Method and system for generating a surface signature - Patents.com

Abstract

1. A method for generating at least one digital signature of at least one surface of a material element, referred to as a "test surface," the method being performed by a data processing system, the method comprising, for each test surface: - an acquisition step (E30) for obtaining an "offset" image having at least a portion showing the inspection surface; an acquisition step (E50) for obtaining at least one region of interest in the offset image by matching the offset image with at least one predetermined "equivalent" region contained in the model image, the at least part of which represents a "reference" surface, by a method known as "template matching"; an acquisition step (E70) for obtaining a "registered" image by registering the offset image with the model image, the registration being performed by applying a first perspective transformation to the offset image, the first perspective transformation being obtained from at least one region of interest and at least one equivalent region; and - a generation step (E90) for generating a digital signature from the aligned image, the digital signature characterizing the structure of the test surface; Equipped with. [Selected figure] Figure 3

Description

[Technical field]

[0001] The present invention is in the general field of generating digital signatures for surfaces of material elements, for example for authenticating said surfaces or said material elements.

[0002] The digital signature of a surface corresponds to a code (eg, a series of numbers and letters) that is algorithmically generated from structural features of that surface.

[0003] More specifically, the invention relates to performing a correction de perspective between an image representing the surface of a material element and a model image of a reference surface in order to retrieve a digital signature of the material element. [Background technology]

[0004] It is now possible to extract a digital signature from a surface based on structural features of that surface, for example identified by detecting interactions between the surface and a light source in an image of the surface. For example, such a method is described in EP1716520.

[0005] Furthermore, the technique described in EP2084886B1 proposes associating a mobile system including a sensor, for example a smartphone including a camera, with an optical module, the optical module being for example integrated into the housing of the phone.

[0006] The above technique makes it possible to obtain a control image of a surface (the surface is arranged in a particular way in the image) and to extract from that image a digital signature of the surface.

[0007] An image of a surface is acquired by placing the phone and housing assembly against the surface such that the optical distance between the surface and the camera sensor is controlled.

[0008] During acquisition, the surface is illuminated by a light source, preferably inclined with respect to the normal to the surface.

[0009] Finally, structural features are obtained by detecting interactions between the surface and the light source in the acquired image.

[0010] A drawback of the above system is that it requires the use of an optical module to control the distance between the surface and the sensor acquiring the image, so that the surface is positioned in a predetermined manner in the image. Summary of the Invention

[0011] The present invention aims to provide a solution that does not have the above mentioned drawbacks and that allows a digital signature to be extracted from a surface by using an image of the surface, the surface being positioned and inclined in any way relative to the acquisition plane of the image.

[0012] In a first aspect, the invention provides a method for generating digital signatures of surfaces of material elements, called "surface examinee", performed by a data processing system, comprising for each examinee surface: - an acquisition step for obtaining an "offset" image having at least a portion representative of said test surface; an acquisition step for obtaining zones of interest in the offset image by matching the offset image with predefined "equivalent" regions contained in a model image, the "equivalent" regions having at least a part representing a "reference" surface, a method known as "template matching"; - an acquisition step for obtaining a "registered" image by registering the offset image with the model image, the registration being performed by applying a first perspective transformation to the offset image, the first perspective transformation being derived from the region of interest and the equivalent region; and - a generation step for generating a digital signature from the aligned images, the digital signature characterizing the structure of the test surface.

[0013] In the sense of the present invention, a surface corresponds to a visible part (i.e. a defined area) of a material element (i.e. an object). This material element or object may for example be a product. For example, the product may be something that is sold and in its packaging. This material element or object may for example correspond to a security document, such as an identity document, a passport, a banknote, etc.

[0014] The "test" surface corresponds to a surface of the material element / object. The "test" surface corresponds to a surface used in the method and thus corresponds to a surface visible in the offset image. The "test" surface may be a part of a larger surface of the material element.

[0015] The "reference" surface corresponds to a surface of a predefined material element / object, for example the reference surface corresponds to the surface from which the digital signature is taken and retained.

[0016] The digital signature of a surface corresponds to a code (eg, a series of numbers and letters) that is algorithmically generated from structural features of the surface.

[0017] A digital signature of a surface describes (i.e., characterizes) the structure of the surface, and may characterize the condition of the surface, the internal and / or external morphology of the surface, the chemical or physicochemical composition of the surface, the color of the surface, or the changes in any combination of these features as a function of their physical location on the surface.

[0018] Hereinafter, the term "digital signature" may be equivalently replaced by the term "signature".

[0019] A digital signature may be said to be "generated" by the method. Alternatively, a digital signature may be said to be "derived" by the method.

[0020] In the method, first an "offset" image of the test surface is obtained, either a portion of the image showing the test surface or the entire image showing the test surface.

[0021] The image is said to be "offset" because it is preferable that the image is aligned so that a signature can then be generated / retrieved for the surface represented.

[0022] For example, an offset image representing a surface may correspond to an image of a flat surface that is a plane that is tilted relative to the plane of acquisition of the image, e.g., when an image of a flat surface is acquired by a sensor, the image of the flat surface is said to be offset when the optical axis of the sensor forms a non-zero angle with the normal to the surface.

[0023] Once the offset image is obtained, one or more regions of interest are obtained in the image. A region of interest in an image may correspond to a series of adjacent or even adjacent points in the image. For example, a region of interest may comprise all of the points forming a particular quadrilateral in the image, or a series of points contained in such a quadrilateral.

[0024] These regions of interest are derived based on predefined "equivalent" regions within a "model" image having at least a portion that represents a "reference" surface.

[0025] Each region of interest is obtained by a method of matching an equivalent region with an offset image. Matching may be referred to as "image matching" or "template matching" and may be performed by various image analysis methods, such as least squares or cross-correlation. Matching an equivalent region with an offset image generally serves to identify a region in the offset image that has characteristics similar or close to those of the equivalent region. Typically, the region of interest and its equivalent region may represent the same object or the same part of an object in two images acquired at different angles of view.

[0026] From the region of interest in the offset image and the equivalent region in the model image, a first perspective transformation is deduced, which serves to register the acquired image onto the model image.

[0027] This alignment accommodates the perspective correction between the two images and serves to simulate the situation of a replacer of the test surface of the offset image in the same plane and orientation as the plane with the reference surface of the model image.

[0028] By applying the above perspective transformation to the offset image, a "registered" image of the test surface is obtained, from which the signature of the surface can be extracted.

[0029] Advantageously, from an image showing a tilted surface and arranged in an arbitrary manner, a signature of the surface can be generated by simulating the surface being oriented in a suitable plane.

[0030] In a specific implementation, obtaining the offset image includes obtaining a "capture" image. The offset image is obtained from the capture image.

[0031] The captured image may also represent all or a portion of the inspected surface.

[0032] In a specific implementation, hereinafter referred to as the "first general implementation", the offset image corresponds to the acquired image, and the signature is generated by analyzing the aligned images in a generation process.

[0033] Advantageously, the alignment of the offset image corresponding to the acquired image is performed by image processing (perspective correction by applying a perspective transformation) and thus does not require the use of a special optical system associated with the acquisition module that acquires the "acquired" image (first acquisition module in the sense of the invention) in order to set the plane of the test surface to a desired plane so that the signature can be extracted from the test surface. The image of the test surface can be acquired with the first acquisition module located at any distance and in any orientation relative to the test surface.

[0034] In a specific implementation, the method includes a preliminary step of defining equivalent regions in the model image.

[0035] In a specific implementation, hereinafter referred to as the "second general implementation", the method includes a preliminary step of acquiring an "orientee" image of the reference surface using a second acquisition module arranged substantially perpendicular to the reference surface. The model image is obtained by applying a second predetermined perspective transformation to the oriented image.

