EP3577635B1 - Verfahren zur verifizierung der authentizität eines empfindlichen produkts - Google Patents

Verfahren zur verifizierung der authentizität eines empfindlichen produkts Download PDF

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Publication number
EP3577635B1
EP3577635B1 EP18705689.0A EP18705689A EP3577635B1 EP 3577635 B1 EP3577635 B1 EP 3577635B1 EP 18705689 A EP18705689 A EP 18705689A EP 3577635 B1 EP3577635 B1 EP 3577635B1
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Prior art keywords
digital image
distinctive
sensitive product
original digital
point
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EP18705689.0A
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French (fr)
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EP3577635A1 (de
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Marc Pic
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Surys SA
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Surys SA
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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G07D7/202—Testing patterns thereon using pattern matching
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G07D7/202—Testing patterns thereon using pattern matching
    • G07D7/206—Matching template patterns

Definitions

  • a sensitive product includes an identifier, and corresponds for example to a bank note, a box of medicines, a luxury product, etc.
  • the identifier includes a set of characters, for example alphanumeric, kenji, etc.
  • the identifier is a serial number.
  • the identifier can be individual, that is to say specific to a given sensitive product.
  • the identifier can also be generic, that is to say specific to a set of sensitive products, for example a batch of medicines.
  • banknotes include a set of security elements, for example such as signs, watermarks, security thread, hologram, etc. which are incorporated in or on the banknotes during their manufacture.
  • US2012/324534 discloses the verification of a security document by comparing the scanned fingerprint of the person with that in the database.
  • US2014/055824 discloses verification of security documents with holograms.
  • WO2015/042485 discloses the verification of security documents by comparison of printed patterns.
  • An authentication solution is proposed here with simple and common optical equipment, allowing anyone to verify the authenticity of a sensitive product, in particular a bank note, in visible light.
  • the invention concerns, according to a first its objects, a method of verifying the authenticity of a sensitive product, as claimed in claim 1.
  • a step (1010) can be provided consisting of defining a set of remarkable points on the original digital image and on the test digital image of the sensitive product, each remarkable point being defined as a set of at least one pixel, that is, that is to say a single pixel or a set of adjacent pixels in pairs for which the contrast gradient is greater than a predefined threshold value, in at least one predefined direction and a predefined distance around said set of at least one pixel .
  • the step (1020) of calculating local collisions consists, for at least one remarkable point, of calculating a set of local histograms in a determined subset of the test digital image or the original digital image, said sub-set. -set comprising said remarkable point.
  • the metrology step (1030) consists of calculating the distance between a first remarkable point and a second remarkable point on at least one of the original digital image and the test digital image of the sensitive product.
  • a step (1040) can be provided consisting of associating in the database each original digital image with a plurality of corresponding attributes, said attributes comprising at least one of: the coordinates of remarkable points, the distances between certain remarkable points , contrast gradient values around remarkable points, or other notable characteristics such as mathematical moments of certain parts of the image.
  • a step (1050) can be provided consisting of associating, in the database, a validity attribute with at least one of the original digital images.
  • the comparison step (1150) is bypassed depending on the value of the validity attribute.
  • the acquisition step (1100) is implemented using a sensor of an optical lens of a communicating object.
  • said subset of the test digital image or the original digital image has a predetermined geometric shape whose value of the surface is predetermined or function of a predetermined gradient of contrast, color or intensity around said remarkable point.
  • the invention relates to a computer program comprising program code instructions for executing the steps of the method according to the invention, when said program is executed on a computer.
  • a sensitive product 100 in this case a bank note (specimen) is illustrated on the figure 1 .
  • the banknote is flat and rectangular.
  • the banknote includes a set of security elements, in particular graphic or optical.
  • the banknote notably comprises a security thread 130, which is integrated into the paper pulp of said banknote and which is optically visible by a local contrast effect.
  • the position of a security thread is not necessarily the same between two banknotes of the same monetary value.
  • a security thread when manufacturing a bank note, it can be provided that it includes a graphic window whose width is that of said note, whose length is at most that of said note, and in the plane of said note, within which the position of the security thread is random, said security thread being generally rectilinear, and in particular in the direction of the width of the note.
  • the banknote also includes a watermark 110, illustrated in particular by the number “20” on the figure 1 and which is optically visible by a local contrast effect.
  • the sensitive product includes an identifier 120, typically composed of alphanumeric characters, for example incremented, and in this case a serial number. Particularly for banknotes, the identifier is not printed offset. Generally, it is printed with dark ink, in this case black, on a light background.
  • the identifier defines a foreground and the background defines a background, it is optically visible by a local contrast effect.
  • the identifier can be recognized by optical character recognition.
  • the sensitive product is at least partially planar, that is to say it is planar or comprises at least one planar face supporting said identifier.
