  • the color properties are then preferably used, which does not mean the recognition of special shapes, for example letters or numbers.
  • the subject matter of the present invention is furthermore a device for processing value documents with at least one input compartment for receiving documents of value, a transport device for transporting isolated documents of value to at least one output compartment, one arranged on a transport path given by the transport device.
  • Sensor device with a Ausenseeiricardi for performing the test method, in particular the determination of the property data and a control device for controlling the transport device in response to signals of the evaluation.
  • the device can have at least two output compartments and the control device can be designed to control the transport device as a function of the signals of the evaluation device, so that the value documents in one of the compartments defined by the respective signal depend on the signals for tested value documents is to be transported.
  • the device preferably the evaluation device, preferably has a memory in which all data necessary for carrying out the method are stored.
  • the invention will be explained in more detail below by way of example with reference to the drawings. Show it:
  • FIG. 1 is a schematic representation of a bank note processing apparatus
  • FIG. 2a and b show a schematic representation of an optical sensor of the bank note processing device in FIG. 1 in the transport direction and from above onto a transport plane
  • FIG. 3 shows a schematic representation of an example of a value document to be examined in the form of a banknote
  • 4 is a simplified process flow diagram for a method for checking documents of value which can be carried out in the batch processing apparatus in FIG. 1
  • FIG. 5 is a simplified flow chart for a method for determining data for the method for checking documents of value in FIG 4.
  • the apparatus 10 has an input tray 14 for input of value documents 12 to be processed, a separator 16, which can access value documents 12 in the input tray 14, a transport device 18 with points 20 and 20 'arranged successively along a transport path 22, and after Each of the points or an end of the transport path 22 following the two points respectively has an output pocket 26 or 26 'or 26''along the transport path 22 given by the transport device 18
  • Sensor arrangement 24 is arranged, which serves for the detection of characteristics of individually supplied value documents 12 and the formation of sensor properties representing a characteristic.
  • a control device 30 is connected at least to sensor arrangement 24 and switches 20 and 20 'via signal connections and serves for the evaluation of sensor signals of sensor arrangement 24 and control of at least the switches 20 u nd 20 'depending on the result of the evaluation of the sensor signals.
  • the sensor arrangement 24 comprises at least one sensor for this purpose; In this embodiment, only one optical sensor 32 is provided for the spatially resolved detection of color properties, which detects the optical document remitted from the value document. In other embodiments, further sensors may be provided, for example for other than optical properties.
  • the sensor 32 captures an image of the value document in three spectral regions corresponding to the three color channels red, green and blue represented by corresponding sensor signals.
  • control device 30 From the analog and / or digital sensor signals of the sensor 32, characteristic data are determined by the control device 30 during a sensor signal evaluation, which are relevant for checking the bank notes with respect to their condition and / or authenticity.
  • the control device 30 has an evaluation device 31, which is integrated in the example in the control device 30, but in other embodiments, but also part of the sensor assembly 24, preferably the sensor 32 may be.
  • the state of a value document is regarded in particular as the state of fitness or fitness for circulation, ie the suitability to continue to be used as a means of payment.
  • predetermined criteria are used. In this example, these relate in particular to the presence of soiling and / or color abrasions or stains as well as the presence of cracks, dog-ears and / or holes, and / or the absence of components of the value documents .
  • the control device 30 has a corresponding chenden interface for the sensor 32 via a processor 34 and connected to the processor 34 memory 36 in which at least one computer program is stored with program code, in the execution of the processor 34 in a first function as the evaluation device 31, the sensor signals, in particular for determining the Authenticity and / or a total state of a checked value document, evaluates and controls the device in a second function or corresponding to the evaluation, the Trarisport worn 18 controls.
  • the control device 30 further has a data interface 37.