[0036] In this implementation, the "oriented" image is acquired using a second acquisition module having an optical axis arranged substantially perpendicular to the reference surface.

[0037] Typically, a manufacturing line repeatedly employs a capture that is substantially perpendicular to the surface of the product or product's packaging.

[0038] The oriented image is transformed to simulate acquisition of an image of the reference surface under conditions different from those under which the oriented image is acquired, e.g., at a different angle, a different direction, and / or a different distance.

[0039] This transformation corresponds to applying a second perspective transformation to the oriented image, resulting in a model image with which the offset image is aligned.

[0040] Advantageously, applying said second perspective transformation serves to obtain a model image having a reference surface with a tilt and position close to the tilt and position of the test surface in the offset image.

[0041] This step serves to optimize the process of aligning the offset image with the model image, for example by making it possible to obtain a better estimate of the first perspective transformation or by avoiding obtaining a singular estimate of said perspective transformation.

[0042] For example, an oriented image of a reference surface acquired at a production line may be transformed in a manner that simulates acquisition of an image of this reference surface using a mobile system such as a phone or tablet, where the alignment or perspective correction between the offset image and the model image is improved if the offset image is acquired using a mobile system such that its orientation and position relative to the inspection surface is similar or close to that of the model image obtained after transformation.

[0043] In a specific implementation example of the second overall implementation example (wherein the model image is obtained by applying a second perspective transformation to the oriented image), the step of generating a digital signature includes an acquisition step to obtain a "transformed" image by transforming the aligned image by applying the inverse of the second perspective transformation to the aligned image, and the signature is generated by analyzing the transformed image in the generation step.

[0044] In this implementation, the model image is obtained by applying a second perspective transformation to the oriented image, and the offset image is aligned with the model image to obtain an aligned image. Finally, the inverse of the second perspective transformation is applied to the aligned image to obtain a transformed image. The transformed image is aligned with the oriented image.

[0045] The signature is extracted from the test surface by using the transformed image, provided that the position and orientation of this surface resembles the position and orientation of a reference surface placed in the oriented image.

[0046] In this implementation, the offset image is aligned (perspective corrected) and then the inverse of the second perspective transform is applied to align the aligned image with the oriented image.

[0047] Alternatively, in a second general implementation example, the aligned image is obtained by applying an inverse perspective transform of the second perspective transform to the acquired image, and the signature is generated by analyzing the aligned image in a generation process.

[0048] In this implementation, a second perspective transformation is also applied to the oriented image, which makes it possible to obtain a model image, while the inverse of this second perspective transformation is pre-applied to the acquired image to obtain an offset image, which is then aligned with the model image to obtain a registered image.

[0049] A signature is extracted from the test surface by using the registered image, provided that the position and orientation of this surface is similar to the position and orientation of the reference surface on which the oriented image is placed.

[0050] In this implementation, the inverse of the second perspective transformation is applied to the acquired image, which is then aligned (perspective corrected) with the model image.

[0051] In a specific implementation, the method includes, for each test surface, an authentication step for authenticating the test surface by comparing the generated signature with an authentication digital signature that characterizes the structure of the reference surface.

[0052] Said authentication may correspond to methods such as those described in EP1747540B1 or EP1971960B1.

[0053] By comparing the generated signature with the authentication signature, it is possible to determine whether the test surface and the reference surface have the same structural characteristics.

[0054] In this way, it is possible, for example, to assess whether a particular product containing an inspection surface comes from a production line in which an authentication signature was previously removed for one or more surfaces contained in the one or more products.

[0055] In a specific implementation example, the method comprises: - in a first general implementation, a preliminary step of generating an authentication signature from the model image, referred to as a "first type of generation"; or In a second general implementation, a preliminary step of generating an authentication signature from an oriented image, referred to as "second type of generation".

[0056] In this example, in a first general implementation, a signature of the test surface is generated from the registered image and compared with a signature of a reference surface taken from registered images of the products.

[0057] In a second general implementation example, a signature of the test surface is generated from the transformed image, or from the aligned image if an offset image is obtained by applying the inverse of a second perspective transformation to the acquired image, and compared with the signature of a reference surface extracted from registered oriented images of the products.

[0058] In both implementations, the signatures are taken from images representing surfaces positioned in the same plane and in the same orientation, thus ensuring that the authentication process is valid.

[0059] In a specific implementation, generating an authentication signature comprises: - acquiring a reference surface using a third acquisition module; and - an illumination step of illuminating the reference surface with a first light source at least during the acquisition step; The obtaining step corresponds to the following: - if the generation is of the first type, obtaining a model image; or - if the generation is of the second type, obtaining an oriented image.

[0060] If the production is of a second type, the third acquisition module corresponds to the second acquisition module.

[0061] In cases where the illumination is insufficient in terms of illuminated area of ​​the inspection surface, multiple steps of acquiring "offset" images are performed to increase the effective area of ​​the inspection surface and / or region of interest. In order to reconstruct a larger inspection surface and / or region of interest, various steps of acquiring offset images are performed by moving (e.g. translating) the acquisition module and the light source.

[0062] In a specific implementation, the optical axis of the third module may be oriented substantially perpendicular to a reference surface that is illuminated by the first light source in the illumination step at an angle of incidence relative to the reference surface that corresponds to a grazing incidence angle.

[0063] In a specific implementation, the attack angle is preferably in the range of 16° to 45°.

[0064] In a specific implementation, the method includes at least an acquisition step, where the acquisition step is performed by the first module, an illumination step in which the test surface is illuminated by a second light source, and the generating step includes an acquisition step for obtaining structural features of the test surface by detecting an interaction between the test surface and the second light source, the detection of the interaction being: - if the generation is of the first type, by analyzing the aligned images; or if the generation is of the second type, by analyzing the transformed images obtained from the aligned images, It will be held.

[0065] In a specific implementation, the method includes a preliminary step of generating an authentication signature, referred to as a “third type of generation”, the third type of generation step comprising: - acquiring a first model image by an acquisition module; - an illumination step of illuminating the reference surface S_REF with a light source, at least during the acquisition step, where the optical axis of the module and the optical axis of the light source have substantially the same direction, e.g. the same tilt angle β, with respect to the reference surface S_REF; and - an analysis step of analysing a "reorientee" image, the reorientee image being obtained by applying a perspective transformation which compensates for the orientation of the acquisition module and the light source, for example a first rotation of the model image by an angle -β; The offset image corresponds to the acquired image: The method includes at least an acquisition step, where the acquisition step is performed by a first module, an illumination step in which the test surface is illuminated by a light source, and the generation of the sequence of signatures includes an acquisition step for obtaining structural features of the test surface by detecting an interaction between the test surface and the light source, the optical axes of the module and the light source being oriented in substantially the same direction, e.g., at the same tilt angle β, with respect to the test surface (S_1); The interactions are detected by analyzing the “flattened image”, which is obtained by a perspective transformation that compensates for the orientation of the acquisition module and the light source, e.g. a first rotation of the aligned image by an angle −β.

[0066] In this implementation, an image of the reference surface is acquired using an acquisition module and a light source, which are for example oriented at an angle β with respect to the reference surface. A model image is thus obtained.

[0067] The model image is then rotated by an angle −β to obtain a redirected image that looks as if it had been acquired with an acquisition module positioned at 90° to the reference surface, in this example.

[0068] A signature of the reference surface is then extracted from this redirected image: this signature is called the "authentic" signature.

[0069] An image of the test surface is acquired with the acquisition module and the light source oriented at an angle substantially equal to β relative to the test surface. An acquired image is thus obtained.

