SENSOR AND METHOD FOR EXAMINATION OF SECURITY DOCUMENTS

Description

[0001] The present invention relates to a sensor and a method for checking value documents.

[0002] Valuable documents are defined as sheet-like objects that represent, for example, monetary value or authorization and therefore should not be arbitrarily producible by unauthorized persons. They therefore possess security features that are difficult to produce, the presence of which is an indication of authenticity. Important examples of such valuable documents are chip cards, coupons, vouchers, checks, and especially banknotes. These valuable documents can differ in their type, for example, in the case of banknotes, by the denomination or face value and the currency, or in the case of checks, by a check form type specified by the check issuer.

[0003] To protect against counterfeiting, it is known to equip valuable documents with magnetic fibers that produce a characteristic magnetic signal or with fibers that produce a characteristic optical signal, e.g., characteristic remission or luminescence. Valuable documents are often equipped with luminescent mottled fibers that are distributed in a specific manner or randomly across their surface. Such mottled fibers are usually added to the paper substrate of the valuable documents during production. It is known to optically excite valuable documents equipped with mottled fibers and to test the mottled fiber luminescence. To distinguish genuine valuable documents from counterfeits, it is usually checked whether the respective valuable document actually contains luminescent mottled fibers or not.US 8 634 066 B1 discloses the examination of valuable documents, which contain fibers which are randomly distributed within a region of the documents.

[0004] US 2008 / 0130963 A1 discloses the verification of documents based on the fibers of predetermined regions. To generate an identifier, one or more regions are selected, and a hash is generated for them from the fiber pattern. The location of the regions is stored so that the corresponding fiber pattern can be detected and compared again during the verification.

[0005] Counterfeits of valuable documents, which are also referred to below as composed counterfeits, occur again and again. These can be created by joining a detached part of a valuable document – ​​usually by gluing – to a substrate section, such as a suitably shaped piece of paper or foil, in such a way that a structure is created that has approximately the dimensions of the valuable document. For example, a valuable document can be cleverly divided into two parts, each of which is then joined together using a suitable substrate section. This creates two counterfeits of the valuable document, which, depending on the design of the counterfeit, can be difficult to distinguish from the genuine valuable documents.

[0006] Various methods are known for detecting composed counterfeits, for example, those aimed at detecting adhesive strips or a print image offset. However, these methods can only detect some composed counterfeits, while others remain undetected.

[0007] The present invention is therefore based on the object of providing a sensor and an improved method for checking a value document for a suspicion of the presence of a forgery, in particular a composed forgery.

[0008] This object is achieved by the features of the independent claims. The dependent claims specify advantageous embodiments and further developments of the invention.

[0009] The invention relates to the verification of value documents comprising a plurality of fibers distributed across the value document and having a characteristic optical or magnetic signal. The fibers can be distributed (unevenly or evenly) across one or more sections of the value document or across the entire value document. They can be distributed, for example, in the substrate of the value document or on the surface of the substrate. In particular, the optical and / or magnetic properties or signals of the fibers differ from the optical and / or magnetic properties or signals of the substrate of the value document. The value documents verified using the method according to the invention are, for example, banknotes, checks, tickets, vouchers, etc.To check such value documents, in particular to detect counterfeits, especially composed counterfeits, the value document to be checked is brought into the detection range of a sensor.

[0010] The sensor has an image capture device configured to capture a value document image of the value document, preferably of the entire value document. In particular, the image capture device is configured for the spatially resolved detection of optical or magnetic signals of the value document. The value document image shows the two-dimensional distribution of optical or magnetic signals of the value document across the value document, preferably across the entire value document, and contains or shows a characteristic optical or magnetic signal of the fibers. In particular, the sensor also has a control device configured to control the image capture device such that it detects optical or magnetic signals of the value document in a spatially resolved manner.

[0011] Furthermore, the sensor has an evaluation device configured to evaluate the value document image. The evaluation device is configured to locate the fibers contained in the respective value document image and to determine at least one local fiber characteristic value for one or more different locations on the value document image, which applies to the respective location and, if applicable, to an area surrounding the respective location on the value document image. The evaluation device is also configured to classify the value document as suspected of being counterfeit based on the at least one local fiber characteristic value, in particular based on the local fiber characteristic values ​​determined for the various locations on the value document image.If the valuable documents are processed automatically using a valuable document processing device, the valuable document suspected of being counterfeit can then be automatically sorted out by the valuable document processing device.

[0012] The evaluation device is configured to receive the valuable document image captured by the image capture device, which is then transmitted (e.g., by a processor or the image capture device) to the evaluation device. The evaluation device can be located in the sensor housing of the sensor or outside the sensor housing. It can also be a central evaluation device of the valuable document processing device, which evaluates the measurement signals from multiple sensors (possibly jointly).

[0013] The respective local fiber characteristic applies individually to the respective location of the value document image or individually to the respective location and its (spatial) surroundings on the value document image. The surroundings of the respective location can include the respective location. The surroundings of different locations are not congruent, but can overlap. In general, the local fiber characteristic values ​​of different locations on the value document differ from one another. For each location and its surroundings, exactly one local fiber characteristic value can be determined, or for each location and its surroundings, different local fiber characteristic values ​​can be determined and used to classify the value document.

[0014] The respective location for which the at least one local fiber characteristic value is determined, and if applicable the surroundings of the respective location, corresponds, for example, to a partial image of the value document image or a raster point, if applicable with the surrounding area assigned to it (as explained further below).

[0015] For example, the local fiber characteristic value is characteristic of the local density of the fibers in the vicinity of the respective location and / or of the local distribution of the fibers in the vicinity of the respective location and / or of the position of one or more fibers in the vicinity of the respective location and / or of the local condition of the fibers in the vicinity of the respective location. This condition can in particular relate to the appearance of the fibers (e.g. the shape or size or color or brightness of the fibers) at the respective location and in the vicinity of the respective location or - in the case of magnetic fibers - also the strength of the magnetic signal of the fibers at the respective location and in the vicinity of the respective location. For example, a representative value, e.g. an average value, of the local condition of the fibers at the respective location and in the vicinity of the respective location is used as the local fiber characteristic value.Alternatively, the distance of the respective location to the nearest fiber is used as the local fiber characteristic, which is characteristic of the local position of one or more fibers in the vicinity of the respective location. The local fiber characteristic can also be the location's membership in an area of ​​influence defined around the respective fiber (defined below).

[0016] In preferred embodiments, a measure of the local fiber density is used as the local fiber characteristic value. For this purpose, the number of fibers or the fiber density (number of fibers divided by the area of ​​the partial image / surrounding region) can be used as the local fiber characteristic value in the respective partial image or surrounding region, or a distance measure characteristic of the distance between the fibers (e.g., statistical) of the fibers closest to the respective location or of the fibers in the respective partial image / surrounding region of the respective location, e.g., the average distance of these fibers in the partial image / surrounding region from the fiber closest to the respective fiber.

[0017] In other preferred embodiments, a measure of the local condition of the fibers at the location and, if applicable, in the surroundings of the respective location is used as the local fiber characteristic value, which particularly relates to the shape (e.g., aspect ratio, orientation, winding(s)) or size (e.g., length, width, area) or color or brightness of the fibers at the respective location and, if applicable, in the surroundings of the respective location.

[0018] The fibers, whose optical and / or magnetic properties differ from the optical and / or magnetic properties of the substrate of the value document, are individual thin, elongated objects, e.g., with a length in the range of a few millimeters. The term fibers in this application does not refer to the paper fibers of the paper substrate of a value document. The fibers are manufactured separately from the substrate material of the value document and, after their manufacture, are incorporated into or applied to the substrate material of the value document. The fibers are, for example, made of paper or of a material that differs from the substrate material of the value document, e.g., of plastic or metal, and the substrate material of the value document is made of paper. The fibers are, for example, luminescent fibers distributed in or on the substrate of a non-luminescent value document substrate, or magnetic fibers distributed in or on the substrate of a non-magnetic value document substrate, or black, gray, or single- or multi-colored fibers distributed in or on the substrate of a light or white value document substrate.

[0019] In some types of security documents, the fibers are distributed essentially evenly throughout the respective security document. Deviations from an absolutely uniform distribution can arise due to statistical fluctuations during the production of the security document, for example, when applying fibers to the security documents or when incorporating the fibers into the mass (e.g., the paper or plastic mass) from which the security document substrate is manufactured. In other types of security documents, the security documents have only one or more specific fiber-containing areas, the location of which on the security document is fixed.

[0020] The evaluation device is particularly configured to perform an image analysis of the value document image, in which—based on the signal distribution of the optical or magnetic signals—fibers that may be contained in the value document image are located. To identify the fibers, neighboring pixels of the value document image can be searched for whose signal intensity exceeds a threshold, and it can be checked whether the objects resulting from such neighboring pixels have the expected shape, in particular the thickness and length and, if applicable, the shape, of a fiber. The located fibers can have the same or different properties, e.g., the same or different shapes or colors.

[0021] For verification, the valuable document can be statically placed within the sensor's detection range. A two-dimensional image sensor is then preferably used as the sensor, which detects the optical or magnetic signals emanating from the valuable document. However, the valuable document is preferably transported past the sensor along a transport direction in order to scan the various sections of the valuable document one after the other with the sensor. An optical or magnetic image sensor configured as a sensor line is then preferably used as the sensor.

[0022] In a first variant, the sensor is a magnetic sensor and the image capture device is configured for the spatially resolved detection of magnetic signals from the value document, in particular from the fibers. The value document image is then a magnetic signal image of the value document. And the fibers are magnetic fibers whose magnetic properties differ from the magnetic properties of the substrate of the value document. The characteristic magnetic signal of the fibers is then a magnetic signal from the fibers that differs significantly from the usually small or negligible magnetic signal of the less magnetic or non-magnetic value document substrate. The image capture device is a magnetic signal image capture device configured for the spatially resolved detection of the magnetic signals from the fibers. It has, in particular, a plurality of magnetosensitive detector elements and can, for example,be a high-resolution magnetic detector line (for checking a value document transported past the sensor) or have two-dimensionally arranged magneto-sensitive detector elements.

[0023] In a second variant, the sensor is an optical sensor, and the image capture device is configured for the spatially resolved detection of optical signals from the value document, in particular from the fibers. The fibers have optical properties that differ from the optical properties of the substrate of the value document. The image capture device is then an optical image capture device (e.g., an optical image sensor) configured for the spatially resolved detection of optical signals from the fibers, in particular from luminescence or remission of the fibers. The image capture device has a plurality of photosensitive elements and is, for example, an image sensor array or a two-dimensional image sensor, e.g., based on a CCD or CMOS array. The value document image can be a remission image or a luminescence image of the value document.

[0024] In the case of an optical sensor, a lighting device, which can be part of the sensor, can be used to illuminate a valuable document placed within the detection range of the optical sensor. It can be suitable for illuminating or exciting the luminescence of the valuable document. The valuable document to be checked is placed within the detection range of the optical sensor in such a way that it can be illuminated or optically excited by the light from the lighting device, and the light emanating from the valuable document can be detected by the optical image capture device. The light emanating from the valuable document can be remission light, i.e. illumination light from the lighting device reflected by the valuable document (directed or non-directed).Alternatively, it can be luminescent light, which the valuable document emits as a result of the illumination suitable for optical excitation emitted by the illumination device. The term luminescence is understood as a generic term for the radiation re-emitted by the valuable document after (optical or electrical) excitation, e.g., fluorescence or phosphorescence.