  • the control device 30 can be operated in at least two operating modes. In a first operating mode, the working mode, it controls the device for checking value documents. In a second mode, the detection mode, it controls the device so that value documents from the input tray are separated and occasionally transported past the sensor 32. Thereafter, the value documents are again output in a predetermined one of the output compartments 26, 26 'or 26 ", whereby the sensor 32 detects the properties of the value documents which have been conveyed past the sensor and which are connected to the sensor 32 via a signal or data connection Controller 30 detects property data sensed by sensor 32 and provides it to each of the value documents via data interface 37.
  • the data interface includes means for describing data carriers, such as CDs, that may be read by a suitable data processing device.
  • the evaluation device 31 In the working mode, the evaluation device 31, more precisely the processor 34 therein, after determining property data, a predetermined Check the authenticity of the value document, which includes at least some of the recorded properties and reference data.
  • the evaluation device 31 can check a criterion for the overall state of the value document into which the property data are received or which depends on them.
  • further reference data for establishing a still permissible state of the value document which are predefined and stored in the memory 36, can enter into the criterion.
  • the overall state can be given for example by two categories "still fit for use” or “marketable” or “to be destroyed”.
  • control device 30 controls the transport device 18, more precisely the switches, in such a way that the checked value document is transported for storage to corresponding output compartments in accordance with its determined overall state.
  • For processing documents of value 12 are separated into the input tray 14 as a stack or individually inserted value documents 12 of the verzier 16 and occasionally fed to the transport device 18, which supplies the isolated value documents 12 of the sensor assembly 24.
  • This captures optical properties of the value documents 12, in the example a color image, whereby sensor signals are formed which represent the corresponding properties of the value document.
  • the control device 30 detects the sensor signals, determines in dependence thereon a state and the authenticity of the respective value document and, depending on the result, controls the points so that the examined value documents are fed to the output compartments in accordance with their ascertained state and authenticity.
  • the sensor 32 is formed as a line sensor which, during the advance of a value document past the sensor 32, comprises a sequence of line images which give an image of the value document in a direction transverse to the direction of the line. It comprises in the present example, in FIGS.
  • a lighting device 38 in the example with two light sources, for illuminating at least a portion of a value document 12 with white light during its Vortechnikransport over its entire extent transverse to the transport direction T and detection device 40 in the example, three line scan 42, 42 'and 42 "with not shown, arranged in the beam path in front of these red, green and blue filters for detecting red, green or blue portions of the remitted from the value document light
  • Each of the line scan cameras has a respective detector row with photodetection elements arranged in a row in front of which in each case the filter is arranged which corresponds to the color component of the remitted light to be detected by the respective line scan camera. in particular to the Abbil tion or focusing, which are not shown here.
  • the detector lines of photodetection elements are arranged parallel to each other.
  • An image captured by the sensor 32 is therefore composed of pixels arranged in a rectangular matrix. It is described by property data in the form of image data. In the illustration of the image of a value document 12 in FIG. 3, only some of the pixels 44 are shown for the sake of clarity. Each of the pixels is assigned as property data next to a number i representing the position in the image, color values n, gi, bi for red, green and blue.
  • a criterion which is predetermined for a respective type of value documents, for a sufficiently good state or the presence of a value document to be regarded as genuine, which depends on the above-mentioned vector.
  • An examination of the criterion can thus consist in calculating the value of the test function K for a given vector V and comparing it with a predetermined value G.
  • a program is stored in the memory 36 in a section serving as part of the evaluation device 31 and thus in this example in the control device 30, which executes the following steps of a method for checking value documents when executed by the processor 34.
  • all the data necessary for carrying out the method are stored in the memory 36.
  • the evaluation device 31 determines in a step S10 in a property data item to be checked for the value document to be tested, which describe predefined properties of the value documents.
  • the sensor 32 captures images of
  • Value documents more precisely the image or image data representing images, in the example full-surface images with three color channels, namely red, green and blue (RGB channels);
  • the type of image data has already been described above.
  • the property data thus indicate optical properties of the value document as a function of the location on the value document.