  • the flat surface supporting said identifier is a surface on which said identifier is integrated, affixed, glued, printed, etc. either directly on the sensitive product, or on the packaging of said sensitive product, in particular on the part of the packaging covering said surface.
  • a step is provided consisting of producing a digital image of said sensitive product, that is to say at least of the flat face supporting said identifier.
  • the image produced is in high definition and stored in a secure database.
  • Said digital image is called an “original digital image”, as opposed to a “test digital image” described later.
  • a step is provided consisting of optically recognizing (OCR) the characters of the identifier in the original digital image of a sensitive product, typically using a scanner.
  • OCR optically recognizing
  • optically recognized identifier is recorded in digital format and associated with the original digital image of said sensitive product in the database, which allows for example indexing thereof.
  • each character of the identifier is graphically defined by a set of printing points.
  • the ink used for printing is dark, usually black.
  • the color of the background on which each character is printed is lighter than that of the ink, so that the character is readable on said background thanks to a local contrast effect.
  • the background on which the identifier is printed is not uniform and may include a set of patterns 150, which may be security or decorative graphic elements; and each pattern 150 of the background of the sensitive product presents a local contrast effect.
  • the identifier is unique. However, for various reasons, it happens that several sensitive products have the same identifier, for example several bank notes of the same monetary value have the same serial number. It is estimated that a maximum of twenty banknotes of the same monetary value can have the same serial number.
  • two banknotes presenting the same identifier in fact present a set of at least one difference in at least one of the security elements or the background.
  • the position of the identifier on the background is different, or the pattern of the background is different, etc.
  • each sensitive product is actually graphically unique. It therefore has a fingerprint, that is to say a set of attributes (notably optical, graphic and geometric) which give it its uniqueness.
  • a fingerprint that is to say a set of attributes (notably optical, graphic and geometric) which give it its uniqueness.
  • the (optical) fingerprint of the sensitive product can be extracted from the original digital image to identify and authenticate said sensitive product as described later.
  • a step 1000 is provided consisting of extracting at least one optical imprint from the original digital image of the sensitive product scanned, that is to say calculating the attributes which contribute to its unique character, from the digital image in the database or before its storage therein. We can then associate said fingerprint with said original digital image in the database.
  • each original digital image is associated 1040 with a plurality of corresponding attributes, all of the attributes of a given original image making it possible to characterize it at least in part.
  • the attributes include, for example, the coordinates of remarkable points (described below), the distances between certain remarkable points, contrast gradient values around the remarkable points, etc. or other notable characteristics such as mathematical moments of certain parts of the image as described below.
  • the extraction of the fingerprint of the sensitive product is implemented automatically and preferably comprises at least one of the steps among: a local collision calculation step and a metrology step.
  • a step 1010 consisting of defining, or identifying, a set of remarkable points on the digital image (original or test) of the sensitive product.
  • a remarkable point is defined as a point in the digital image of the sensitive product, that is to say a pixel or a set of adjacent pixels two by two, for which the contrast gradient, according to a predefined direction and distance , is greater than a predefined threshold value.
  • the predefined direction is horizontal and/or vertical.
  • a first notable point belongs to the foreground.
  • a first remarkable point is a printing point of a character of the identifier.
  • a second remarkable point belongs to the foreground or the background (fond).
  • a second remarkable point is a point on the outline of a graphic element of the background pattern.
  • a set of remarkable points can be defined or identified according to the FAST algorithm (for Features from Accelerated Segment Test in English), for example such as described in the article by Edward Rosten and Tom Drummond “Machine learning for high-speed corner detection” (2006) published at https://www.edwardrosten.com/work/rosten_2006_machine.pdf.
  • a step 1020 of calculating local collisions can be provided on the original digital image of the sensitive product.
  • the step of calculating local collisions consists, for at least one remarkable point, of calculating a set of local histograms in a determined subset of the digital image, said subset being a part of the digital image which comprises said remarkable point, which has a predetermined geometric shape and whose surface value is predetermined or a function of a predetermined gradient of contrast, color or intensity around said remarkable point.
  • any predetermined geometric shape can be provided. This is recorded in a memory.
  • the surface value of the predetermined shape can also be predetermined and stored in said memory.
  • the geometric shape is a circle centered on said remarkable point, and whose radius is a function of the chosen gradient, which simplifies the calculations and therefore increases the processing speed.
  • Local histograms are calculated in a number of predetermined directions.
  • SIFT Scale Invariant Feature Transform
  • SURF Speeded Up Robust Features
  • the detection of points is based on the differences of the Gaussians (DoG) obtained by calculating the difference between each pair of images smoothed by a Gaussian filter, by varying the sigma parameter each time (i.e. the deviation standard) of the filter.
  • DoG can be calculated for different scale levels allowing the notion of scale space to be introduced.