[0025] In a first embodiment of the second variant, the optical sensor is a remission sensor and the value document image, which the optical image capture device is configured to capture, is a remission image of the value document. The characteristic optical signal of the fibers is then a remission signal of the fibers. In the remission image, the fibers appear, for example, black, gray, or colored against a background formed by the value document substrate or other security features of the value document. The background can be dark, light, or white, but also structured or multi-colored, as long as the remission signal of the fibers is clearly different. The fibers can be luminescent or non-luminescent, magnetic or non-magnetic. The remission sensor may have an illumination device configured to illuminate the value document with illumination light.

[0026] In a second embodiment of the second variant, the fibers are luminescent fibers and the optical sensor is a luminescence sensor. Accordingly, the value document image, which the optical image capture device is configured to capture, is then a luminescence image of the value document, and the characteristic optical signal of the fibers is a luminescence signal of the fibers. The luminescence signal can be a fluorescence or phosphorescence signal. The background of the non-luminescent value document substrate is then usually dark. The luminescence sensor may have an illumination device configured to illuminate the value document with excitation light emitted by the illumination device in order to optically excite the luminescent fibers of the value document. Alternatively, the luminescence of the fiber can also be electrically excited if the luminescence is electroluminescence.The image capture device of the luminescence sensor is an optical image capture device that is configured to capture the luminescence image of the value document.

[0027] All of the following statements refer equally to both the first and the second variant (and both embodiments of the second variant).

[0028] The evaluation device can be configured to determine one or more partial images of the value document image, each containing a section of the value document image. The shape of the partial images can be, for example, square, rectangular, round, or any other shape. The partial images contain, for example, non-congruent sections of the value document image, which may or may not overlap with one another. Overlapping several partial images increases the probability that one of the partial images used is located in a possibly existing forged section of the value document (the position of which is not known in advance). The local fiber characteristic value of the forged section then deviates more from an expected value than in the case where the partial image only partially lies in the forged section. The forgery in question is therefore more easily detected when the partial images overlap.

[0029] The respective partial image is preferably determined such that the characteristic optical or magnetic signal of several fibers of the value document is expected in the respective partial image. The evaluation device is configured, for example, to determine the at least one local fiber characteristic value for one or more of the partial images and to classify the value document as suspected of being counterfeit (or as not suspected of being counterfeit) depending on the at least one local fiber characteristic value of one or more of the partial images. The position or size of the partial images in the value document image can be predetermined or selected dynamically, e.g., depending on the position of the (previously localized) fibers, or depending on the transport position of the value document. The local fiber characteristic value is, for example,characteristic of the local density of the fibers in the respective partial image and / or the local distribution of the fibers in the respective partial image and / or the position of one or more fibers in the respective partial image and / or the local nature of the fibers in the respective partial image.

[0030] In a further development of the invention, the evaluation device for evaluating the value document image is configured to (systematically) scan the value document image point by point using raster points, wherein a local fiber characteristic value is determined for each raster point of the value document image, and to classify the value document as suspected of being counterfeit depending on the local fiber characteristic values ​​determined in this process. The raster point can be a single pixel of the value document image or several pixels of the value document image that are combined to form a raster point. The raster points have, for example, predefined positions on the respective value document image and are preferably evenly distributed across the value document. The local fiber characteristic value determined for the respective raster point can apply point-by-point to the respective raster point or to an area surrounding the respective raster point.The surrounding area can also contain the respective raster point. The respective raster point, possibly with the surrounding area assigned to it, can correspond to a partial image of the value document image.

[0031] The local fiber characteristic value determined for each raster point of the value document image is characteristic, for example, of the density / position / condition / distribution / number / distance of one or more fibers closest to the respective raster point. For example, an average local fiber characteristic value can be determined across multiple raster points, and the scatter of the local fiber characteristic values ​​around this average, which results from considering multiple raster points, can be used to classify the value document as suspected of being counterfeit. If the scatter is too large, the value document is rejected as suspected of being counterfeit.

[0032] In a further development of the invention, the evaluation device for evaluating the value document image is configured to identify one or more conspicuous raster points that are conspicuous with regard to the local fiber characteristic value determined at the respective raster point, and, in particular based on the position of the conspicuous raster points on the value document image, to identify one or more conspicuous regions of the value document image in which conspicuous raster points are located. The evaluation device then classifies the value document as suspected of being counterfeit depending on one or more properties of the respective conspicuous region and / or depending on the local fiber characteristic values ​​determined for the raster points of the respective conspicuous region (for which purpose, the local fiber characteristic values ​​of the conspicuous and, if applicable, also of the non-conspicuous raster points located in the conspicuous region can be used).

[0033] A raster point is classified as suspicious, for example, by comparing the local fiber characteristic value determined for the respective raster point with an expected value applicable to the respective local fiber characteristic value. If the deviation exceeds an acceptable fluctuation range, the respective raster point is classified as suspicious. The value document can, for example, be classified as suspected of being counterfeit if at least a minimum proportion of the raster points in a suspicious region are suspicious. Or the value document can be classified as suspected of being counterfeit depending on a mean local fiber characteristic value that is averaged across all raster points in the respective suspicious region. Alternatively, the scatter of the local fiber characteristics around this mean value, which results from considering several areas surrounding the suspicious region, can also be used to classify the value document as suspicious.

[0034] The respective partial image / the respective surrounding area is identified as a conspicuous region, for example. Alternatively, the conspicuous region of the value document image can first be determined based on the distribution of conspicuous raster points, i.e. dynamically. In particular, the evaluation device for evaluating the value document image can be set up to determine the distribution of the conspicuous raster points and to use this to identify one or more conspicuous regions. Conspicuous partial images can also be selected from predefined partial images. Alternatively, conspicuous regions of variable shape and size can be defined on the basis of the distribution, e.g. by means of an image analysis in which the respective proportion of conspicuous raster points in each row / column / row section / column section of the value document image is determined.If this proportion is greater than a reference value, the respective row / column / row section / column section is classified as suspicious. The suspicious row / column / row section / column sections or grid points can then be used to form the suspicious region, based on whose properties the valuable document can be classified as suspected of being counterfeit.

[0035] The property(ies) of the respective conspicuous region, depending on which the value document is classified as suspected of being counterfeit, are, for example, the differences in the local fiber characteristics at the grid points of the conspicuous region of the value document image compared to an expected value applicable to the respective local fiber characteristic and / or the shape of the conspicuous region or the distribution of several conspicuous regions across the value document image and / or the number of conspicuous regions found in the value document image. The expected value can be predetermined or determined based on the local fiber characteristics of other regions of the value document image or using the average local fiber characteristic of the entire value document image.

[0036] In some embodiments, the evaluation device for evaluating the value document image is configured to determine the or at least one of the local fiber characteristic values ​​determined for the respective raster point of the value document image for a (planar) surrounding area assigned to the respective raster point. The respective raster point with surrounding area can be one of the above-mentioned partial images of the value document image. The surrounding areas can form concurrent partial images during scanning. The surrounding area assigned to the respective raster point is preferably located at least in the vicinity of the respective raster point, e.g. directly next to or around the respective raster point, so that the respective raster point lies in the respective surrounding area. The respective raster point lies, for example, at the edge or inside the surrounding area assigned to it.The size of the surrounding area can be fixed or selected based on the expected fiber density. The respective local fiber characteristic is determined in the surrounding area of ​​the respective grid point. The surrounding areas of neighboring grid points can overlap or not overlap.

[0037] In other embodiments, the evaluation device for evaluating the value document image is configured to determine the local fiber characteristic value(s) determined for each raster point of the value document image, point by point, for the respective raster point. In this case, the local fiber characteristic value is determined only at the respective raster point itself. Accordingly, no surrounding area of ​​the raster point is required or defined for determining the respective local fiber characteristic value. For example, the local distance of the respective raster point to the nearest fiber can be used as the local fiber characteristic value, or the affiliation of the respective raster point to one or more effective areas of the fibers (see below).

[0038] Preferably, the evaluation device is configured to determine each of the partial images of the value document image such that the characteristic optical or magnetic signal of a minimum number of fibers is expected in the respective partial image. In particular, an expected density value for the areal density of fibers for the respective value document type can be provided in the sensor for one or more value document types. This is particularly preferred for those value document types in which the fibers are distributed substantially uniformly (but randomly) across the respective value document, either substantially uniformly across the entire value document or at least across a section of the value document in which the partial images are determined.In order to determine the at least one partial image of the value document image, the evaluation device can be configured to select the surface area of ​​each partial image of the value document image, based on the density expectation value of the fibers of the value document type to be checked, to be at least so large that - taking into account a random statistical distribution of the fibers over the value document - it is expected that the respective partial image contains the characteristic optical or magnetic signal of at least the minimum number of fibers.

[0039] For example, the evaluation device can be configured to determine the partial images such that their surface area F is each at least the minimum number M divided by the expected density value DE: F>=M / DE. If the expected density value DE of the fibers is lower, the sensor therefore defines partial images with a larger surface area. This ensures that the expected value for the number of fibers in the respective partial image is large enough to enable a precise test. This is because a fiber count of zero in a genuine value document equipped with fibers is then very unlikely. The probability of erroneously classifying a genuine value document as a composed forgery decreases with increasing expected value for the number of fibers.

[0040] With a larger expected value, the probability that - in the case of a genuine value document with an even distribution of fibers - a very small number (e.g. zero) fibers will appear in the partial image to be checked is reduced. Otherwise, if only a few fibers are expected in a partial image, it could happen that even with a genuine value document, no fibers are found by chance in the checked partial image. To avoid genuine value documents being inadvertently classified as suspected of being forged due to an insufficient number of fibers being found in a partial image, it is therefore advantageous to define partial images that have a relatively large expected value for the number of fibers and / or, in the case of a value document, to determine two or more partial images that cover the largest possible area of ​​the value document.

[0041] The evaluation device is preferably configured to determine at least two partial images of the value document image (which are arranged next to one another on the value document image, for example), in particular at least two such partial images of the value document image which together preferably cover at least 50% of the area of ​​a value document side of the value document, in particular at least 75% of the area of ​​a value document side of the value document. The partial images can be distributed unevenly across the value document or arranged evenly, for example row by row and / or column by column, on the value document. In particular, the partial images can be arranged in a grid of at least two rows and / or at least two columns on the value document. The evaluation device can also be configured to divide the value document image into a plurality of partial images essentially across the entire area when determining the partial images of the value document image, for example independently of the type of value document.