  • the property or image data are transmitted to the evaluation device 31 and detected by this. Depending on the type of sensor, preprocessing of the detected data in the sensor 32 or the ejection may be performed in this step. teairiliens 31 are performed, in which the image data to be transformed, for example, to compensate for background noise.
  • the evaluation device 31 determines the type of a value document to be checked in step S12 as a function of the property data detected by the sensor 32.
  • value documents are checked in the form of euro banknotes.
  • the evaluation device 31 can therefore first perform a search or recognition of edges of the banknote in the image. From the recognized borders, it can determine the format of the value document and, in the example of value documents in the form of euro banknotes, the denomination and thus the type from the set of predefined possible value document types.
  • step S14 using the property data for the value document of the determined type to be checked, it obtains a class from a number n of classes given for value documents of the predetermined type, where n is a number greater than 1.
  • the evaluation device 31 positions predetermined regions of interest (ROI) in the image, which are the known position of given regions on the value documents of the given type relative to the outlines of the value documents and an outline determined in the image of the value document.
  • ROI regions of interest
  • the evaluation device can in particular firstly search or detect edges of the banknote in the image or access the results of step S12, in order then to position the ROI in the image, depending on the position of the edges in the image, ie to select appropriate property values. For example, twenty-four evaluation areas can be selected for a 10 Euro banknote.
  • Fig. 3 For illustration purposes, an evaluation area 46 emphasized by hatching and comprising nine pixels 44 is shown.
  • feature vectors are determined from the property data, which represent color properties of the evaluation areas; In determining the classes, the feature vectors, and in particular those color properties, are used, i. the classification is done depending on the color properties.
  • the evaluation device 31 determines from the property data for each of the evaluation areas at least one value assigned to the respective evaluation area, which is referred to below as a feature value.
  • three feature values are determined, a feature value for each of the color channels. For example, like the evaluation area 46, nine adjacent pixels arranged in a given rectangle can have as a property value for each of the color channels, for example, the average over the 10 pixel values of the corresponding color channel be calculated.
  • the feature values for a banknote are referred to as the feature vector X of the banknote.
  • the evaluation device 31 depending on their training, perform a transformation of the property values or the feature vector into another color space, for example a device-independent color space, in particular a CIE-Lab color space.
  • the actual classification of the value document takes place by means of a predetermined classifier.
  • a classifier is used, which is determined by the method described below for determining data for the present test method.
  • step S22 the evaluation device 31 checks the predetermined criterion for checking the value document, which relates to the transformed property data or processing data and depends on the determined class or is specified for value documents of this class. It then forms a signal describing the result of the test.
  • the two aforementioned criteria are checked, one for the state of the value document and further for the authenticity of the value document, and respectively corresponding signals are formed.
  • the control device then activates the trapping device.
  • step T10 value documents of the same type are provided, in the example banknotes of the same currency and denomination, but from different production batches.
  • step T12 images of the value documents, more specifically the image representative property data are detected by the sensor 32.
  • step S10 a sub-step corresponding to step S10 is performed for each of the predetermined value documents of the same type.
  • the detected property data are transmitted via the data interface 37 to an external data processing device with a corresponding interface, which takes over the further processing of the data. The following steps are performed by the external data processing device.
  • the data processing device carries out the following positioning of predetermined evaluation ranges for each of the value documents and stores corresponding data for the respective value document. More specifically, the data processing device positions predetermined regions of interest (ROI) corresponding to the evaluation areas in step S16 in the image consisting of the known location of predetermined areas on the value documents of the given type relative to the outlines of the value documents and one in the image determined outline of the value document.
  • ROI regions of interest
  • the data processing device can in particular first perform a search or recognition of edges of the banknote in the image according to the procedure for edge detection in step S12, and then depending on the position of the edges in the image to position the ROI in the image, ie corresponding Select property values.