  • the detection of potential areas of points of interest / remarkable points is carried out by searching for the extrema according to the plane of the dimension of the image (x,y) and the plane of the scale factor. Then a filtering step is necessary to remove irrelevant points, for example by eliminating points whose contrast is too low.
  • the calculation of the SIFT descriptor is carried out on an area around each point of interest, for example 16x16 pixels, subdivided into 4x4 zones of 4x4 pixels. On each of the 16 zones, a histogram of the gradient orientations based on 8 intervals is then calculated. The concatenation of the 16 histograms gives a descriptor vector of 128 values.
  • the method consists of using the determinant of the Hessian matrix, calculating an approximation of the second derivatives of the Gaussians of the image through filters at different scales using masks of different sizes (for example 9x9, 15x15, 21x21, ).
  • the principle is based on the sums of the responses of the horizontal and vertical Haar wavelets as well as their norms.
  • the circular description area is again divided into 16 regions.
  • a wavelet analysis is performed on each region in order to construct the final descriptor.
  • the latter is made up of the sum of the gradients in x and y as well as the sum of their respective norm for all 16 regions.
  • the descriptor vector is thus made up of 64 values which represent properties extracted both in normal space and in that of magnitude scales.
  • Each subset corresponds to a single fingerprint.
  • a metrology step 1030 consisting of calculating the distance between a first remarkable point and a second remarkable point on the original digital image of the sensitive product.
  • the distance between the first remarkable point and the second remarkable point is greater than a first threshold value recorded in a memory, and less than a second threshold value recorded in said memory.
  • the first threshold value ensures that the two remarkable points are not too close to each other; the second threshold value ensures that the two remarkable points are not too far from each other.
  • the first remarkable point is located on one of the characters of the identifier of the sensitive product.
  • the second remarkable point is located on a security wire of said sensitive product.
  • the second remarkable point is located on an edge of said sensitive product or on an edge of the face supporting said identifier.
  • the second remarkable point located on the contour of a pattern of the background of the face supporting said identifier.
  • the distance between two remarkable points is illustrated by a double arrow.
  • the first remarkable points are located on the character outline of the identifier, in this case the digits 04 of the serial number of a bank note; and at the other end of the double arrows, the second remarkable points are located on the outline of a character in the background (in this case the letter R which appears slightly in the background, with guilloches).
  • the previous variants can be combined with each other. We can calculate the distance between a first and a second remarkable point, and calculate the distance between the first remarkable point and a third remarkable point different from the second.
  • the first remarkable point and the second remarkable point are aligned on a horizontal straight line, or on a vertical straight line, so that the distance is calculated in the horizontal direction and/or in the vertical direction, in one direction or in the 'other, the horizontal and the vertical being defined typically by the reading direction.
  • At least one of the distances calculated for the sensitive product is recorded and associated with the original digital image of said sensitive product in the database.
  • a step 1100 is provided for acquiring a digital image of said sensitive product, typically using an optical lens of a communicating object, said sensitive product being preferably planar and comprising a surface supporting an identifier. Said digital image is called a “test digital image”.
  • communicating object we mean any object, preferably portable, equipped with an optical lens, a processor and a memory, and capable of establishing communication, radio or otherwise, with the database.
  • the communicating object is a mobile phone, a smart phone - or Smartphone by Anglicism, a PDA, a tablet, etc., a personal computer or an automatic bank note sorter.
  • test image of said sensitive product comprising said identifier then undergoes a digital processing step, which aims to compare said test image to a corresponding original digital image and which can be implemented on the communicating object or, preferably, on a remote server.
  • the remote server is the server hosting the database, or a server in communication with it and with the communicating object, which limits the risks of hacking the communicating object.
  • the digital processing step includes an optical character recognition (OCR) step 1110 consisting of recognizing the characters of the identifier of said sensitive product.
  • OCR optical character recognition
  • a step 1140 is then provided consisting of identifying in the database a set of at least one original digital image corresponding to the characters of the optically recognized identifier.
  • the digital processing state also includes a step 1120 consisting of extracting an optical print from the test digital image, in a manner identical to the extraction of an optical print from the original digital image, that is to say according to steps 1010, 1020, 1030 previously described.
  • the optical fingerprint of the test digital image is then compared 1150 to each optical fingerprint of the set of at least one original digital image. If several optical fingerprints of the digital test image are calculated, it can be planned to compare each optical fingerprint of the digital test image with each optical fingerprint of the original digital image.
  • a value of said attribute means that the sensitive product at the origin of said original digital image is considered to be invalid, for example because it has been withdrawn from circulation or declared stolen.
  • the comparison step is short-circuited as a function of the value of said attribute, that is to say if the sensitive product at the origin of said original digital image is considered to be invalid.
  • the calculation of local collisions can advantageously be carried out on a support (bank note, packaging) that is wrinkled or whose edges are damaged.