[0070] The acquired image corresponds to the offset image and is aligned with the model image to obtain an aligned image.

[0071] The aligned image is then rotated by an angle −β to obtain a flattened image that appears as if it had been acquired with the acquisition module positioned at 90° to the test surface.

[0072] Finally, a digital signature of the reference surface is extracted from the flattened image.

[0073] In a specific implementation, for acquiring at least two images by the first module, for each acquired image, the second light source is provided at the same position and in the same direction relative to the first module.

[0074] In this implementation, the method may be applied in a repeated manner to different test surfaces using a single moving system having a first acquisition module and a second light source with a fixed position and orientation relative to the system.

[0075] For example, the method may be performed by a phone or tablet, for example the phone or tablet including a camera operating as the first capture module and a flash operating as the second light source.

[0076] In this implementation, the use of a single mobile system increases the reproducibility of the method.

[0077] In a specific implementation, the method includes reading the protected information, in digital form, and subjecting the protected information to a digital process that is the inverse of the process used to protect the information, the process utilizing the generated signature.

[0078] In this implementation, the generated signature is necessary to be able to read the protected information and is used as a key to protect the information, as described in EP1716520B1.

[0079] In a specific implementation, the protected information is contained in a visible code provided on the inspection surface or on a product or packaging that includes the inspection surface.

[0080] In a specific implementation, the visible code corresponds to a one- or two-dimensional barcode.

[0081] The protected information may be contained in a one- or two-dimensional barcode that is read by a sensor, and using the generated signature to read this information ensures that the information is protected.

[0082] In a specific implementation, the method includes the step of defining "search" regions in the offset image, which contain the region of interest, and based on these search regions, a template matching method is performed.

[0083] For example, the search space can be estimes: - in the offset image, it is located at a position close to the position of the equivalent area in the model image; and - In the offset image, the size is larger than the region of interest.

[0084] The search regions correspond to regions within which the region of interest is located by the template matching method and serve to identify certain perimeters in the offset image within which the region of interest is more likely to be found, in order to make the template matching method more efficient.

[0085] In a specific implementation example, the template matching method is responsible for obtaining a first estimate of parameters of an affine transformation that transforms predetermined points of the region of interest to corresponding predetermined points of the equivalent region based on the search area.

[0086] This template matching method is performed for each region of interest defined in the offset image.

[0087] These parameters, specific to each pair comprising a region of interest and an equivalent region, serve to estimate the parameters of a first perspective transformation which serves to transform the offset image into a model image.

[0088] In a specific implementation, the first estimate is obtained by using a least squares fit between the coordinates of the points of the equivalent region and the coordinates of the points of a search region that includes the region of interest.

[0089] Alternatively, the first estimate is obtained by using a cross-correlation method between the coordinates of the points of the equivalent region and the coordinates of the points of the search region.

[0090] These two methods correspond to the well-known "template matching" method, and they may be replaced by other similar methods.

[0091] In a specific implementation, the template matching method includes an acquisition step for obtaining a second estimate of the parameters, the second estimate being obtained by optimizing the first estimate using an iterative algorithm for maximizing a first enhanced correlation coefficient between the equivalent region and the search region.

[0092] This optimization corresponds to the method described in the paper “Parametric image alignment using enhanced correlation coefficient maximization” (Georgios D. Evangelidis and Emmanouil Z. Psarakis) published in the journal “IEEE transactions on pattern analysis and matching intelligence”, Vol. 30, No. 10 in October 2008.

[0093] The above optimization makes it possible to obtain a more accurate estimate of the perspective transformation for aligning the offset image with the model image, in particular to correct distortion effects that may occur in the images during alignment.

[0094] In a specific implementation, the reference surface is a surface whose tilt and position relative to the acquisition plane of the model image is known.

[0095] In a specific implementation example, the first perspective transformation is obtained by using the Random Sample Consensus (RANSAC) algorithm, as described, for example, in the paper by MA Fischler and RC Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography", Communications of the ACM, 24(6), pp. 381-395, 1981.

[0096] This algorithm makes it possible to exclude outlier points from the series of points used in the method for estimating the parameters of the first perspective transformation.

[0097] In this way, a better estimate of the parameters of the first perspective transformation is obtained.

[0098] In a specific implementation, the perspective transformation is obtained by using an iterative optimization algorithm to maximize a second enhanced correlation coefficient between the offset image and the model image.

[0099] This algorithm using this second enhanced correlation coefficient is similar to the algorithm using the first coefficient described above, but is applied when aligning the offset image with the model image rather than when template matching with an equivalent region of the region of interest.

[0100] The algorithm, using this second enhanced correlation coefficient, makes it possible to obtain improved estimates for the parameters of the first perspective transformation.

[0101] In a specific implementation, the perspective transformation is obtained from the coordinates of pairs of points, each pair comprising one point in the equivalent region and another point in a region of interest defined by template matching between the equivalent region and the offset image.

[0102] In a specific implementation, the points comprise the center of the region of interest and the center of the equivalence region.

[0103] In this implementation, the first perspective transformation is determined from a series of pairs of points, each pair comprising the center of a region of interest and the center of an equivalent region determined by template matching between the region of interest and a model image.

[0104] For example, one possible method for identifying the perspective transformation could be the method used in part 4.2 of the document "Image registration for perspective deformation recovery" (George Wolberg and Siavash Zokai).

[0105] In a specific implementation, the region of interest is defined near and / or in relation to one or more geometrical elements in the test surface, which are also in the reference surface.

[0106] The presence of the graphic elements facilitates the definition of the region of interest and the alignment of the offset image with the model image, for example by using a method that recognizes these symbols to define the region of interest. In particular, when applying the "image matching" or matching method, it is preferable to use input images that have abrupt changes in color and / or brightness (e.g., on the order of about 10 pixels).

[0107] Preferably, these geometric elements appear in a contrasting manner on the test and reference surfaces, which further facilitates the template matching process.

[0108] In a specific implementation, the digital signature is generated from structural features of the test surface, the test surface being made of material elements selected from all or some of the following: textile materials, plastic materials, metal materials, leather, wood, composite materials, glass, or minerals, particularly those having a crystalline structure.

[0109] In a specific implementation, the method of the present invention includes a preliminary step of defining equivalent regions in the model image.

[0110] In a specific implementation, the inspection surface includes a symbol, and an acquisition step for acquiring an acquisition image is automatically initiated in response to determining an orientation of the first acquisition module relative to the inspection surface, the determination being based on an image of the symbol.

[0111] Preferably, the method comprises a display step of displaying on a screen of a terminal comprising said at least one acquisition module an image of an acquisition area of ​​said first module, on which a virtual symbol is superimposed. The acquisition step of acquiring an acquisition image is started automatically depending on the relative position of the image of said symbol in said acquisition area and the position of said virtual symbol.

[0112] More preferably, the acquisition step for acquiring an acquisition image is automatically initiated when an image of said symbol in said acquisition area matches said virtual symbol.

[0113] Advantageously, in this implementation, superimposing these two symbols requires that the second or third capture module be oriented in a particular manner and the direction of the second or third capture module be controlled.

[0114] For example, the symbology may be selected such that the optical axis of the acquisition module is oriented at 45° or 90° relative to the inspection surface.