[0042] In a further development of the invention, the sensor is configured to check value documents of one or more specific value document types, each of which has at least one interfering (e.g., optical or magnetic) security element that interferes with or impairs the detection of the characteristic optical or magnetic signal of the fibers. To check such value documents, the sensor's evaluation device is configured to classify the value documents of the specific value document type as suspected of being counterfeit, depending on the at least one local fiber characteristic value of only one or more locations on the value document image where the detection of the optical or magnetic signal of the fibers is not impaired by the specific (e.g., optical or magnetic) security element.“Not affected” means that the optical or magnetic signals of the fibers are not influenced by the specific security elements, or at most are influenced only to the extent that at least one local fiber characteristic value of the respective location can still be determined, despite the specific security element that may be present there. This excludes or avoids locations of the value document image where physical shielding of the optical or magnetic signals of the fibers occurs, e.g. by absorbing or reflective security elements, or where there is an interfering superposition with optical or magnetic signals of the security elements. Preferably, only those locations of the value document image are selected, or the local fiber characteristic value of only those locations is evaluated, that lie outside of an interfering security element.

[0043] For example, prior to the value document verification (e.g. during sensor adaptation), the sensor's evaluation device receives information about the positions of interfering (optical or magnetic) security elements on the value documents to be verified, possibly for multiple value document types. Based on the information about the position of one or more interfering security elements, the evaluation device can be configured to determine the locations or partial images of the respective value document image to be evaluated during the evaluation in such a way that the optical or magnetic signals of the fibers at the respective location or in the respective partial image are not impaired by an interfering (e.g. optical or magnetic) security element. In particular, the position (and possibly also the shape or size) of the partial images on the value document can be determined in such a way that the partial images do not overlap with any interfering security element.

[0044] In the case of an optical sensor, when determining the locations or partial images to be evaluated, in particular those areas of the value document image are skipped or omitted which contain fluorescent or absorbing optical security elements, such as patches, fluorescent elements or dark-printed areas of the value document. For example, the locations or partial images to be evaluated are preferably positioned in white and light-printed areas. In the case of a magnetic sensor, when determining the locations or partial images to be evaluated, in particular those areas of the value document image are skipped or omitted which contain magnetic security elements with a very large magnetic signal, e.g. a magnetic security thread or a magnetic print area whose magnetic signal is on the order of magnitude of the magnetic signal of the magnetic fibers.These interfering magnetic security elements can be located on the side of the valuable document facing the sensor or on the side of the valuable document facing away from the sensor (their magnetic signal can still cause interference).

[0045] The sensor's evaluation device can also have information about the transport position of the value document to be checked and / or information about the value document type (e.g. currency or denomination) of the value document to be checked. The transport position can be one of four possible transport positions: front of the value document at the top / bottom, distinguished edge of the value document leading / trailing. The evaluation device can be configured to use the information about the transport position and / or the information about the value document type of the value document to be checked to determine only those locations or partial images of the value document image for evaluation at which the detection of the optical or magnetic signal from the fibers is not impaired by one of the interfering security elements.The respective value document to be checked is then classified by the evaluation device as suspected of being counterfeit depending on the local fiber characteristics only of the locations or partial images intended for evaluation, i.e. depending on the local fiber characteristics only of those locations or partial images where the detection of the optical or magnetic signal of the fibers is not impaired by an interfering security element.

[0046] For example, the sensor's evaluation device receives information about the position of one or more interfering (e.g. optical or magnetic) security elements of the respective value document type for one or more value document types prior to the value document verification (e.g. during sensor adaptation), depending on the value document type and / or the transport position of the value documents. The evaluation device can, for example, be set up to - based on the information about the value document type of the respective value document to be verified and using the information about the position of the interfering (optical or magnetic) security element(s) of the respective value document type depending on the value document type - only identify those locations orTo determine partial images of the respective value document to be checked for evaluation in which the capture of the optical or magnetic signal of the fibers is not impaired by an interfering security element. Additionally or alternatively, the evaluation device can be configured to determine for evaluation only those locations or partial images of the respective value document to be checked in which the capture of the optical or magnetic signal of the fibers is not impaired by an interfering security element - based on the information about the transport position of the respective value document to be checked and using the information about the position of the interfering (optical or magnetic) security element(s) of the respective value document type depending on the transport position of the value documents.

[0047] The information about the transport position or value document type of the value document to be checked can be provided in the sensor itself (e.g. in cases where it is immutable), e.g. stored in a data memory of the sensor and transmitted to the evaluation device, or supplied to the evaluation device from outside the sensor, e.g. from another sensor of the value document processing device that has detected the transport position or value document type of the value document to be checked, or from another device of the value document processing device in which the transport position currently set on the value document processing device or the value document type is stored. The information on the position of the specific security elements of the value document depending on the transport position and / or depending on the value document type of the value document can also be provided in the sensor itself, e.g.stored in a data memory of the sensor, which the evaluation device can access, or fed to the evaluation device from outside the sensor, e.g. from another sensor or from another device of the value document processing device.

[0048] In some embodiments, the evaluation device for evaluating the value document image is configured to assign a (areal) area of ​​effect to each of the localized fibers of the value document image (all or a subset of the fibers of the value document image or each fiber of the respective partial image / the respective surrounding area of ​​the respective raster point). The respective fiber is preferably located in the interior (e.g. center) of its assigned area of ​​effect. For evaluation, the evaluation device locally analyzes the areas of effect of the fibers localized at the respective location and possibly in its surroundings for the respective locations of the value document image (e.g. for several different partial images or surrounding areas of raster points), e.g. the areas of effect of the fibers present in the respective partial image or in the respective surrounding area of ​​the respective raster point.For example, the effective areas are analyzed locally with regard to the area they cover or do not cover, or with regard to any overlap between neighboring effective areas. The evaluation device determines the respective local fiber characteristic value of the respective location (e.g., partial image or surrounding area) based on the local analysis of the (locally existing) effective areas located at the respective location and, if applicable, in its surroundings.

[0049] For example, the local fiber characteristic is determined depending on the overlap / distribution of the effective areas / the position of the effective areas / the area of ​​the effective areas.

[0050] The size and / or shape of the effective areas can be the same for each of the localized fibers of the value document image. However, the size and / or shape can also vary depending on the region on the value document. For example, the effective areas can each have the shape of a circle, oval, or rectangle with the respective fiber in the center. Alternatively, the shape and / or size can also be selected depending on the fiber shape, e.g., in the form of a tube-like structure around the respective fiber. The effective areas are preferably defined such that they have a smaller area than the partial images or surrounding areas. Then, certain local fiber characteristics can be determined more precisely. However, the partial images or surrounding areas can also be smaller than the effective areas, e.g., in the case of local fiber characteristics that are only determined at the respective raster point, e.g.,the local distance of the respective grid point to the next fiber, or affiliation of the respective grid point to at least one effective area of ​​a fiber (yes / no).

[0051] In particular, the evaluation device for evaluating the value document image is configured to select the size of the effective areas depending on an expected density value that specifies the (possibly locally) expected areal density of the fibers, in particular inversely proportional to the expected density value. The expected density value can be the same at every location in the value document image if the fibers are evenly distributed across the value document, or it can only apply to the respective partial image or surrounding area. Therefore, with a high expected density value, smaller effective areas are defined than with a low expected density value. This makes it easier to find conspicuous regions of the value document image in which too few or too many fibers are located by analyzing the effective areas, even for different value document types (with different expected density values).

[0052] In one embodiment, the evaluation device is configured to evaluate the value document image, for the entire value document image or for one or more partial images respectively or for at least one or more surrounding areas of raster points respectively To identify overlapping areas that belong to the effective area of ​​at least one of the fibers of the value document image or the respective partial image or the respective surrounding area and / or to identify free areas that do not belong to any effective area of ​​at least one of the fibers of the value document image or the respective partial image or the respective surrounding area and / or to identify overlapping areas in which the effective areas of at least two (neighboring) fibers of the value document image or the respective partial image or the respective surrounding area overlap, and to identify one or more conspicuous regions (e.g. partial image, surrounding area) of the value document image that, with regard to their overlapping areas / free areas / overlapping areas (e.g.(with regard to their area / area proportion) are conspicuous, and to classify the value document as suspected of being forged depending on the properties of the overlapping areas and / or the free areas and / or the overlapping areas in / at one or more conspicuous regions of the value document image.

[0053] The property(ies) depending on which the value document is classified as suspected of being forged are, for example, the surface area and / or the surface proportion of the coverage areas and / or the free areas and / or the overlap areas in / at one or more conspicuous regions of the value document image and / or the shape of the conspicuous region or the distribution of several conspicuous regions across the value document image and / or the number of conspicuous regions found in the value document image. A region / a partial image / a surrounding area can also be classified as conspicuous depending on the surface area of ​​the largest free area and / or overlap area found therein. A region is conspicuous, for example, if the surface area or the surface proportion of the coverage areas / free areas / overlap areas in the respective conspicuous region is larger than expected.This can be determined by comparing with a predetermined reference value for the area / area proportion or by comparing with other regions (partial images, surrounding areas) or with the average area proportion of the coverage areas / free areas / overlap areas in the entire value document image.

[0054] In a further development of the invention, the value document image captured by the image capture device is a first value document image captured from a first value document side (front or back) of a value document to be checked, and the evaluation device additionally has a second value document image captured from the second side of the same value document to be checked, opposite the first side (back or front). The evaluation device is then configured to determine at least one local fiber characteristic value for at least one first partial image of the first value document image and for at least one second partial image of the second value document image, wherein corresponding local fiber characteristic values ​​that are comparable with one another are preferably determined for the first and second partial images.For example, the local fiber characteristic value of the first and second partial images is each characteristic of the local density of the fibers in the respective first or second partial image, or of the local distribution of the fibers in the respective first or second partial image, or of the position of one or more fibers in the respective first or second partial image, or of the local nature of the fibers in the respective first or second partial image. The value document is then classified as suspected of being a forgery depending on the local fiber characteristic value of the at least one first partial image and depending on the local fiber characteristic value of the at least one second partial image, in particular with regard to the presence of a composed forgery. The first and second partial images can be positioned in the same or in different sections of the respective value document.

[0055] The local fiber characteristics of the first and second partial images can be checked separately (e.g., compared with an expected value each), or they can be combined or compared with each other. When combining, for example, the mean fiber density of the first and (if applicable, corresponding) second partial images is determined, or the fiber count of the first and second partial images is added together, and the value document is classified as suspected of being forged depending on the mean fiber density or the sum of fibers in the first and (if applicable, corresponding) second partial images. The evaluation device can also compare the local fiber characteristics of the first and (if applicable, corresponding) second partial images with each other (e.g., the density or the mean fiber spacing) and classify the value document as suspected of being forged depending on the comparison result, e.g.,for deviations that exceed an acceptable range. This allows counterfeits to be detected that have fibers on only one side.

[0056] The selection of partial images or the area of ​​the possible partial images on a security document side may be limited by other security elements or dark printed areas of the security document. By evaluating at least one partial image of the front and at least one partial image of the back, a larger area of ​​the security document is examined than with a single-sided examination of the security document, thus making the examination more reliable. By evaluating partial images of the front and back, it is therefore possible to reliably examine even security documents for which only small partial images are possible or which have relatively few fibers.