  • evaluation areas For example, for a 10-euro banknote 12, twenty-four evaluation areas can be selected. Preferably, these are chosen so that they are also tested for authenticity and / or for testing. Stand test can be used. In the example, one of the evaluation areas is area 46 in FIG. 2.
  • step T16 the data processing device determines for each of the value documents from the property data for each of the evaluation areas at least one feature value assigned to the respective evaluation area.
  • the determination of the feature values for each of the value documents takes place as in step S18. From the feature values, as in the test method, a feature vector X is formed for each of the value documents.
  • the data processing device can carry out a transformation of the property values or of the feature vector into another color space, for example a device-independent color space, in particular a CIE-Lab color space. Such a transformation must then also be carried out in the test procedure.
  • the data processing device searches classes depending on the determined values of the feature vectors for the value documents which are respectively associated with value documents relating to the property data or in the example of the processing data determined therefrom in the form of the values of the feature vectors criterion does not differ significantly from one another, ie it sets corresponding classes.
  • the evaluation device determines clusters or clusters of the feature vectors in a corresponding space, which are separated from each other according to at least one predetermined criterion. Each of these clusters corresponds to a class. It has been shown that the classes distinguished the origin! .- can reproduce chen production batches, if they differ sufficiently in their properties.
  • a class or an accumulation banknotes can correspond to several production batches, but it is also possible that one class is assigned to only one production batch.
  • PCA Principal Component Analysis
  • KL transformation Karhunen Loeve transformation
  • at least two, in the example, four main components are determined, by means of which the largest parts of the scattering of the feature vectors can be represented.
  • Clusters are then determined in the subspace formed by these main components.
  • the criterion for the presence of two different clusters is that the distance of the mean vectors for two different clusters must be greater than the sum of the values determined by the difference between the mean vectors. decorated covariances of the feature vectors of the clusters.
  • step T22 the data processing device sets for the accumulations or classes found at least one classifier, ie a classification function and classifier parameters for them, by means of which a value document of the predetermined type can be assigned to one of the classes.
  • This at least one classifier, ie the corresponding classification function is the classifier used in step S20, with the function used in step S20.
  • the data processing device determines the classifier parameter values for the classifier or the predefined classification function, by means of which a value document of the predetermined type, in the example of a banknote of the specified type, for the data corresponding to the steps T12 to T16 or T18 is detected and supplied Property values or feature vectors were processed, depending on the property values for one of the clusters or a ner of the determined classes can be assigned.
  • a reduction of the property values or feature vectors to a subspace in which the separable accumulations are easily recognizable can take place in this step.
  • the average vector of the accumulation and covariance data, in particular in the subspace, and threshold values for the maximum distance from the mean vector according to FIG an optionally dependent on the covariance data distance measure, in the example, a Euclidean distance are determined.
  • the classification in step S20 first the projection of the feature vector X on the subspace is determined. Then, for each of the classes, the distance of the projection from the mean value vector of the class in the subspace is determined and compared with the maximum distance for the respective class. The class is assigned to the class for which the distance is smaller than the respective maximum value. If there are several such classes, the one with the distance is the smallest. If no distance is determined for any of the classes that is less than the maximum distance for the class, the classification is aborted with an error message. In the example, n classes were determined.
  • step T24 the data processing device determines for each of the classes a criterion for checking the value documents, in this example one for authentication and one for checking the state.
  • criteria function or at least one of the arithmetic and / or comparison operations continue to input the property or processing data as a variable.
  • the criterion function or the at least one of the arithmetic and / or comparison operations for the authenticity check depends on the processing data, more precisely the feature vectors, while the criterion function or the at least one of the computational and / or comparison operations for the health check depends on the Property data depends
  • the defined criteria parameter values and the data describing the criterion function or the sequence of arithmetic and / or comparison operations are then stored and can be transmitted to the evaluation device 31.
  • step T20 after determining a predetermined number of the main main components, in the example four main components, and corresponding unit vectors in a subspace spanned by the main components, a linear discrete error analysis is performed on the basis of the projections of the feature vectors into the subspace.