[0115] In a second aspect, the present invention provides a system for generating a digital signature of an inspection surface, the system comprising: - an acquisition module for obtaining, for each test surface, an "offset" image having at least a portion representative of said surface; - an acquisition module responsible for obtaining, for each test surface, a region of interest in an offset image by means of a template matching method between said first offset image (IM_1) and at least one predefined "equivalent" region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4), said at least one equivalent region being contained in at least one model image (IM_M) having at least a part representative of a reference surface (S_REF); - an alignment module for aligning, for each test surface, the offset image with at least one model image, the alignment being performed by applying a first perspective transformation to the offset image, the perspective transformation being derived from the region of interest and the equivalent region; and a generation module responsible for generating, for each test surface, a digital signature from the aligned images, the digital signature characterizing the structure of the test surface.

[0116] In a specific implementation, the system includes: a first module having a first camera and a first light source forming an angle of attack with respect to a reference surface corresponding to a grazing incidence angle, the angle of attack being preferably in the range of 16° to 45°, more preferably in the range of 16° to 25°, even more preferably in the range of 16° to 20°; and / or a second module having a communication terminal, a second camera and a second light source.

[0117] In a specific implementation example, the communication terminal is a mobile phone or a tablet, the second camera is a camera of the mobile phone or the tablet, and the second light source is a flash of the mobile phone or the tablet.

[0118] In a third aspect, the present invention provides a second method for generating a digital signature of a test surface comprising for each test surface: - an acquisition step for obtaining a series of offset images, each image showing at least a portion of the test surface; -For each offset image: - obtaining a region of interest in an image by template matching said image with a predefined "equivalent" region, said equivalent region being included in a model image having at least a portion representative of a reference surface; and - an acquisition step for obtaining an aligned image by registering the offset image with the model image, the registration being performed by applying a perspective transformation to the offset image, the perspective transformation being derived from the region of interest and the equivalent region; - combining the resulting registered images into a "combined" image; and - generating a digital signature from the combined image, the digital signature characterizing the structure of the test surface.

[0119] In a particular embodiment, the various steps of the method for generating a digital signature for an inspection surface are specified by instructions of a computer program. Thus, the invention provides a computer program on a data medium, the program being adapted to be executed by a computer, the program comprising instructions adapted to perform the method for generating a signature for an inspection surface as described above.

[0120] The program may be in any programming language and may be in the form of source code, object code, or a code form intermediate between source and object code, for example a partially compiled form, or in another desired form.

[0121] The invention further provides a computer readable data medium comprising instructions for the computer program described above.

[0122] The data medium may be any entity or system capable of storing a program. For example, the medium may comprise a storage means such as a read-only memory (ROM), for example a compact disc (CD) ROM or a microelectronic circuit ROM, or a magnetic recording means, for example a hard disk.

[0123] Furthermore, the data medium may also be a transmissible medium such as an electrical or optical signal adapted to be transmitted via electrical or optical cable, by radio or by other means. The inventive program may in particular be downloaded from an Internet-type network.

[0124] Alternatively, the data medium may be an integrated circuit having the program embedded therein and adapted to perform or to be used in the performance of the method in question.

[0125] Other characteristics and advantages of the invention will become apparent from the following description, made with reference to the accompanying drawings, in which: [Brief description of the drawings]

[0126] [Figure 1] FIG. 1 illustrates a system for generating a digital signature of an inspection surface according to the present invention. [Diagram 2] FIG. 2 shows a terminal included in a system for generating a digital signature of an inspection surface according to the invention. [Diagram 3] 3 and 4 show a system for generating a digital signature of an inspection surface according to the present invention. [Figure 4] 3 and 4 show a system for generating a digital signature of an inspection surface according to the present invention. [Diagram 5] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 6]5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 7] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 8] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 9] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 10] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 11] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 12] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 13] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 14] 5-14 show the steps of a method for generating a digital signature of an inspection surface according to a first general implementation example of the present invention. [Figure 15] FIG. 15 shows an example of an "offset" image of a reference surface in accordance with the present invention. [Figure 16] FIG. 16 shows an example of an "aligned" image of a reference surface according to the present invention. [Figure 17] FIG. 17 is a diagram summarizing the various transformations applied to the image involved in the first general implementation. [Figure 18] 18 and 19 show the steps of a method for generating a digital signature of an inspection surface according to a second general implementation of the present invention. [Figure 19] 18 and 19 show the steps of a method for generating a digital signature of an inspection surface according to a second general implementation of the present invention. [Figure 20] 20 and 21 are diagrams summarizing two different transformation variants applied to the image involved in the second general implementation. [Figure 21] 20 and 21 are diagrams summarizing two different transformation variants applied to the image involved in the second general implementation. [Figure 22] 22-24 show a system for generating a digital signature of an inspection surface according to the present invention. [Diagram 23] 22-24 show a system for generating a digital signature of an inspection surface according to the present invention. [Figure 24] 22-24 show a system for generating a digital signature of an inspection surface according to the present invention. [Diagram 25] FIG. 25 shows a terminal included in a system for generating a digital signature of an inspection surface according to the present invention. [Figure 26] FIG. 26 shows method steps for generating a digital signature of an inspection surface according to a fourth implementation of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0127] 1, 3 and 4 show a system SYS according to the invention for generating a digital signature of a test surface S_1.

[0128] In this embodiment, the system SYS may include two terminals T1 and T2 for generating digital signatures and carrying out the steps of the method according to the invention, which will be described with reference to Figures 5 to 14, 18 and 19.

[0129] In this embodiment, as shown in Figure 1, a first terminal T1 is provided along or near a production line for producing a "compatible" product, for example a product to be sold.

[0130] As shown in Figures 3 and 4, the terminal T1 may be a mobile terminal, such as, for example, a smartphone, a phone or a tablet.

[0131] The terminal T1 comprises a first light source LUM_1 for illuminating a visible reference surface S_REF of the conforming product or its packaging, which reference surface S_REF may be made of material elements selected from all or some of the following: textile materials, plastic materials, metal materials, leather, wood, composite materials, glass or minerals, in particular those having a crystalline structure.

[0132] This first light source LUM_1 may be a white light (for example of a phone or tablet) and / or a flash. The flash may be as shown in FIG.

[0133] Following FIG. 1, the angle of incidence of the first light source LUM_1 with respect to the reference surface S_REF is denoted as α.

[0134] In a specific embodiment, this incidence angle α corresponds to a grazing incidence angle. The incidence angle α is preferably in the range of 16° to 45°, more preferably in the range of 16° to 25°, and even more preferably in the range of 16° to 20°.

[0135] In a variant, the terminal T1 does not have a light source, in which case the reference surface S_REF may be illuminated by a light source external to the terminal T1 or by a light source external to the system SYS.

[0136] Terminal T1 further comprises an acquisition module, hereinafter referred to as a "third" acquisition module CAM_3, which is responsible for acquiring an image having at least a part representative of the reference surface S_REF.

[0137] This image is acquired while the reference surface S_REF is illuminated by the first light source LUM_1 or by any other light source.

[0138] Said third acquisition module CAM_3 may comprise a still camera, a video camera or any sensor.

[0139] In a specific embodiment, as shown in FIG. 1, the third acquisition module CAM_3 is arranged substantially perpendicular to the reference surface S_REF.

[0140] In a specific embodiment, as shown in FIG. 3, the third acquisition module CAM_3 assumes the same relative position and the same relative orientation to the first light source LUM_1.

[0141] Typically, this embodiment corresponds to the case where the terminal T1 is a phone or tablet with a flash and a camera, as shown in FIG.

[0142] Terminal T1 may further comprise a module (not shown) making it possible to extract from the image (representing the reference surface S_REF) acquired by the third acquisition module CAM_3 an "authentication" signature, said signature characterizing the structure of the reference surface S_REF.

[0143] In a specific embodiment, this module is responsible for obtaining one or more structural features of the reference surface S_REF by detecting the interaction between the reference surface S_REF and the first light source LUM_1.