[0057] In a particularly advantageous variant of the two-sided evaluation, the evaluation device is configured to determine a corresponding second partial image of the second value document image for the at least one first partial image of the first value document image, which is a section of the second value document image, wherein the first partial image and the corresponding second partial image contain the optical or magnetic signals of the front and back of the same value document section of the same value document. The evaluation device is configured, for example, to determine the corresponding pixels of the second value document image for the pixels of the first value document image. In order to find the second partial image (e.g. the back) corresponding to the first partial image (e.g. the front), a mirroring of the first or second partial image (front or back image) and, if applicable,a slight rotation and / or shifting of the images relative to each other may be necessary.

[0058] The evaluation device is also configured to determine at least one local fiber characteristic value for each of one or more pairs of the first and corresponding second partial images. Preferably, corresponding local fiber characteristic values ​​are determined for the first and second partial images, which are comparable with each other, and to classify the value document as suspected of being a forgery depending on the local fiber characteristic values ​​of the first and the second partial images corresponding to the first partial image, e.g., with regard to the presence of a composed forgery. The local fiber characteristic values ​​of the first and corresponding second partial images can be checked separately, or they can be combined or compared with each other (see examples above).

[0059] By evaluating the corresponding partial images of the same security document section on the front and back, an even more precise security document verification is achieved. Since the two corresponding partial images show the same security document section (e.g., the front and back of the same piece of paper), this bilateral evaluation does not simply enlarge the examined area, but – due to the spatial correspondence of the partial images on the security document – ​​is more meaningful than evaluating two arbitrary partial images of the same security document together. For any two partial images of the same security document, in the case of a composed forgery, it is to be expected that they are not both located in the forged section or both in the genuine section, but in many cases, one of the partial images is located in the forged section and one in the genuine section of the composed forgery. A combined local fiber characteristic (e.g.,The mean value of such partial images would therefore be closer to the expected value of the genuine value document than in the case of corresponding partial images.

[0060] However, if the two corresponding partial images of the front and back are evaluated, which contain exactly the same section of the value document, it is certain that if one of these partial images (e.g., the front partial image) lies in the forged section of a composed forgery, then the other corresponding partial image (the back partial image) also lies in the forged section of this composed forgery. Therefore, the two corresponding partial images are more likely to both lie in the forged part of a composed forgery. A combined local fiber characteristic value of the two corresponding images will then deviate significantly from the expected value. As a result, the bilateral evaluation of the same value document section achieves a significantly improved discriminatory power for detecting forgeries.

[0061] The respective pair of the first and corresponding second partial image can be classified as suspicious depending on the two local fiber characteristics, and the value document can be classified as suspicious depending on the pairs of the first and corresponding second partial image of the respective value document that are classified as suspicious, in particular depending on the number of pairs of the first and corresponding second partial image of the respective value document that are classified as suspicious, e.g. if the number of such pairs for the same value document is at least 1 or 2.

[0062] The second value document image can be captured using the same image capture device, with the first and second value document images being captured one after the other, for example, when the value document is transported past the optical sensor again in the reversed transport position. Alternatively, the second value document image can also be captured using a different image capture device (possibly simultaneously with the first value document image), which is arranged, for example, on the opposite side of the aforementioned image capture device.

[0063] In a further development of the invention, the evaluation device is configured to compare the local fiber characteristic value with a (fiber-related) expected value E for one or more locations of the value document image (partial images or the raster points or their surrounding areas). Depending on the result of this comparison obtained for one or more locations of the value document image, the value document is then classified by the evaluation device as suspected of being forged. For example, the evaluation device is configured to classify the value document as suspected of being forged depending on a difference that arises when comparing the respective local fiber characteristic value of the respective location and the expected value determined for the respective location. The expected value can be different for different locations (partial images or the raster points or their surrounding areas) of the value document image.

[0064] For example, the evaluation device determines those locations (e.g. partial images or raster points or their surrounding areas) whose local fiber characteristic value deviates from the respective expected value (e.g. by more than an acceptable fluctuation range). The acceptable fluctuation range is preferably at least 20%, particularly preferably at least 40%, of the respective expected value. And the value document is classified as suspected of being forged depending on the number and / or position and / or distribution of the locations on the value document image (partial images or raster points or their surrounding areas) whose local fiber characteristic value deviates from the expected value (by more than the acceptable fluctuation range). In particular, a spatial arrangement of the locations (partial images orRaster points or their surrounding areas) are compared with a target arrangement known for the respective value document, and the value document is classified as suspected of being forged depending on the comparison of the spatial arrangement of the locations deviating from the expected value with the target arrangement.

[0065] For example, the expected value for the number of fibers can be used as an expected value. This indicates how many fibers are expected for the respective location if the value document to be checked is a genuine value document of the respective value document type. Or the density expected value, which indicates the fiber density expected in the respective partial image. The expected value can be a natural number, a positive real number, or zero. Different expected values ​​can be used for fibers of different properties, e.g., fibers of different colors.

[0066] If the expected value for the fiber count or fiber density is greater than zero, then - as an alternative to a quantitative determination of the difference to the expected value - it can also be checked whether the number of fibers or the fiber density in the respective partial image is equal to zero (or greater than zero). This is because, to determine a suspicion of forgery, it may be sufficient that the number of fibers or the fiber density is equal to zero, even though the expected value for this is greater than zero. In this case, it is not important how large the difference to the respective expected value is. For example, the evaluation device can be used to check a value document whose fibers are distributed (unevenly or essentially evenly) across the (entire) value document (i.e.where the expected value for the number of fibres or fibre density is greater than zero everywhere), be set up to classify the respective value document as suspected of being forged if the number of fibres is zero for at least a minimum number of partial images, where the minimum number is > 0.

[0067] The expected value can be predefined for the respective value document or for the respective location, e.g. already having been determined before the value document verification, in particular depending on the value document type, whereby different expected values ​​are generally predefined or determined for different value document types. Alternatively, the expected value can only be determined during the value document verification, e.g. on the basis of the local fiber characteristics that were determined for several locations of the respective value document image. In the case of a predefined expected value, this can be stored in the evaluation device of the sensor, e.g. in a data memory of the evaluation device. However, the predefined expected value can also be stored externally, e.g. in the value document processing device, and transmitted from there to the evaluation device.

[0068] Alternatively or in addition to the test based on a predefined expected value, the evaluation device can also be configured to determine the expected value with which the local fiber characteristic value of at least one location (partial image or raster point or its surrounding area) is compared, based on the local fiber characteristic values ​​found for one or more other locations (partial images or raster points or their surrounding areas) of the same value document image. Thus, a relative test of the local fiber characteristic values ​​of at least two different locations (partial images or raster points or their surrounding areas) of the same value document image can be performed. This is particularly advantageous for testing a value document whose fibers are essentially evenly distributed across the (entire) value document. This is because individual predefined expected values ​​then do not need to be stored, for example for newly published value documents.For example, the average local fiber characteristic of several other locations of the same value document image can be used as the expected value.

[0069] In particular, the evaluation device can be configured to carry out a relative evaluation of the partial images of the same value document with regard to the local fiber characteristics determined in the partial images. In this case, the local fiber characteristic value of one partial image can be compared with the local fiber characteristic value of one or more other partial images of the same value document and the value document can be classified as suspected of being forged depending on the result of the comparison, e.g. in the event of a significant deviation between the local fiber characteristics of different partial images of the same value document. For example, the evaluation device can be configured to calculate the expected value with which the local fiber characteristic value of at least one of the partial images is compared based on the local fiber characteristic value found at / in one or more other locations / partial images of the same value document.For example, the evaluation device can determine an average areal density of fibers for this value document based on one or more partial images of the same value document and use this as the expected density value. For example, the ratio of the local fiber characteristic values ​​determined for different locations / partial images can also be calculated, and the banknote can be classified as suspected counterfeit based on this ratio.

[0070] The evaluation device can perform a step-by-step classification of the individual locations to be examined (partial images or raster points or their surrounding areas) of a value document as suspected of being forged or not suspected of being forged. For example, the evaluation device for evaluating the value document image can be configured to classify the respective location as suspicious depending on the fiber characteristic value applicable to these locations, e.g., if it differs significantly from the expected value, e.g., by more than a threshold value. Otherwise, the respective location is classified as non-suspicious. The respective value document is then classified by the evaluation device as suspected of being forged (or not suspected of being forged) depending on the number of locations classified as suspicious for the respective value document.In particular, the evaluation device for evaluating the value document image can be set up to classify the respective value document as suspected of being forged if the number V of locations (partial images or raster points or their surrounding areas) classified as suspicious for the respective value document reaches or exceeds a minimum number P, ie if V≥P, where the minimum number is P>0 and is preferably 1 or 2, ie if at least one or at least two locations are classified as suspicious, the value document is classified as suspected of being forged.

[0071] The acceptable fluctuation range S can be determined from the expected value E, e.g., it can be specified proportional to it. To determine an acceptable fluctuation range S, the local fiber characteristic value for at least one predetermined location of the respective value document can also be determined before the value document verification - for a large number (e.g., 100) genuine value documents of the respective value document type. By averaging these local fiber characteristic values ​​of the large number of value documents, an average local fiber characteristic value can be determined for the respective value document type and, if applicable, for the respective location, which is then used as the expected value when verifying the value documents of this value document type. The genuine value documents contained in the large number do not have to belong to the same denomination, but merely have to nominally have the same fiber distribution, e.g., be made from the same fiber-containing substrate.Additionally or alternatively, the standard deviation s of the local fiber characteristic value of the respective value document type and, if applicable, the respective location can be determined from the local fiber characteristic values ​​determined for the multitude of genuine value documents of the respective value document type. The acceptable fluctuation range S for the respective value document type can then be selected depending on the standard deviation s of the local fiber characteristic value. In particular, a value can be set for the acceptable fluctuation range that is at least twice, preferably at least four times, the standard deviation s.

[0072] In a further development of the invention, the sensor provides the expected value for the respective location of the value document image (e.g., partial image or raster point or its surrounding area) for one or more value document types. The evaluation device also has information about the value document type of the respective value document to be checked. The evaluation device can be configured to determine the expected value for the local fiber characteristic value at the respective location of the respective value document to be checked, based on the value document type of the respective value document to be checked and using the expected value for the local fiber characteristic value at the respective location provided for one or more value document types. The information about the value document type of the respective value document to be checked can be provided in the sensor itself, e.g.stored in a data memory of the sensor, which the evaluation device can access, or it can be fed to the evaluation device from outside the sensor, e.g. from another sensor or from the value document processing device. The information about the value document type of the value document to be checked can be the same for several value documents to be checked one after the other, e.g. if a stack of value documents of the same value document type is checked. However, the information about the value document type can also vary from one value document to be checked to the next and can be transmitted to the sensor according to the invention by the other sensor which determines the value document type, individually, i.e. dynamically, for each of the value documents.