Claims (10)

  1. Verfahren zur Überprüfung der Echtheit eines empfindlichen Produkts, wobei das empfindliche Produkt eine Kennung umfasst, die eine Menge von Zeichen umfasst, dadurch gekennzeichnet, dass das Verfahren Schritte umfasst, die darin bestehen:
    - ein digitales Testbild zu erfassen (1100), das die Kennung des empfindlichen Produkts umfasst;
    - Zeichen der Kennung optisch zu erkennen (1110),
    - eine Menge von markanten Punkten auf dem digitalen Originalbild und auf dem digitalen Testbild des empfindlichen Produkts zu definieren (1010), wobei ein markanter Punkt als ein Punkt des digitalen Bildes des empfindlichen Produkts definiert ist, d. h. ein Pixel oder eine Menge aus paarweise benachbarten Pixeln, bei dem der Kontrastgradient gemäß mindestens einer vorgegebenen Richtung und einem vorgegebenen Abstand um die Menge aus mindestens einem Pixel herum größer als ein vorgegebener Schwellenwert ist,
    - einen optischen Abdruck des digitalen Testbildes zu extrahieren (1120),
    - an einen entfernten Server, der eine Datenbank umfasst, die eine Menge digitaler Originalbilder von empfindlichen Produkten umfasst, mindestens eines der folgenden Elemente zu senden (1130):
    o die optisch erkannten Zeichen der Kennung,
    o den extrahierten optischen Abdruck des digitalen Testbildes und
    o das digitale Testbild,
    - in der Datenbank eine Menge aus mindestens einem digitalen Originalbild zu identifizieren (1140), das dem digitalen Testbild entspricht,
    - einen optischen Abdruck des entsprechenden digitalen Originalbildes zu extrahieren (1000) und
    - den optischen Abdruck des digitalen Testbildes und den optischen Abdruck des digitalen Originalbildes zu vergleichen (1150),
    bei dem:
    - der Schritt (1120), der darin besteht, einen optischen Abdruck des digitalen Testbildes zu extrahieren, auf identische Weise im Schritt (1000) durchgeführt wird, der darin besteht, einen optischen Abdruck des digitalen Originalbildes zu extrahieren,
    - der Schritt des Extrahierens (1000, 1120) mindestens einen der folgenden Schritte umfasst:
    - einen Schritt (1020) des Berechnens lokaler Kollisionen, der für mindestens einen markanten Punkt darin besteht, eine Menge lokaler Histogramme in einer bestimmten Teilmenge des digitalen Bildes zu berechnen, wobei die Teilmenge ein Teil des digitalen Bildes ist, das den markante Punkt umfasst, und
    - einen Metrologieschritt (1030), der darin besteht, den Abstand zwischen einem ersten markanten Punkt und einem zweiten markanten Punkt auf dem digitalen Originalbild oder auf dem digitalen Testbild zu berechnen.
  2. Verfahren nach Anspruch 1, bei dem
    beim Schritt (1020) des Berechnens lokaler Kollisionen die Teilmenge, die den markanten Punkt umfasst, eine vorbestimmte geometrische Form aufweist, bei welcher der Wert der Fläche vorbestimmt ist oder von einem vorbestimmten Kontrast-, Farb- oder Intensitätsgradienten um den markanten Punkt herum abhängig ist.
  3. Verfahren nach Anspruch 2, bei dem die geometrische Form ein auf den markanten Punkt zentrierter Kreis ist.