[0144] This reference surface S_REF may be made of material elements selected from all or some of the following: textile materials, plastic materials, metal materials, leather, wood, composite materials, glass or minerals, particularly those having a crystalline structure.

[0145] This method of deriving the authentication signature will be explained in detail with reference to FIGS.

[0146] The authentication signature of this reference surface S_REF characterizes, more generally, a conforming product, or a package of a conforming product, which is formed in part by this surface S_REF.

[0147] Alternatively, the above-mentioned modules contained in the system SYS are separate from the terminal T1.

[0148] The system SYS further comprises a second terminal T2, which may be distinct from the first terminal T1, as shown in FIGS.

[0149] The terminal T2 may be a mobile system, for example a smartphone, a phone or a tablet.

[0150] This terminal T2 comprises a first acquisition module CAM_1 which can be used to acquire an image of a "test" surface S_1 present on a "candidate" product or on the packaging of a candidate product.

[0151] Like the reference surface S_REF, this test surface S_1 may be made of material elements selected from all or some of the following: textile materials, plastic materials, metal materials, leather, wood, composite materials, glass or minerals, particularly those having a crystalline structure.

[0152] The first acquisition module CAM_1 may be a still camera, a video camera or any sensor. The first acquisition module CAM_1 is shown in FIGS.

[0153] The second terminal T2 may further comprise a second light source LUM_2, as shown in FIGS.

[0154] This second light source LUM_2 may comprise a white light (eg, of a phone or tablet) and / or a flash.

[0155] The terminal T2 may furthermore comprise a screen, as shown in Fig. 25. This screen is responsible for displaying an image of the acquisition area of ​​the first acquisition module CAM_1, on which a virtual symbol SYMB_V is superimposed, which corresponds for example to the contour of the symbol.

[0156] In a particular embodiment, the terminal T2 further comprises a module (not shown) responsible for extracting a "generated" signature from the image (representing the test surface S_1) acquired by the first acquisition module CAM_1, the generated signature characterizing the structure of the test surface S_1.

[0157] In a specific embodiment, this module is responsible for obtaining one or more structural features of the test surface S_1 by detecting an interaction between the test surface S_1 and a second light source LUM_2.

[0158] The method for generating this signature will be described in detail with reference to FIGS.

[0159] The signature generated for this test surface S_1 serves more generally to characterize the candidate product or the packaging of the candidate product which is partly formed by the surface S_1.

[0160] Alternatively, the above-mentioned modules contained in the system SYS are separate from the terminal T2.

[0161] In a specific embodiment, in the authentication process, the generated signature of the test surface S_1 of the candidate product is compared with the authentication signature of the reference surface S_REF of the matched product.

[0162] For example, this comparison may be performed by a module contained in terminal T1, by a module contained in terminal T2, or by an external module separate from these two terminals.

[0163] In such a case, for example, the external module may include a communication sub-module that enables the external module to communicate with terminals T1 and T2 in order to recuperate the generated signatures and authentication signatures.

[0164] For example, if the above comparison shows that the signature generated for the inspection surface S_1 of the candidate product is substantially identical to the authentication signature for the reference surface S_REF of the matched product, it is possible to infer that the candidate product is from a particular production line.

[0165] In a specific embodiment, the system SYS includes only a terminal T2.

[0166] First comprehensive implementation example FIG. 5 illustrates the main steps of a method for generating a digital signature of a test surface S_1 according to a first general implementation example of the present invention.

[0167] The method has four steps E30, E50, E70 and E90 that can be carried out by the system, as shown in Figures 1, 3, 4 and 22-24.

[0168] In step E30, an "offset" image IM_1 is obtained by a module MOD_OBT1 of the system SYS as shown in FIG.

[0169] This module MOD_OBT1 may be included in a terminal T2 of the system SYS, as shown in FIG.

[0170] In a specific implementation, a part of this offset image IM_1 represents the test surface S_1. In a variant, the entire offset image IM_1 represents the test surface S_1.

[0171] This image IM_1 may be as shown in FIG.

[0172] In a specific implementation example, according to FIG. 6, the step E30 of obtaining an offset image IM_1 comprises an acquisition step E20 of obtaining an "obtained" image IM_0 by means of a first acquisition module CAM_1 as shown in FIGS.

[0173] As shown in FIG. 23, the acquisition module MOD_OBT1 includes a first acquisition module CAM_1.

[0174] In this first overall implementation example, the acquired image IM_0 corresponds to the offset image IM_1 (hereinafter referred to as "offset image IM_1").

[0175] As mentioned above, the terminal T2 may include a screen, as shown in figure 25. This screen is responsible for displaying an image of the acquisition area of ​​the first acquisition module CAM_1, on which is superimposed a virtual symbol SYMB_V.

[0176] In such a situation, the surface S_1 may include a symbol SYMB and an acquisition step E20 of acquiring an acquired image IM_0 may be started automatically when an image IM_SYMB of said symbol SYMB in the acquisition area matches the virtual symbol SYMB_V.

[0177] In a specific implementation, as shown in Figure 7, step E30 also includes a step E15 of illuminating the test surface S_1 with a second light source LUM_2, said illumination being performed at least during the acquisition step E20.

[0178] The acquisition module MOD_OBT1 has a second light source LUM_2 as shown in FIG.

[0179] In a particular implementation example, according to figure 8, the method comprises a step E35 of defining equivalent regions ZEQ_1, ZEQ_2, ZEQ_3 and ZEQ_4 in the model image IM_M. At least a part of the model image IM_M exhibits a reference surface S_REF.

[0180] This step is followed by a step E50 of obtaining regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 in the offset image IM_1, as shown in FIG.

[0181] These regions of interest are obtained by using template matching to match the offset image IM_1 with predefined "equivalent" regions ZEQ_1, ZEQ_2, ZEQ_3 and ZEQ_4, which are contained in one of the model images IM_M.

[0182] This step E50 may be performed by a module MOD_DEF of the system SYS, as shown in Figure 22. This module MOD_DEF may also be included in the terminal T2, as shown in Figure 23. In a variant, this step may be executed by a module external to the terminal T2.

[0183] In a specific implementation example, as shown, for example, in FIG. 15, these regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 are positioned near and / or in association with one or more graphical elements TAG_1, TAG_2, TAG_3 and TAG_4 on the inspection surface S_1.

[0184] Preferably, the or these graphic elements TAG_1, TAG_2, TAG_3 and TAG_4 contrast with the background color of the inspection surface S_1.

[0185] Preferably, these graphic elements TAG_1, TAG_2, TAG_3 and TAG_4 have different shapes.

[0186] In a specific implementation, step E50 is preceded by a step (not shown) of defining "search" regions in the offset image IM_1, which include the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4, on the basis of which a template matching method is performed.

[0187] For example, these search regions may be defined as follows: - in the offset image IM_1, at a position close to the position of these regions of interest ZI_1, ZI_2, ZI_3 and ZI_4; and In the offset image IM_1, the size is larger than the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4.

[0188] The search area corresponds to an area within which the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 are located by the template matching method. The search area makes it possible to define a particular perimeter in the offset image IM_1 within which the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 are found with a higher probability, in order to perform the template matching method more efficiently.

[0189] Step E50 is followed by a step E70 of obtaining an "aligned" image IM_2 by aligning the offset image IM_1 with the "model" image IM_M.

[0190] This alignment step E70 may be carried out by a module MOD_RECAL of the system SYS, as shown in FIG.

[0191] The module MOD_RECAL may be included in the terminal T2, as shown in Figure 23. In a variant, this module MOD_RECAL is external to the terminal T2.