[0073] If the evaluation device has information about the value document type of the valuable document to be checked, it can determine the locations (partial images or raster points or their surrounding areas) of the valuable document image for which the respective local fiber characteristic value is determined, depending on the value document type of the valuable document to be checked. For example, the locations can be specifically determined in an unprinted or lightly printed area of ​​the valuable document, depending on the value document type. In particular, several locations are predefined in the evaluation device, and the evaluation device determines specific locations for evaluation from these predefined locations, depending on the value document type of the valuable document to be checked. The locations can, for example, be selected so that the unprinted / lightly printed area of ​​the respective valuable document is utilized as extensively as possible.The security document is then classified as suspected of being counterfeit only based on the local fiber characteristics of these locations, while other locations not intended for evaluation are ignored. In particular, the position and / or area and / or shape of the partial images can be selected depending on the type of security document being examined. The position and / or shape and / or area of ​​the partial images can also be the same for multiple security document types, e.g., for multiple denominations of the same currency.

[0074] To determine the position of the locations to be evaluated on the value document image, dynamic information about the transport position of the respective value document can be used, e.g., to specifically locate the unprinted or lightly printed area of ​​the value document. However, if the transport position of the value documents is fixed (as is the case with some value document processing devices), the position of the unprinted or lightly printed area is known in advance, and no dynamic information about the transport position of the respective value document is required to determine the position of the locations.

[0075] In particular, for the verification of valuable documents whose fibers are essentially evenly distributed across the (entire) valuable document, the sensor can have information about the average number or average areal density of fibers for one or more valuable document types. This information can differ for different valuable document types. And the evaluation device can be configured to determine or search for the average number or average areal density of fibers for the respective valuable document to be verified based on the information about the valuable document type of the valuable document to be verified and to define the surface area of ​​the partial images of the valuable document to be verified as a function of the average number or average areal density of fibers.For example, the surface area, the average number or average surface density of fibers can be determined to be so large that a minimum number of fibers is expected in the respective partial image. With a high surface density, partial images with a relatively small surface area are sufficient; with a low surface density, however, partial images with a relatively large surface area are necessary. The information about the average number of fibers or average surface density of the fibers on the value document, which the evaluation device has at its disposal, can be provided in the sensor or evaluation device itself or transmitted thereto by the value document processing device.

[0076] In a further development of the invention, the sensor is configured to record individual fingerprint data of the respective valuable document, such as can be used for tracing valuable documents, and possibly also for tracing the valuable documents themselves. Tracing valuable documents, in particular counterfeit or suspected counterfeit valuable documents, is performed, for example, to determine processing information of the respective valuable document, which can provide an indication of the origin or depositor of the respective (e.g., counterfeit or suspected counterfeit) valuable document.

[0077] The sensor, in particular the evaluation device of the sensor, can be configured to determine individual fingerprint data of the respective value document based on one or more properties of the fibers located in the value document image (e.g., concerning their position(s), distance(s), shape(s) or size(s), color(s) or brightness(ies)) and / or based on one or more of the local fiber characteristics of the respective value document, which it has determined for the various locations of the value document image (and, if applicable, their respective surroundings). These individual fingerprint data are unique for the respective value document and generally different for different value documents of the same value document type. The sensor, e.g., its evaluation device or another device of the sensor, can be configured to convert the individual fingerprint data of the respective value document into processing data of the respective value document (e.g.,concerning the origin of the value document and / or the denomination of the value document and / or the time and, if applicable, the location of the value document verification performed by the sensor) and to store them together with the processing data of the respective value document, e.g., in a list for multiple value documents, in a manner associated with each other, and to output them if necessary. The processing data of the respective value document may have been determined at least partially by the sensor itself or made available to the sensor from outside.

[0078] The individual fingerprint data of the respective value document relate, for example, to the number and / or positions and / or color location(s) and / or size(s) and / or local densities and / or fluorescence or phosphorescence properties of the fibers, of the value document image as a whole or of the respective location(s) of the value document image and, if applicable, its respective surroundings, e.g. one or more partial images of the value document image or one or more raster points with surrounding areas. The individual fingerprint data can, for example, comprise a vector whose coordinates are formed by the positions of all fibers in the value document image. Alternatively, the individual fingerprint data can also comprise a vector whose various coordinates are given by the local fiber characteristics, e.g. the local fiber densities, of the various locations and, if applicable, their surroundings on the value document image (e.g. the partial images orThe various coordinates of the vector can also be formed by different local fiber characteristics of one or more locations. Instead of a vector, however, a single local fiber characteristic or a single numerical value for the respective fiber property, e.g., the mean value of the respective property (e.g., color location, size, distances) of all fibers located in the value document image, can be used as individual fingerprint data.

[0079] In order to be able to use it for tracing purposes itself, the sensor can have an operating mode (different from the normal test mode) for tracing (genuine, counterfeit, or suspected counterfeit) valuable documents, in which the evaluation device is configured to determine the individual fingerprint data of a valuable document intended for tracing, of which the sensor records a valuable document image, for example based on the properties of the fibers located in the valuable document image of the valuable document intended for tracing and / or based on one or more local fiber characteristics of the valuable document intended for tracing. A list is available to the sensor for tracing purposes, in which processing information, e.g.about the origin of the respective valuable document and / or about the denomination and / or about the time and, if applicable, the location of the valuable document verification. The list may have been generated at least partially by the sensor itself, or it may have been supplied to it externally. Using the individual fingerprint data of the valuable document intended for traceability, the sensor can, in particular by looking up the list, determine processing data for the valuable document intended for traceability, in particular about the origin / denomination / time / location of the valuable document verification of the valuable document intended for traceability, and output this as the result of the traceability.

[0080] The invention also relates to a valuable document processing device comprising the described sensor and a transport device that places the respective valuable document into the detection range of the sensor. Alternatively, the valuable document can also be placed manually into the detection range of the sensor.

[0081] The invention also relates to a method corresponding to the above statements for checking a value document, in particular with the aid of the described sensor, wherein the value document has a plurality of fibers distributed over the value document. In the method, a value document is introduced into the detection range of a sensor and a value document image of the value document is captured using an image capture device of the sensor, wherein the value document image contains a characteristic optical or magnetic signal of the fibers. To evaluate the value document image, an evaluation device of the sensor is configured to localize the fibers contained in the respective value document image and to determine at least one local fiber characteristic value for one or more different locations in the value document image, which applies to the respective location and, if applicable, to an area surrounding the respective location on the value document image.The evaluation device is also configured to classify the value document as suspected of being counterfeit depending on the local fiber characteristic value(s) determined for the location(s) of the value document image.

[0082] To check a valuable document that has luminescent fibers distributed throughout the valuable document, the valuable document is placed in the detection area of ​​the optical sensor and illuminated there with the excitation light emitted by an illumination device of the sensor to optically excite the luminescent fibers of the valuable document, or is electrically excited there accordingly. Using the image capture device of the sensor, a luminescence image of the valuable document is then captured, with the luminescence of the luminescent fibers being included in the luminescence image. The evaluation device of the optical sensor then performs the aforementioned evaluation of the luminescence image.

[0083] The invention is described below by way of example with reference to the figures. They show: Fig. 1Schematic sketch of the structure of a value document processing device with an optical sensor for checking the value documents, Fig. 2a-cFiber distribution and possible partial image for a genuine banknote ( Fig. 2a,b ) and a related forgery ( Fig. 2c ), Fig. 3a-cFiber distribution and grid of predefined partial images on a genuine banknote ( Fig. 3a, 3d ) and in the case of an associated counterfeit ( Fig. 3b, 3c, 3e, 3f ), Fig. 4a-cFiber distribution and grid of predefined partial images on a genuine banknote ( Fig. 4a, 4c ) and in the case of an associated counterfeit ( Fig. 4b, 4d ), Fig. 5a-bFiber distribution and corresponding partial images of both opposite sides of a genuine banknote Fig. 6a-cLuminescence image that is systematically scanned in a grid of raster points ( Fig. 6a ), in which each localized fiber is assigned an area of ​​effect ( Fig. 6b ), where a surrounding area is defined around each grid point ( Fig. 6c ).

[0084] In the exemplary embodiments, the value document to be verified is a banknote with luminescent (e.g., fluorescent or phosphorescent) fibers and an optical sensor that records and evaluates a luminescent image of the banknote. However, the invention equally relates to the verification of banknotes with reflective or magnetic fibers or the verification of other value documents that have luminescent, reflective, or magnetic fibers. A magnetic sensor is used for the verification of magnetic fibers, which records and evaluates a magnetic signal image of the value document.

[0085] Fig. 1shows, by way of example, the schematic structure of a value document processing device 1 with an input compartment 2 in which a stack of banknotes 3 to be processed is provided, and a separator 8, by which one banknote at a time from the input stack is detected and transferred to a - only schematically shown - transport device 10 (transport belts and / or transport rollers), which transports the banknote past an optical sensor 25 for its checking in the transport direction x.

[0086] The optical sensor 25 has an optical image sensor 20, which converts the luminescence intensities emitted by the banknote being transported past into corresponding sensor signals. The optical excitation of the banknote's luminescence occurs, for example, by means of excitation light sources 27, 28 arranged on both sides of the image sensor 20. However, only one of the light sources can also be used. The image sensor 20 has, for example, one sensor row or several sensor rows, e.g. for different spectral components of the luminescence light. The sensor row(s) is / are arranged transversely to the transport direction x of the banknotes. The image sensor 20 is controlled by a control device (not shown) such that it detects the luminescence of the banknote at several detection times in order to optically scan the banknote being transported past. Detection areas of the banknote arranged adjacently along the transport direction are recorded one after the other.The successively recorded detection areas of the banknote each correspond to one pixel of the luminescence image.

[0087] The optical sensor 25 is arranged on the left side of the transport path, viewed in the transport direction x of the banknote. Opposite the optical sensor 25, on the right side of the transport path, another optical sensor 29 can be arranged, which also has an optical image sensor (not shown) and, if appropriate, illumination devices for optically exciting the banknote luminescence and, if appropriate, its own evaluation device. The luminescence image recorded by the optical image sensor of the opposite optical sensor 29 is, if appropriate, transmitted to the evaluation device 19 of the optical sensor 25 to enable a joint evaluation of both luminescence images of the same banknote.

[0088] The image sensor 20 forwards the recorded luminescence image to the evaluation device 19 of the optical sensor 25. The evaluation device 19 can be contained in the housing of the optical sensor 25 or externally thereof, e.g., in the value document processing device 1. The evaluation device 19 determines the respective local fiber characteristic value of one or more locations, e.g., one or more partial images, of the luminescence image recorded by the image sensor 20. Based on the local fiber characteristic values, the authenticity of the banknote is checked, and the banknote is classified as suspected of being counterfeit.

[0089] Information about the grid points or partial images and, if applicable, expected values ​​for one or more types of valuable documents can be stored in a data memory 26 of the evaluation device 19. Information about the type of valuable document to be checked and, if applicable, about the transport position of the valuable documents 3 can be transmitted to the evaluation device 19 from the control device 50 of the device 1.

[0090] Depending on the authenticity of the respective banknote determined by the evaluation device 19, the transport device 10 and the switches 4 and 5 along the transport path are controlled by the control device 50 such that the banknote is fed to one of several output compartments 30 and 31 and deposited there. For example, banknotes identified as genuine are deposited in a first output compartment 30, while banknotes classified as suspected counterfeit are deposited in a second output compartment 31. At the end of the transport path shown (reference number 6), further output compartments and / or other devices can be provided, for example for storing or destroying banknotes and / or a reject compartment into which banknotes are deposited for special handling, for example by an operator.