  4. Verfahren nach einem der vorhergehenden Ansprüche, bei dem beim Metrologieschritt (1030) der Abstand zwischen dem ersten markanten Punkt und dem zweiten markanten Punkt größer als ein erster Schwellenwert ist, der in einem Speicher gespeichert ist, und kleiner als ein zweiter Schwellenwert ist, der in dem Speicher gespeichert ist.
  5. Verfahren nach einem der Ansprüche 2 bis 4, das einen Schritt (1040) umfasst, der darin besteht, in der Datenbank jedes digitale Originalbild mit einer Mehrzahl entsprechender Attribute zu verknüpfen, wobei die Attribute mindestens eines der folgenden Elemente umfassen: die Koordinaten von markanten Punkten, die Abstände zwischen bestimmten markanten Punkten und Kontrastgradientwerte um markante Punkte herum oder aber weitere bemerkenswerte Merkmale wie mathematische Momente bestimmter Teile des Bildes.
  6. Verfahren nach einem der vorhergehenden Ansprüche, das einen Schritt (1050) umfasst, der darin besteht, in der Datenbank ein Gültigkeitsattribut mit mindestens einem der digitalen Originalbilder zu verknüpfen.
  7. Verfahren nach Anspruch 6, bei dem der Schritt des Vergleichens (1150) in Abhängigkeit vom Wert des Gültigkeitsattributs umgangen wird.
  8. Verfahren nach einem der vorhergehenden Ansprüche, bei dem der Schritt des Erfassens (1100) dank eines Sensors eines optischen Objektivs eines kommunizierenden Objekts durchgeführt wird.
  9. Verfahren nach einem der vorhergehenden Ansprüche, das ferner einen Schritt umfasst, der darin besteht, den optischen Abdruck des digitalen Originalbildes mit dem digitalen Originalbild in der Datenbank zu verknüpfen; und
    Schritte, die darin bestehen, in der Datenbank mindestens eines der folgenden Elemente zu speichern und mit jedem digitalisierten empfindlichen Produkt zu verknüpfen:
    - den Wert der lokalen Histogramme,
    - die Art und Weise, wie die lokalen Kollisionen berechnet worden sind, und
    - die Position der markanten Punkte.
  10. Verfahren nach einem der vorhergehenden Ansprüche, bei dem ein erster markanter Punkt ein Druckpunkt eines Zeichens der Kennung ist und ein zweiter markanter Punkt dem Vordergrund oder dem Hintergrund angehört.
EP18705689.0A 2017-01-31 2018-01-29 Verfahren zur verifizierung der authentizität eines empfindlichen produkts Active EP3577635B1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1750810A FR3062509B1 (fr) 2017-01-31 2017-01-31 Procede de verification de l’authenticite d’un produit sensible.
PCT/FR2018/050200 WO2018142054A1 (fr) 2017-01-31 2018-01-29 Procede de verification de l'authenticite d'un produit sensible.

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EP3577635B1 true EP3577635B1 (de) 2024-02-28

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2952738B1 (fr) * 2009-11-17 2012-01-13 Advestigo Procede et systeme de controle automatique et d'authenticite d'un document d'identite
FR2973137B1 (fr) * 2011-03-25 2015-07-24 Hologram Ind Procede et systeme d'authentification d'un document securise
MX2016003537A (es) * 2013-09-20 2016-06-28 Mobile Search Security LLC Sistema de autenticacion de instrumentos y documentos.

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FR3062509B1 (fr) 2020-10-23
WO2018142054A1 (fr) 2018-08-09
EP3577635A1 (de) 2019-12-11

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