[0192] In a specific implementation, a part of this model image IM_M represents the reference surface S_REF. In a variant, the entire model image IM_M represents the reference surface S_REF.

[0193] This model image IM_M may be as shown in FIG.

[0194] In this first general implementation example, according to FIG. 9, the model image IM_M corresponds to the image of the surface S_REF acquired by the third acquisition module CAM_3 in step F200.

[0195] In a preferred implementation, the optical axis of the third acquisition module CAM_3 is oriented substantially perpendicular to the reference surface S_REF.

[0196] For example, in this implementation, a reference surface S_REF of a product or of a package of that product can be obtained long d'une ligne along which the product is manufactured.

[0197] In a specific implementation example, and referring to FIG. 9, the surface S_REF is illuminated in step F400 by a light source LUM_1 at an angle of attack α with respect to the reference surface S_REF in at least the acquisition step F200.

[0198] In a specific implementation, this angle α corresponds to the grazing incidence angle.

[0199] In a specific implementation example, the angle α is preferably in the range of 16° to 45°, more preferably in the range of 16° to 25°, and further preferably in the range of 16° to 20°.

[0200] In a specific implementation, the reference surface S_REF includes the shapes TAG_1, TAG_2, TAG_3 and TAG_4 as shown in FIG.

[0201] Aligning the offset image IM_1 with the model image IM_M corresponds to performing a perspective correction between these two images and serves to simulate the situation of repositioning the test surface S_1 of the offset image IM_1 in the same plane and in the same orientation as the plane in which the reference surface S_REF of the model image IM_M is viewed.

[0202] Such alignment or obtaining the aligned image IM_2 is performed by applying a first perspective transformation H1 to the offset image IM_1.

[0203] As shown in FIG. 16, a first perspective transformation H1 is obtained from regions of interest ZI_1, ZI_2, ZI_3, and ZI_4 in the offset image IM_1 and equivalent regions ZEQ_1, ZEQ_2, ZEQ_3, and ZEQ_4 in the model image IM_M.

[0204] In a specific implementation example, the template matching method is responsible for obtaining, from the search area, a first estimate of the parameters of the affine transformation T that transforms predetermined points of the region of interest ZI_1 to corresponding predetermined points of the equivalent region ZEQ_1.

[0205] For example, this estimate may be obtained by using the least squares method or the cross-correlation method between the coordinates of the points of the equivalent region ZI_1 and the coordinates of the points of the search region.

[0206] The cross-correlation method can be defined as one whose objective is to maximize the normalized cross-correlation coefficient, defined as follows, for a number of points (x,y) in a search region of the model image IM_M:

number

number

[0207] The above estimates may also be obtained using other known image matching or image template techniques.

[0208] In a specific implementation example, according to Fig. 10, the template matching method comprises a step E75 of obtaining a second estimate of the parameters of the affine transformation, which is obtained by optimizing the first estimates using an iterative algorithm for maximizing a first enhanced correlation coefficient between the equivalent region ZEQ_1 and a search region including the region of interest ZI_1.

[0209] The first enhanced correlation coefficient above may be defined in the same manner as in section 3.1 of the above-cited document “Parametric image alignment using enhanced correlation coefficient maximization.”

[0210] Once the parameters of each affine transformation transforming each region of interest ZI_1 into an equivalent region ZEQ_1 have been estimated, a set of pairs of points is obtained, each pair comprising one point in the equivalent region ZEQ_1 and another point in a region of interest Z_I1 defined by a template matching method applied to the equivalent region ZI_1 and to the tilted image IM_1.

[0211] In a specific implementation example, the pairs of points comprise or correspond to the centers (plural) of the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 and the centers (plural) of the equivalent regions ZEQ_1, ZEQ_2, ZEQ_3 and ZEQ_4.

[0212] The parameters of the first perspective transformation H1 that transforms the offset image IM_1 into the aligned image IM_2 can be estimated from these pairs of points.

[0213] For example, these parameters may be estimated by a method such as that described in part 4.2 of the document "Image registration for perspective deformation recovery" (George Wolberg and Siavash Zokai).

[0214] In a specific implementation example, the first perspective transformation H1 is obtained by using the Random Sample Consensus (RANSAC) algorithm.

[0215] The above algorithm serves to eliminate outlier points from the set of points or point pairs used to estimate the parameters of the first perspective transformation H1.

[0216] In a specific implementation example, the first perspective transformation H1 is obtained by using an iterative optimization algorithm to maximize a second enhanced correlation coefficient between the offset image IM_1 and the model image IM_M.

[0217] The above algorithm using the above-mentioned second enhanced correlation coefficient is similar to the algorithm using the above-mentioned first enhanced correlation coefficient, but is applied when aligning the offset image to the model image, and not when matching the equivalent region ZI_1 with the model image IM_M (template matching) (lors).

[0218] The step E70 of obtaining an aligned image IM_2 is followed by a generation step E90 for generating a digital signature from the aligned image IM_2, the digital signature characterizing the structure of the test surface S_1.

[0219] This generation step E90 is carried out by a module MOD_GEN, which is for example included in the terminal T2, as shown in Figure 14, or which is external to the terminal T2.

[0220] In a specific implementation example, according to FIG. 11, step E90 of generating a digital signature includes a step E95 of obtaining structural characteristics of the test surface S_1 by detecting an interaction between the test surface S_1 and a second light source LUM_2.

[0221] In this first general implementation, the interaction is detected by analyzing the registered image IM_2.

[0222] In a specific implementation example, according to figure 12, the step E90 of generating a generated signature is followed by a step E120 of authenticating the test surface S_1 by comparing the generated signature with an authentication digital signature, said authentication signature characterizing the structure of the reference surface S_REF.

[0223] In this first general implementation, the authentication signature is generated from the model image IM_M in step E5, as shown in FIG.

[0224] More precisely, generating this authentication signature involves obtaining structural features of the reference surface S_REF by detecting an interaction between the reference surface S_REF and the first light source LUM_1.

[0225] In a specific implementation, according to figure 14, the method further comprises a step E130 of reading the protected information, for example contained in a visible code (not shown) provided on the inspection surface or on a product or packaging containing the inspection surface.

[0226] When reading the protected information, the information, in digital form, is subjected to a digital process that is the inverse of the process used to protect the information, which process utilizes the generated signature. For example, the protected information may be contained in a one- or two-dimensional barcode.

[0227] In Fig. 17 the main steps of the first general implementation example are summarized: an offset image IM_1 of the inspection surface S_1 is obtained, where this image IM_1 corresponds to the image IM_0 acquired by the acquisition module CAM_3. The image IM_1 is then aligned with respect to a model image IM_M representing the reference surface S_REF, so that an aligned image IM_2 is obtained. A digital signature of this aligned image is extracted. In this example, a double arrow represents a link between two images showing surfaces both oriented and positioned in the same manner.

[0228] Second comprehensive implementation example 18 and 19 show a method for generating a digital signature of a test surface S_1 according to a second general implementation example of the present invention.

[0229] These two methods reproduce the four main steps E30, E50, E70 and E90 in the first general implementation, which can be performed equally well by systems of the kind shown in Figures 1, 3, 4 and 22-24.

[0230] They further include the optional steps E15, E60, E75, E95, E120 and E130 of the first general implementation.

[0231] As in the first general implementation, the step E30 of obtaining an offset image IM_1 comprises a step E20 of obtaining an "obtained" image IM_0 by using a first acquisition module CAM_1 as shown in FIGS.

[0232] However, in this second overall implementation, the model image IM_M is obtained by applying a second perspective transformation H2 to an "oriented" image IM_M' that represents the reference surface S_REF.

[0233] With reference to FIG. 13, this oriented image IM_M' is generated in step E5'.