[0091] In the example shown, the value document processing device 1 further comprises an input / output device 40 for inputting data and / or control commands by an operator, for example by means of a keyboard or a touchscreen, and for outputting or displaying data and / or information relating to the processing process, in particular relating to the banknotes being processed. 1. Example

[0092] Figure 3a shows an example of the fiber distribution of luminescent fibers of a genuine banknote 80 of currency A, denomination 10. And Figure 3b shows an example of the fiber distribution of a composed counterfeit 66 for this banknote 80. The composed counterfeit 66 is a composition of a part 82 of a genuine banknote, which has an average fiber density of 1 / cm 2<, and a counterfeit part 62, which has no fibers at all.

[0093] For evaluation, the fibers are first located in the luminescence image recorded by the optical sensor 25. Then, the luminescence image is systematically scanned in a grid of, for example, 2x4 grid points. In the first embodiment, the fiber density is used as the local fiber characteristic value. For each grid point, the local fiber density is determined in a surrounding area surrounding the respective grid point, which corresponds to a partial image of the banknote image. In the example of the Fig. 3d,e,fThe surrounding areas / partial images 11-14, 21-24 are distributed across the banknote in a grid of 2 rows and 4 columns. The 8 grid points are located, for example, in the respective center of the respective surrounding area or partial image. In the evaluation device 19 of the optical sensor 25, the grid of partial images 11-14, 21-24 is fixed for several banknote types. The surface area of ​​the partial images is, for example, F=8cm 2< . It is assumed that the optical sensor 25 is set up to check banknotes of currencies A and D, in which all denominations have fibers with a uniform, but random, distribution across the banknote, with a certain average surface density (expected density value).

[0094] The optical sensor 25 receives information about the banknote type to be checked from the value document processing device 1 or from another sensor of the value document processing device 1. A table stored in the data memory 26 of the evaluation device 19 specifies which of the predetermined partial images 11-14, 21-24 are actually to be examined for the respective banknote type, see Table 1. For currency A, denomination 10, according to Table 1, all partial images of the 1st and 2nd columns are to be checked; for currency A, denomination 50, only 7 of the possible 8 partial images are to be checked (sub-image 24 is omitted). Using the information about the banknote type to be checked provided to the optical sensor 25, the evaluation device 19 can select one or more of the possible partial images for evaluation depending on the banknote type.

[0095] In Table 1, the expected density value DE of the fibers is also given for each banknote type. Table 1 for currencies A and D, denominations 10 and 50 respectively Density expectation value DE Drawings to be checked Currency A, Denomination 10 1 / cm 2< 11-14, 21-24 Currency A, Denomination 50 1 / cm 2< 11-14,21-23 Currency D, Denomination 10 5 / cm 2< 11-14, 21-24 Currency D, Denomination 50 2 / cm 2< 11-14, 21-24

[0096] The acceptable range of variation S for the fiber density can be calculated depending on the expected density value and the area or can be fixed, e.g. S=0.5 / cm 2< .

[0097] Based on the recorded value document image, the evaluation device 19 of the optical sensor 25 determines the number of fibers N in each of the partial images to be checked and, with the aid of the area F, calculates the respective fiber density D=N / F. It then compares this for each of the partial images to be checked with the respective expected density value DE, for currency A with DE=1 / cm 2< . This check is carried out to determine whether the fiber density D lies in the range DE+ / -S. For the case of currency A, denominations 10 and 50, for example, a check is carried out according to Table 1 to determine whether the fiber density in the partial images lies in the range E+ / -S= 1+ / -0.5 / cm 2<, i.e. between 0.5 / cm 2< and 1.5 / cm 2<. If this is the case, the respective partial image or banknote is classified as non-suspicious. If the fiber density D is greater or less than DE+ / -S, the respective partial image or banknote is classified as suspected of being counterfeit.

[0098] The composed forgery 66 from Fig. 3b, 3eis a composed counterfeit for currency A, denomination 10. According to Table 1, all partial images 11-14 and 21-24 are examined. In the two partial images 11 and 21, no fibers are found (fiber density D=0) and are therefore classified as suspect. In the partial images 12 and 22, the fiber density D is still within the acceptable range DE+ / -S, so that these are not classified as suspect. And in the partial images 13, 14, 23, and 24, a fiber density D is also found in the range DE+ / -S and these are classified as not suspicious. Due to the two partial images 11 and 21 being classified as suspicious, the composed counterfeit 66 is Fig. 3b, 3e classified as suspected of being counterfeit.

[0099] In the composed forgery 67 from Fig. 3c, 3fThis is a counterfeit of currency A, denomination 50. Both the genuine banknote and the counterfeit 67 have a luminescent security element in area 68. This outshines the luminescence of the luminescent fibers in the luminescence image. From Table 1, the evaluation device 19 of the optical sensor 25 determines that for currency A, denomination 50 - in contrast to denomination 10 of currency A - the fiber density is only checked in partial images 11-14 and 21-23, but not in partial image 24 (which lies in the area of ​​the luminescent element 68). The test results of partial images 11-14 and 21-23 correspond to those of the counterfeit 66 from Fig. 3b,3e .

[0100] If the transport position of the banknotes is variable, the sensor can receive information about the transport position of the banknote and, based on the transport position, determine in which partial images the fiber density should be checked. For this purpose, the information about the partial images to be checked for up to four transport positions of the respective banknote type can be stored in Table 1. During sensor adaptation, in order to create the thus expanded Table 1, it can be determined in which of the partial images 11-14, 21-24 the luminescent element 68 is located in the respective transport position and must therefore be omitted during the check. For example, in a different transport position of the composed counterfeit 67, in which the luminescent element 68 is in the bottom left of the luminescent image, partial image 21 would be omitted instead of partial image 24. 2. Example

[0101] Figure 2ashows, as an example, the fiber distribution of luminescent mottled fibers on a genuine banknote 70 of currency B. Banknote 70 has mottled fibers only in the left half, with an average areal density of 1 / cm 2< . The right half of banknote 70 has no mottled fibers. In this example, the sensor does not receive any information about the banknote type being checked, but is permanently tuned to currency B, whose denominations all have this fiber distribution.

[0102] Regardless of the type of banknote, a single partial image 11 is always defined in the left half of the banknote in the evaluation device 19 for all denominations of currency B, cf. Fig. 2b. Its surface area can be fixed, e.g., 10 cm 2< . However, it is also possible to select the surface area or size depending on the expected density value known for currency B (given by the known average surface density), which is stored in the evaluation device 19. Assuming the expected value E is to be 10, then, for an expected density value of 1 / cm 2<, a partial image 11 with an area of ​​10 cm 2< would be selected.

[0103] For evaluation, the fibers are first localized in the recorded luminescence image. In the second embodiment, the number of fibers located in a partial image is used as the local fiber characteristic value. Fig. 2cshows a counterfeit 64 of a banknote of currency B, which has no mottled fibers at all. In sub-image 11, the fiber count N=0 is then determined. However, since for currency B in sub-image 11 a fiber count of more than zero (E>0) is expected, the counterfeit 64 is Fig. 2c classified as suspected of being counterfeit.

[0104] In order to also find counterfeits with an incorrect number of fibers, a more precise test can be carried out in which the number of fibers N in the respective partial image is compared with the expected value E for the number: For a banknote to be checked, the number N of mottled fibers in partial image 11 is then determined and compared with the predetermined expected value, e.g. E=10. Preferably, the comparison does not require exact agreement with the expected value, but allows an acceptable fluctuation range S around the expected value E, e.g. S=5. The comparison checks whether the number of fibers N is in the range E+ / -S or not. If not, the banknote is classified as suspected of being a counterfeit; if yes, it is classified as not suspected of being a counterfeit.

[0105] In the concrete example, with E=10 and S=5, the banknote is classified depending on the number of fibers N as follows: If no or up to 4 mottled fibres are included (as in the case of counterfeit 64 from Fig. 2c ): suspected of being counterfeit If 5 to 15 mottled fibres are counted (as with the genuine banknote 70 from Fig. 2a,b ): not suspected of being counterfeit If more than 15 mottled fibres are counted: suspected of being counterfeit.

[0106] If the transport position of the banknotes is variable in the value document processing device, information about the transport position can be transmitted to the optical sensor 25, based on which the latter determines the position of partial image 11 such that partial image 11 lies in a banknote section in which the fibers are present in the genuine banknote 70. In the transport position from Fig. 2a,bThe partial image 11 is therefore placed in the left half of the value document image of the banknote 70. If the banknote 70 were in a different transport position, in which the fibers in the value document image are on the right, the partial image 11 would be placed in the right half of the value document image. 3. Example

[0107] In Figure 4a a genuine banknote 90 of currency C, denomination 50 is shown, which has fibers distributed approximately evenly over the banknote with an average areal density (expected density value) of 0.66 / cm 2<, which applies to all denominations of currency C.

[0108] And Figure 4b shows an example of the fiber distribution of a composed counterfeit 65 for banknote 90, in which a part 92 of a genuine banknote is combined with a counterfeit part 63, which has a lower fiber density than the genuine banknote. For example, the genuine part 92 has an average fiber density of 0.67 / cm 2 , while the counterfeit part 63 has an average fiber density of 0.1 / cm 2 .

[0109] Due to the known lower average areal density of the fibers, the evaluation device 19 defines partial images with a larger area for currency C than for currency A.

[0110] During sensor adaptation, a Table 2 was determined for each banknote type to be tested by the sensor. It contains a partial image definition (position and dimensions), an expected value E, and an acceptable fluctuation range S for each partial image (see Table 2). The respective area is determined by multiplying the partial image width dx and the partial image height dy. The partial images 11, 12, 21, and 22 in Table 2 all have the same shape and size (see Table 2). Fig. 4c . Table 2 for Currency C, all denominations Drawing number Partial image coordinates (x, y) (upper left corner) Partial image width dx in mm Partial image height dy in mm Expected value E Fluctuation range S 11 5,5 60 40 16 5 12 5,50 60 40 16 5 21 70, 5 60 40 16 5 22 70, 50 60 40 16 5

[0111] Due to the explicit partial image definitions in Table 2, different partial image sizes are also possible on the same banknote. The expected values ​​E and fluctuation ranges S are the same for all partial images 11, 12, 21, 22, since their surface areas are the same. However, they can also be different, e.g., in the case of partial images with different surface areas. For larger surface areas, a larger fluctuation range S can also be permitted. Corresponding tables for other denominations or currencies are also stored in the optical sensor 25, for which generally different numerical values ​​apply. For non-uniformly distributed fibers, such as in banknote 70 of currency B from Fig. 2a , the corresponding table would contain different expected values ​​E for different partial images.

[0112] The acceptable fluctuation range S can be specified in the table. It can also be calculated based on the expected value E, e.g., 40% of the expected value E, or it can be adjustable by the operator of the security document processing device.