  • a Fisher discriminant analysis can be carried out. Depending on the available data, this can result in improved separation of clusters.
  • a linear classifier is used in step T22 and thus a function that is a linear function of the feature vectors.
  • Each component of the vector g (X) therefore corresponds to one of the given classes.
  • the linear classifier is given by the rule that the feature vector X is assigned to that class whose component of the vector g (X) is greater than all other components.
  • the vector B and the matrix A are determined as the classifier parameters.
  • step S20 the described linear classifier is used as a classifier in step S20.
  • step T20 as a criterion for defining the clusters, it may be used that the length of the difference between a feature vector of a respective cluster from the mean over the feature vectors of the cluster must be smaller than the smallest length of the differences between feature values different clusters.
  • Another embodiment differs from the first embodiment by the formation of the clusters in step T20 and the determination of the classifier.
  • a discriminant analysis in the example a Fisher Discriminant Analysis, which sets the classes to achieve maximum cluster spacing with minimal scattering in the clusters.
  • the parameters determined in the Fisher dislaim analysis analysis which correspond in particular to the matrix A and the vector B, are then determined as classification parameters.
  • the matrix A still contains portions that represent the projection in the subspace determined by the PCA or KL transformation.

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Abstract

La présente invention concerne un procédé pour vérifier des documents de valeur d'un même type prédéterminé. Selon ce procédé : des données de propriétés qui décrivent des propriétés prédéterminées de l'un des documents de valeur, sont déterminées pour ce document de valeur; une catégorie est déterminée pour le document de valeur à partir d'un nombre n de catégories prédéterminées pour des documents de valeur du type prédéterminé, n étant supérieur à 1 et les catégories étant prédéterminées de sorte que celles-ci sont associées respectivement à des documents de valeur qui ont été produits dans des charges de réalisation identiques; et, pour réaliser la vérification du document de valeur, un critère prédéterminé qui concerne les données de propriétés ou données de traitement résultantes, est vérifié au moins en fonction de la catégorie déterminée, et un signal décrivant le résultat de la vérification est produit.
PCT/EP2010/007687 2009-12-16 2010-12-15 Procédé pour vérifier des documents de valeur WO2011082792A1 (fr)

Applications Claiming Priority (2)

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DE102009058438.2 2009-12-16
DE102009058438A DE102009058438A1 (de) 2009-12-16 2009-12-16 Verfahren zur Prüfung von Wertdokumenten

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WO2011082792A1 true WO2011082792A1 (fr) 2011-07-14

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AT517868A1 (de) * 2015-11-05 2017-05-15 Ait Austrian Inst Technology Verfahren zur Bestimmung des räumlichen Reflexionsverhaltens einzelner Gegenstandspunkte
CN109767546A (zh) * 2017-01-10 2019-05-17 中国人民银行印制科学技术研究所 有价票据的质量核查调度装置和质量核查调度方法
RU2774736C1 (ru) * 2019-03-14 2022-06-22 Лорел Бэнк Машинз Ко., Лтд. Устройство обнаружения бумажных листов, способ обнаружения бумажных листов и устройство обработки бумажных листов
US11858775B2 (en) 2019-03-14 2024-01-02 Laurel Bank Machines Co., Ltd. Paper sheet detection device, paper sheet detection method, and paper sheet processing device

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CN109767546A (zh) * 2017-01-10 2019-05-17 中国人民银行印制科学技术研究所 有价票据的质量核查调度装置和质量核查调度方法
RU2774736C1 (ru) * 2019-03-14 2022-06-22 Лорел Бэнк Машинз Ко., Лтд. Устройство обнаружения бумажных листов, способ обнаружения бумажных листов и устройство обработки бумажных листов
US11858775B2 (en) 2019-03-14 2024-01-02 Laurel Bank Machines Co., Ltd. Paper sheet detection device, paper sheet detection method, and paper sheet processing device

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