[0234] 9, this oriented image IM_M' is acquired in a step F200 using a second acquisition module CAM_2 arranged substantially perpendicular to the reference surface S_REF. At least in the acquisition step F200, an illumination step F400 similar to the first general implementation example is performed.

[0235] The second perspective transformation H2 is preferably selected in such a way that it transforms the oriented image IM_M' into an image of a reference surface S_REF that is simulated as being acquired under certain conditions, for example by a phone or a tablet.

[0236] This transformation also serves to "shift" the reference surface S_REF in the model image IM_M to a position and orientation as close as possible to that of the acquired image IM_0.

[0237] In this first variant of the second overall implementation example, according to FIG. 18, the offset image IM_1 corresponds to the acquired image IM_0.

[0238] In step E50, regions of interest are obtained in the offset image IM_1, and in step E70, the offset image IM_1 is transformed into an aligned image IM_2 by using these regions of interest.

[0239] The various steps for aligning the image IM_1 are performed in a manner similar to the first general implementation.

[0240] Once the aligned image IM_2 is obtained, in step E80, the inverse of the second perspective transformation H2, denoted H2', is applied to the aligned image IM_2 such that the aligned image IM_2 is aligned with the oriented image IM_M', thereby producing a "transformed" image IM_2'.

[0241] In step E90, a digital signature of the surface S_1 is generated from the transformed image IM_2'.

[0242] In a second variant of the second overall implementation example, as shown in FIG. 19, first, an offset image IM_1 is obtained by applying a perspective transformation H2' to the acquired image IM_0, and then the offset image IM_1 is aligned with the oriented image IM_M'.

[0243] In this variant, unlike the previous variant in which the acquired image IM_0=IM_1 is first aligned to obtain an image which is subsequently aligned with the oriented image IM_M', a perspective transformation H2' is first applied to the acquired image IM_0 to obtain an image which is subsequently aligned with the model image IM_M.

[0244] Then, in step E90, a digital signature of the test surface S_1 is generated from the aligned image IM_2.

[0245] In Fig. 20 a first variant of this second overall implementation is summarized: an offset image IM_1 of the test surface S_1 is obtained, where this image IM_1 corresponds to the image IM_0 acquired by the acquisition module CAM_3. The image IM_1 is then aligned with respect to a model image IM_M representing the reference surface S_REF, where the model image IM_M has already been obtained after transforming the oriented image IM_M' by applying a perspective transformation H2 to the oriented image IM_M', so as to obtain an aligned image IM_2. The inverse of the perspective transformation H2, denoted H2', is applied to the aligned image IM_2, so as to obtain a transformed image IM_2' from which the signature is extracted.

[0246] In Fig. 21 a second variant of this second implementation example is summarized: an offset image IM_1 of the test surface S_1 is obtained by applying a perspective transformation H2' to the image IM_0 acquired by the acquisition module CAM_3. The image IM_1 is then aligned with an oriented image IM_M' representing the reference surface S_REF, where the model image IM_M has already been obtained by transforming the oriented image IM_M' by applying the perspective transformation H2 to the oriented image IM_M', so as to obtain an aligned image IM_2. The signature is extracted by analyzing the aligned image IM_2.

[0247] Third implementation example The method of the third implementation reproduces the four main steps E30, E50, E70 and E90 in the first and second overall implementations.

[0248] As in the first and second general implementation examples, the step E30 of obtaining an offset image IM_1 comprises a step E20 of obtaining an "obtained" image IM_0 by means of an acquisition module.

[0249] In this third overall implementation example, the acquired image IM_0 corresponds to the offset image IM_1 (hereinafter referred to as "offset image IM_1").

[0250] In a step E50, regions of interest are obtained in the offset image IM_1, and in a step E70, the offset image IM_1 is transformed into an aligned image IM_2 on the basis of these regions of interest.

[0251] The various steps making it possible to align the image IM_1 are carried out in a manner similar to the first overall implementation example: the aligned image IM_2 is obtained by applying a first perspective transformation H1 to the offset image IM_1 by the above-mentioned template matching method, which is applied to predetermined points of the region of interest in the offset image IM_1 relative to points referred to in the model image IM_M.

[0252] However, this third implementation differs from the first two in the placement of the acquisition modules for acquiring the model and offset images, the placement of the light source, and the way the signature is retrieved.

[0253] In this implementation, the model image IM_M of the reference surface S_REF is acquired by an acquisition module and a light source having the same orientation with respect to the reference surface S_REF, e.g., the same tilt angle β, which is not 90° with respect to the reference surface. This tilt angle of the acquisition module and the light source avoids the formation of a halo of light.

[0254] This third implementation is particularly advantageous for specular or glossy surfaces where 90° illumination creates a halo of light that reduces contrast and affects signature retrieval.

[0255] Then, a first perspective transformation is performed to compensate for the orientation of the acquisition module and the light source, such that a reoriented image is obtained that looks as if it was acquired with an acquisition module positioned at 90° with respect to the reference surface S_REF. For example, this perspective transformation may include rotating the model image IM_M by an angle −β, which may be combined with the first perspective transformation H1 as described in other implementations.

[0256] An authenticating signature of the reference surface S_REF is then extracted from the redirected image.

[0257] Furthermore, an offset image of the test surface is acquired with the acquisition module and the light source oriented at an angle β′ with respect to the test surface S_1, the angles β and β′ being preferably similar.

[0258] For example, this angle β' is determined by matching the symbols SYMB_V and SYMB described with reference to Fig. 25, or by using any other means that serves to ensure the orientation of the acquisition module with respect to the inspection surface at the time of acquisition. This mechanism for ensuring the orientation of the acquisition module may also be used in other implementations of the invention. As described above, the offset image is aligned with the model image so that aligned images are obtained.

[0259] A perspective transformation is performed to compensate for the orientation of the acquisition module and the light source in a manner that results in an image that is flattened back in a manner that it appears as if it was acquired with the acquisition module positioned at 90° to the inspection surface. For example, this perspective transformation may comprise rotating the aligned image by an angle -β', which may be performed in conjunction with a first perspective transformation H1 as described in other implementations.

[0260] Finally, in step E90, a digital signature of the test surface S_1 is generated using the flattened image.

[0261] 4th implementation example The present invention proposes a fourth implementation example, which is described below with reference to Fig. 26. Steps E20, E50, E70 and E90 of this fourth implementation example are the same as the steps of the second variant of the second implementation example, and they have the same reference numerals.

[0262] It should be recalled that in the second variant of the second implementation example, a second perspective transformation H2 is applied to the image, which is precisely defined by the model image IM_M and the "oriented" image IM_M'. In this sense, this perspective transformation H2 is always the same, regardless of the acquired image IM_0, and in this respect can be called "static". However, the fourth implementation example differs from the second variant of the second implementation example in that the constant or static perspective transformation H2 is replaced by a third perspective transformation H3, which is dynamically calculated after the manufacturing step E20 depending on the acquired image IM_0 relative to the oriented image IM_M'.

[0263] In this fourth implementation, the offset image IM_1 is obtained by applying a perspective transformation H3 to the acquired image IM_0. The image IM_1 is then aligned with respect to an oriented image IM_M' representing the reference surface S_REF, so that an aligned image IM_2 is obtained. The signature is extracted by analyzing the aligned image IM_2.

[0264] In this fourth implementation example, the main advantage of the dynamic calculation H3 is that it facilitates positioning of the acquisition module, speeds up the start of acquisition, and improves the user experience by making the orientation of the acquisition module more "tolerant", e.g., more tolerant with respect to the tilt angle of the optical axis of the acquisition module.