[0113] The optical sensor 25 receives information about the banknote type to be checked, i.e., currency C and, if applicable, the denomination, from the security document processing device 1 or from another sensor. Using the information about the banknote type to be checked, the evaluation device 19 extracts from Table 2 the information about the partial images predetermined for the banknote type to be checked.

[0114] For evaluation, the fibers are again first located in the luminescence image recorded by the optical sensor 25. Based on the luminescence image recorded from the banknote to be checked, the number N of fibers in each of these partial images 11, 12, 21, 22 can be determined and compared with the respective expected value E+ / -S. In the example of currency C, denomination 10, a fiber count of E+ / -S in the range of 11 to 21 is expected in each of the partial images 11, 12, 21, 22. In the composed counterfeit 65 of the Fig. 4b, 4d In partial images 11 and 21, 18 mottled fibers are actually found, so these partial images are not classified as suspicious. In partial images 12 and 22, however, a small number of mottled fibers of 8 and 10, respectively, is found and is therefore classified as suspicious. Since at least one partial image is classified as suspicious (12 and 22), the composed forgery 65 is Fig. 4b, 4dclassified as suspected of being a composed forgery.

[0115] In addition to or alternatively to the number of fibers in the respective partial image, a characteristic of the fibers in the respective partial image can also be used as a local fiber characteristic, such as the length of the fibers, their aspect ratio (width-to-length ratio), the shape or color of the fibers, or the respective mean value of this characteristic across the respective partial image or the scatter of this characteristic around this mean value in the respective partial image. This allows for the identification of conspicuous partial images whose characteristics, mean values, or scatter deviates from a reference value (by more than an acceptable fluctuation range). And the valuable document is classified as suspected of being counterfeit if one or more conspicuous partial images are found in this respect. 4. Example

[0116] In the fourth embodiment, a banknote with fibers evenly distributed over the banknote is considered, such as the banknote 90 of currency C in Fig. 4a .

[0117] For evaluation, the fibers are again first located in the luminescence image recorded by the optical sensor 25 and the number N of fibers in each of the partial images 11, 12, 21, 22 is determined.

[0118] In contrast to the third embodiment, the expected value E for the fiber count is not stored in the sensor, i.e., it is not predefined, but is only determined when the respective banknote is examined. A relative examination of the fiber count of at least two different partial images is performed, with the fiber count of at least one specific partial image defining the expected value E for the other partial image(s).

[0119] For example, banknote 90 of currency C can be made from Fig. 4cThe fiber count of partial image 11 (e.g. N=18) determines the expected value E for the other partial images 12, 21 and 22, ie E=18. This is followed by a comparison of the fiber count N of partial images 12, 21, 22 with E=18. If the difference exceeds the acceptable range S (e.g., with S=4, a fiber count in the range 14-22 is expected), the banknote to be tested is classified as suspected of being counterfeit. For the counterfeit 65 from Fig. 4b, 4d the following results: Part 11: N=18, is defined as expected value E, Part 12: 10 fibers, suspected of being counterfeit, Part 21: 17 fibers, not suspected of being counterfeit, Part 22: 9 fibers, suspected of being counterfeit.

[0120] In the case of evenly distributed fibers and equal-area partial images, such as partial images 12, 12, 21 22 from Fig. 4c, 4d, the average fiber count of the other sub-images 12, 21, and 22 can also be used as the expected value for one of the sub-images: For example, the average fiber count of sub-images 12, 21, and 22 can be used as the expected value for sub-image 11, which in the above example results in E=12. With a fluctuation range of S=4, a fiber count of 8-16 is expected. The deviation in the fiber count in sub-image 11 (N=18) is then classified as suspicious.

[0121] In an additional test, the average fiber count of sub-images 11, 12, and 21 can be used as the expected value for sub-image 22, which in the above example results in E=15. With a fluctuation range S=4, a fiber count of 11-19 is expected, and the deviation from sub-image 22 (N=9) is classified as suspicious. 5. Example

[0122] In the fifth embodiment, a banknote with luminescent fibers is considered. Two luminescence images of this banknote are captured from opposite sides in the value document processing device 1, and the fibers imaged there are localized.

[0123] As an example, banknote 70 of currency B is taken from Fig. 2a which has luminescent fibers only in its left half. During the inspection in the value document processing device 1, the optical sensor 25 records a luminescent image of the banknote front side of the banknote 70, cf. Fig. 5a , and the opposite optical sensor 29 simultaneously records a luminescence image of the banknote back of the banknote 70, cf. Fig. 5b .

[0124] Since the luminescent light is typically strongly attenuated by the value document substrate, only the luminescent light of the fibers located on or immediately below the value document surface is detectable on the respective side, but not the luminescent light of the fibers located deeper in the substrate or on the other side of the value document. The luminescent fibers on the front side are therefore only visible in the luminescent image of the banknote front, but not in the luminescent image of the banknote back, and vice versa.

[0125] The examination of both opposing luminescence images enables a particularly accurate double-sided examination of the banknote, in which the local fiber characteristic value is determined for two corresponding partial images of the opposite sides of one and the same banknote section.

[0126] In the front image of banknote 70, for example, the number N1 of luminescent fibers is determined in a partial image 11, cf. Fig. 5a . In the reverse image of banknote 70, a partial image 11' is defined that is congruent with partial image 11 of the front image and covers exactly the same banknote section as partial image 11 of the front. Thus, partial images 11 and 11' show the front and back of one and the same banknote section. For example, the two partial images 11, 11' lie in the white field of banknote 70. A number N2 of luminescent fibers is determined for partial image 11' of the back.

[0127] The sum of the luminescent fibers in both partial images 11, 11' results in the total number (N total = N1 + N2) of fibers contained in the respective first partial image 11 and in the corresponding second partial image 11'. In the case of the genuine banknote 70, for example, a total of 20 fibers is expected for the total number of luminescent fibers (i.e., expected value E = 20). The tested banknote is then classified as suspected or not suspected of being counterfeit depending on the total number N total.

[0128] If, for example, in a composed forgery, the genuine banknote was replaced by a piece of paper without luminescent fibers in the left part of banknote 70, a corresponding total number of N total = 0 luminescent fibers would be determined in both partial image 11 and partial image 11', and the composed forgery would consequently be rejected. The total number N total of fibers can be compared with the expected value E=20, and if the deviation from E is too large (more than the acceptable fluctuation range S), it can be classified as suspected counterfeit, and if the deviation is only small, it can be classified as non-suspect counterfeit. However, other local fiber characteristics can also be used to check the corresponding partial images 11, 11'. 6. Example

[0129] In the sixth embodiment, the composed forgery 65 is Figure 4b considered a counterfeit of the banknote 90 from Fig. 4awherein a part 92 of a genuine banknote is combined with a counterfeit part 63 with lower fiber density.

[0130] For evaluation, the fibers are again first located in the luminescence image recorded by the optical sensor 25. Then, the luminescence image is systematically scanned in a grid of grid points R. In the example of the Fig. 6a The grid points R are distributed across the banknote in a grid of 3 rows and 9 columns.

[0131] The distance a of the respective grid point R to the nearest fiber is used as the local fiber characteristic value of the respective grid point, cf. Fig. 6a, and compared with a reference distance which is chosen depending on the expected density value DE of the fibres. Those raster points whose distance a is greater than the reference distance are classified as conspicuous. The value document is then classified as suspected of being counterfeit, for example depending on whether one or more conspicuous raster points are found in the banknote image, or for example depending on whether one or more conspicuous regions are found which have several conspicuous (e.g. a minimum proportion of conspicuous) raster points. The classification of the value document as suspected of being counterfeit can also be based on the position of the conspicuous raster points or regions on the value document.

[0132] In the example of the composed forgery 65 from Fig. 6aThe right two columns of grid points each contain many conspicuous grid points in this respect and form a conspicuous region. Composed forgery 65 is therefore classified as a suspected forgery. 7. Example

[0133] The seventh embodiment is also based on the grid points R described in the sixth embodiment, cf. Fig. 6b .

[0134] To evaluate the luminescence image, each localized fiber is assigned a (areal) effective area W, see the grey marked areas in Fig. 6b. The effective area W is an area around the respective fiber that is defined solely for the purpose of evaluation, but is not physically present on the value document. In the example shown, circular effective areas W are defined around the respective fiber that is located inside (e.g. in the center) of its assigned effective area W. The size or area of ​​the effective area W is preferably determined as a function of an expected density value DE of the fibers. For example, the area F of the effective areas W is selected using the formula F=K / DE, where K is a numerical factor. For example, with a numerical factor K=1, the effective area area can be selected to be so large that with a fiber density equal to the expected density value, the sum of the areas of all effective areas corresponds to the banknote area.

[0135] For example, the local fiber characteristic value used is the membership (yes / no) of the respective grid point R to one or more of the effective areas W around the fibers. For each grid point, it is checked whether it lies within one or more of the effective areas W or not. If yes, the respective grid point is classified as belonging to an effective area, and if no, the respective grid point is classified as not belonging to an effective area.

[0136] Then, one or more conspicuous regions of the value document image are searched for in which the number or proportion of raster points that were classified as not belonging to an area of ​​effect is larger than expected. In the example from Fig. 6aIn the two right-hand columns, which are in the counterfeit part 63 of the composed forgery 65, the proportion of grid points classified as not belonging to a functional area is 3 out of 4 grid points in each case, corresponding to 75%. This proportion is compared, for example, with a reference proportion (e.g. 50%), and if the reference proportion is exceeded, the respective column of the grid is classified as suspicious. The reference proportion can be predetermined or adjustable, or determined depending on the proportions of grid points in other banknote areas that do not belong to a functional area. For example, the proportion of grid points in the respective right-hand columns that do not belong to a functional area can be compared with the average proportion of grid points that do not belong to a functional area, which is determined for several of the left-hand columns of the grid.

[0137] The valuable document can then be classified as suspected of being counterfeit depending on whether one or more conspicuous columns are found. For example, the composed forgery 65 is classified as suspected of being counterfeit due to the two conspicuous right-hand columns. 8. Example

[0138] The eighth embodiment is also based on the grid points R described in the sixth embodiment and on the effective areas W used in the seventh embodiment.

[0139] Each of the raster points R is assigned a (flat) surrounding area 111-119, 121-129, 131-139, 141-149 around the respective raster point, which corresponds to a partial image of the banknote image, cf. Fig. 6c The surrounding areas 111-119, 121-129, 131-139, and 141-149 overlap with each other. The grid points R, for example, are located in the center of the respective surrounding area.

[0140] The local fiber characteristic value is the proportion of the area covered by at least one effective area W (grey or dark grey) or the area not covered by at least one effective area (white) in the respective surrounding area around the respective grid point. For this purpose, coverage areas can be identified in the respective surrounding area (in Fig. 6c grey or dark grey) that belong to the effective range of at least one of the fibres (these can be fibres inside or outside the respective surrounding area, some of whose effective range lies in the surrounding area). Alternatively or additionally, free areas (white) can be identified in the respective surrounding area that do not belong to the effective range of at least one of the fibres. Alternatively or additionally, overlapping areas can also be identified in the respective surrounding area in which the effective ranges of (neighbouring) fibres overlap (dark grey).

[0141] Based on the size of the respective coverage area and / or free area and / or overlap area, a local fiber characteristic value of the respective surrounding area is determined. The following can be used as a local fiber characteristic value, for example: the area share of the (grey) overlap areas in the respective surrounding area (e.g. percentage), or the area share of the (white) free areas in the respective surrounding area (e.g. percentage), or the area share of the (dark grey) overlap areas in the respective surrounding area (e.g. percentage), or the area of ​​the overlap areas and / or the area of ​​the free areas and / or the area of ​​the overlap areas.

[0142] The valuable document is then classified as suspected of being counterfeit depending on one or more of these proportions or surface areas determined for the examined surrounding areas of the valuable document.

[0143] For example, the respective proportion or surface area of ​​the respective surrounding area can be compared with a reference value, and if the reference value is exceeded, the respective surrounding area can be classified as suspicious. In the case of the composed forgery 65, for example, the surrounding areas 118, 119, 128, 129, 138, 139, 147, 148, and 149 are suspicious in this respect. The valuable document can then be classified as suspected of being counterfeit depending on whether one or more suspicious surrounding areas are found.

[0144] Alternatively, the mean of the proportions or areas of all surrounding areas of the security document image can be determined, and the scatter of the proportions or areas around this mean can be evaluated. If the scatter is too large, the security document would be rejected as suspected of being counterfeit.

Claims

1. Sensor (25) for verifying a value document which comprises a multiplicity of fibres distributed over the value document and which is brought into a capture region of the sensor for the purpose of verifying said value document, wherein the sensor comprises: - an image capture device configured to capture a value document image of the value document (3), wherein the value document image shows a characteristic optical or magnetic signal of the fibres, and - an evaluation device (19), which, for the purpose of evaluating the value document image, is configured - to localize the fibres contained in the respective value document image, and - to ascertain for a plurality of different locations of the value document image in each case at least one local fibre characteristic value which applies to the respective location and optionally to surroundings of the respective location on the value document image, wherein the evaluation device (19) has information about the value document type of the value document to be verified, the information being the currency or the denomination of the value document to be verified, and said evaluation device is configured to determine those locations of the value document image for which the respective local fibre characteristic value is determined depending on the value document type of the value document to be verified, and - to classify the value document (3) as suspected counterfeit or not suspected counterfeit depending on the at least one local fibre characteristic value.

2. Sensor (25) according to Claim 1, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured to scan the value document image point by point using grid points (R), wherein a local fibre characteristic value is ascertained for each grid point of the value document image, and to classify the value document (3) as suspected counterfeit depending on the local fibre characteristic values ascertained for the grid points.

3. Sensor (25) according to Claim 2, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured - to identify one or more conspicuous grid points which are conspicuous with regard to the local fibre characteristic value ascertained at the respective grid point, - to identify one or more conspicuous regions of the value document image in which conspicuous grid points are situated, and - to classify the value document as suspected counterfeit depending on one or more properties of the respective conspicuous region and / or depending on the local fibre characteristic values which were ascertained for the grid points of the respective conspicuous region.

4. Sensor (25) according to Claim 2 or 3, wherein the evaluation device (19), - for the purpose of evaluating the value document image, is configured to ascertain the local fibre characteristic value ascertained for the respective grid point of the value document image for a surrounding region (111-119, 141-149) assigned to the respective grid point, or, - for the purpose of evaluating the value document image, is configured to ascertain the respective local fibre characteristic value ascertained for the respective grid point of the value document image pointwise for the respective grid point.

5. Sensor according to any of the preceding claims, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured - to determine one or more partial images (11-14, 21-24, 111-119, 141-149) of the value document image, each of which contains a segment of the value document image, wherein the respective partial image of the value document image can be in particular a surrounding region around a respective one of the grid points according to Claim 4, - to determine the local fibre characteristic value for the respective partial image, - to classify the value document (3) as suspected counterfeit depending on the local fibre characteristic value(s) of one or more of the partial images.

6. Sensor (25) according to any of the preceding claims, wherein the local fibre characteristic value used is a measure of local density of the fibres, in particular - the number (N) of fibres situated in the surroundings of the respective location, in particular in the respective partial image (11-14, 21-24) or in the respective surrounding region (111-119, 141-149) around a grid point, or - the fibre density in the surroundings of the respective location, in particular in the respective partial image or in the respective surrounding region, or - a distance measure - which is characteristic of the distance between the fibres - of the fibres in the surroundings of the respective location, e.g. a mean distance of the fibres of the partial image or of the surrounding region from the fibre that is the most closely adjacent to the respective fibre.

7. Sensor according to either of Claims 5 and 6, characterized in that the evaluation device (19) is configured to determine at least two partial images of the value document image which together cover preferably at least 50% of the area of a value document side of the value document, particularly preferably at least 75% of the area of a value document side of the value document, wherein the partial images are arranged in particular in rows and / or in columns on the value document, wherein the partial images are arranged for example in a grid composed of at least two rows and / or at least two columns on the value document.

8. Sensor (25) according to any of the preceding claims, wherein the local fibre characteristic value used is a measure of the local constitution of the fibres at the respective location and optionally in the surroundings of the respective location, which concerns in particular the shape or size or colour or brightness of the fibres at the respective location and optionally in the surroundings of the respective location, wherein the local fibre characteristic value used is a representative value, e.g. a mean value, of the local constitution of the fibres at the respective location and optionally in the surroundings of the respective location.

9. Sensor (25) according to any of the preceding claims, which is configured, on the basis of one or more properties of the fibres localized in the value document image and / or on the basis of one or more of the local fibre characteristic values of the respective value document which were ascertained for the different location(s) of the value document image, to determine individual fingerprint data of the respective value document, to assign the individual fingerprint data to processing data of the respective value document and to store them together with the processing data of the respective value document, optionally in a list for a plurality of value documents, in each case in a manner assigned to one another.

10. Sensor according to any of the preceding claims, characterized in that the evaluation device (19) has information about the value document type of the value document to be verified and is configured to carry out the determining of the partial images depending on the value document type of the value document to be verified, wherein e.g. a plurality of partial images are fixedly predefined in the evaluation device and the evaluation device is configured to determine specific partial images for evaluation purposes from these fixedly predefined partial images depending on the value document type of the value document to be verified.

11. Sensor according to any of the preceding claims, characterized in that - the sensor is configured for verifying value documents of one or more specific value document types, the value documents of which comprise in each case at least one disturbing security element (68) which adversely affects the capture of the characteristic optical or magnetic signal of the fibres, and - the evaluation device (19) of the sensor is configured to classify the value documents of the specific value document type as suspected counterfeit depending on the at least one local fibre characteristic value of only one or more such locations of the value document image at which the capture of the optical or magnetic signal of the fibres is not adversely affected by the at least one disturbing security element (68).

12. Sensor (25) according to any of the preceding claims, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured - to assign an effect region (W) to each of the localized fibres, - for a plurality of different locations of the value document image to analyse in each case locally the effect regions of the fibres present at the respective location and optionally in the surroundings thereof, in particular with regard to the area covered or not covered by the effect regions (W) or with regard to the overlap of adjacent effect regions, and - to ascertain the respective local fibre characteristic value of the respective location on the basis of the local analysis of the effect regions (W) which lie at the respective location and optionally in the surroundings thereof, wherein the evaluation device (19), for the purpose of evaluating the value document image, is preferably configured to choose the size of the effect regions (W) in each case depending on an expected density value (DE) indicating the area density of the fibres that is expected for the value document image and optionally for the respective location of the value document image.

13. Sensor (25) according to Claim 10, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured - to assign an effect region to each of the localized fibres of the value document image or of the respective partial image or of the respective surrounding region and ∘ to identify coverage regions which belong to the effect region of at least one of the fibres, and / or ∘ to identify free regions which do not belong to any effect region of at least one of the fibres, and / or ∘ to identify overlap regions in which the effect regions of at least two adjacent fibres overlap, and - to identify one or more conspicuous regions of the value document image which are conspicuous with regard to their coverage regions and / or free regions and / or overlap regions, and - to classify the value document as suspected counterfeit depending on one or more properties of the coverage regions and / or the free regions and / or the overlap regions in / at one or more conspicuous regions of the value document image.

14. Sensor (25) according to any of the preceding claims, wherein the evaluation device (19), for the purpose of evaluating the value document image, is configured - for one or more locations of the value document image to compare the local fibre characteristic value of the respective location with an expected value, wherein the expected value, for the respective value document, and optionally for the respective location of the respective value document, ∘ is predetermined or ∘ the evaluation device (19) is configured to determine the expected value with which the local fibre characteristic value of the respective location is compared on the basis of the local fibre characteristic values which are ascertained for one or more other locations of the same value document image, and - to classify the value document (3) as suspected counterfeit depending on the comparison results obtained for one or more locations of the value document image, in particular depending on a difference established during the comparison between the local fibre characteristic value of the respective location and the expected value.

15. Sensor according to any of the preceding claims, characterized in that the value document image is a first value document image, which is captured from a first value document side of a value document (3) to be verified, and the evaluation device has a second value document image, which is or was captured from the second side - opposite the first side - of the same value document, and the evaluation device (19) is configured - to determine in each case at least one local fibre characteristic value for at least one first partial image (11) of the first value document image and for at least one second partial image (11') of the second value document image, and - optionally to combine the local fibre characteristic value of the first partial image and the local fibre characteristic value of the second partial image with one another or to compare these with one another, and - to classify the value document (3) as suspected counterfeit depending on the local fibre characteristic value of the first partial image and depending on the local fibre characteristic value of the second partial image, in particular depending on a result of the combination or depending on a result of the comparison, wherein the second partial image is preferably a second partial image which corresponds to the first partial image and which is a segment of the second value document image, wherein the first partial image and the corresponding second partial image contain the optical or magnetic signals of the front and rear sides of the same value document section of the value document (3).

16. Value document processing apparatus (1) comprising - a sensor (25) according to any of the preceding claims and - a transport device (10) for introducing the value documents into the capture region of the sensor (25).

17. Method for verifying a value document (3) with the aid of a sensor, in particular with the aid of the sensor according to any of Claims 1-15, wherein the value document comprises a multiplicity of fibres distributed over the value document, and wherein the following steps are carried out in the method: - introducing the value document (3) into the capture region of the sensor (25) and capturing a value document image of the value document with the aid of an image capture device of the sensor, wherein the value document image contains a characteristic optical or magnetic signal of the fibres, - evaluating the value document image with the aid of an evaluation device (19) of the sensor, which evaluation device, for the purpose of evaluating the value document image, is configured - to localize the fibres contained in the respective value document image, and - to ascertain for a plurality of different locations of the value document image in each case at least one local fibre characteristic value which applies to the respective location and optionally to surroundings of the respective location, wherein the evaluation device (19) has information about the value document type of the value document to be verified, the information being the currency or the denomination of the value document to be verified, and said evaluation device is configured to determine those locations of the value document image for which the respective local fibre characteristic value is determined depending on the value document type of the value document to be verified, and - to classify the value document (3) as suspected counterfeit or not suspected counterfeit depending on the at least one local fibre characteristic value.