[0265] To explain this, firstly, it should be understood that the perspective transformation H2 (or H2') is calculated from the model image IM_M and the oriented image IM_M', simulating a particular orientation as close as possible to the orientation of the acquired image IM_0, whereas the perspective transformation H3 is called "dynamic" because it is calculated according to the acquired image IM_0 at the time of acquisition and does not depend on a particular orientation. H2 is the perspective transformation that is called "constant".

[0266] Advantageously, by using a "dynamic" perspective transformation H3 rather than a "fixed" perspective transformation like H2 (see the second variant of the second implementation example), it becomes possible to dynamically align the images as they are acquired, making it possible to avoid the need for the acquisition of the acquired image IM_0 to have an orientation close to that of the model image IM_M' in order to accurately align the images, a need that may exist in other implementation examples.

[0267] FIG. 22 illustrates a system SYS for generating at least one digital signature from at least one test surface by performing either of two general implementations of the present invention.

[0268] The system SYS comprises, for each test surface S_1, an acquisition module MOD_OBT1 for obtaining an "offset" image IM_1 having at least a part representative of the test surface S_1.

[0269] The system SYS also comprises a definition module MOD_OBT2 which is responsible for obtaining, for each test surface S_1, a region of interest in the offset images.

[0270] These regions of interest are obtained by template matching with predefined equivalent regions ZEQ_1, ZEQ_2, ZEQ_3 and ZEQ_4 applied to the offset images, which are contained in a model image IM_M having at least a part representative of the reference surface S_REF.

[0271] The system SYS also comprises a registration module MOD_RECAL, which is used in cooperation with each test surface S_1, for registering the offset image IM_1 with the model image IM_M. This registration is performed by applying a first perspective transformation H1 to the offset image IM_1. The perspective transformation H1 is obtained from the regions of interest ZI_1, ZI_2, ZI_3 and ZI_4 and the equivalent regions ZEQ_1, ZEQ_2, ZEQ_3 and ZEQ_4.

[0272] The system SYS also comprises a generation module MOD_GEN for generating, for each test surface, a digital signature from the registered image IM_2, which digital signature characterizes the structure of the test surface S_1.

[0273] Finally, the system SYS includes a storage medium SUP responsible for storing a program PG containing the instructions for carrying out the method.

[0274] In a specific embodiment, as shown in FIG. 23, the system SYS comprises: a first terminal T1 including a first camera CAM_2 and a first light source LUM_1 forming an angle of attack with respect to a reference surface S_REF corresponding to a grazing incidence angle, where the angle of attack is preferably in the range of 16° to 45°, more preferably in the range of 16° to 25°, even more preferably in the range of 16° to 20°; and a second product including a communication terminal T2, a second camera CAM_1 and a second light source LUM_2;

[0275] In this embodiment, the system SYS has a computer hardware architecture as shown diagrammatically in FIG.

[0276] The system SYS includes a processor 10, a rewritable non-volatile memory 11, a ROM 12, a random access memory (RAM) 13, and a communication module COM.

[0277] The ROM 12 of the system SYS is a data medium according to the invention which is readable by the processor 10 and which stores a computer program according to the invention containing instructions for carrying out the steps of the method according to the invention having the steps described with reference to Figures 5 to 14, 18 and 19 for generating a digital signature of an inspection surface.

Claims

1. 1. A method for generating at least one digital signature of at least one surface of a material element, referred to as a "test surface" (S_1), which surface does not include a physically embedded authentication pattern incorporating identification data by converting said authentication pattern into a relief structure on said surface, said method being performed by a data processing system, said method comprising the steps of: - an acquisition step (E30) for obtaining an "offset" image (IM_1) having at least a part representative of said inspection surface (S_1); - an acquisition step (E50) for obtaining at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4) in said offset image (IM_1) by matching said offset image (IM_1) with at least one predetermined "equivalent" region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4) contained in a model image (IM_M) having at least a part representing a "reference" surface (S_REF), by a method known as "template matching"; an acquisition step (E70) for obtaining an "aligned" image (IM_2) by aligning said offset image (IM_1) with said model image (IM_M), said alignment comprising repositioning said inspection surface (S_1) in the same plane as said reference surface (S_REF), said alignment being carried out by applying a first perspective transformation (H1) to said offset image (IM_1), said first perspective transformation (H1) being obtained from said at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4) and said at least one equivalent region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4); and - a generation step (E90) for generating said digital signature from said aligned image (IM_2), said digital signature characterizing the structure of said test surface (S_1); Equipped with The method comprises, for each test surface (S_1), an authentication step (E120) for authenticating said test surface (S_1), said authentication step being performed by comparing said generated signature with an authentication digital signature, said authentication signature characterizing the structure of said reference surface (S_REF).

2. 2. The method of claim 1, wherein the step (E30) of obtaining the offset image comprises a step (E20) of obtaining an "acquired" image (IM_0) by a first acquisition module (CAM_1), and the offset image (IM_1) is obtained from the acquired image (IM_0).

3. 3. The method of claim 2, wherein said offset image (IM_1) corresponds to said acquired image (IM_0) and said signature is generated by analyzing said registered image (IM_2) in said generating step (E90).

4. 3. The method according to claim 2, further comprising a preliminary step (E10) of acquiring an "oriented" image (IM_M') of said reference surface (S_REF) using a second acquisition module (CAM_2) arranged substantially perpendicular to said reference surface (S_REF), said model image (IM_M) being obtained by applying a predetermined second perspective transformation (H2) to said oriented image (IM_M').

5. The method comprises: - when the signature is generated in a generation step (E90) according to claim 3 or 4, a generation (E5) of the authentication signature from the model image (IM_M), called "generation of a first type"; or - when the signature is generated in the generation step (E90) according to claim 1, a generation (E5') of the authentication signature from the oriented image (IM_M'), called "generation of a second type"; The method of claim 1 including a preliminary step.

6. The generating step (E5, E5′) for generating the authentication signature comprises: an acquisition step (F200) of acquiring said reference surface (S_REF) using a third acquisition module (CAM_3); and - an illumination step (F400) of illuminating said reference surface (S_REF) using a first light source (LUM_1) at least during said acquisition step (F200); Equipped with The obtaining step (F200) - if said generation is of said first type, obtaining said model image (IM_M); or - if said generation is of said second type, obtaining said oriented image (IM_M'); The method of claim 5 , corresponding to

7. 7. The method according to claim 6, wherein an optical axis (OX) of said third module (CAM_3) is oriented substantially perpendicular to said reference surface (S_REF), and said reference surface (S_REF) is illuminated in said illumination step (F400) by said first light source (LUM_1) at an angle of attack (α) relative to said reference surface that corresponds to a grazing incidence angle.

8. The method according to claim 7, wherein the angle of attack (α) is preferably in the range of 16° to 45°.

9. The method comprises at least the acquisition step (E20), which is performed by the first module (CAM_1), an illumination step (E15) in which the test surface (S_1) is illuminated by a second light source (LUM_2), and the step (E90) of generating the signature comprises an acquisition step (E95) for obtaining structural features of the test surface (S_1) by detecting an interaction between the test surface (S_1) and the second light source (LUM_2), the detection of the interaction being - by analysing said registered image (IM_2), if said generation is of said first type; or if said generation is of said second type, by analyzing a transformed image (IM_2′) obtained from said aligned images, The method according to any one of claims 2 to 8,

10. The method includes a preliminary step of generating the authentication signature, referred to as a "generation of a third type", the step of generating the third type comprising: - an acquisition step for acquiring said first model image (IM_M) by an acquisition module; - an illumination step, at least during said acquisition step, of illuminating said reference surface (S_REF) with a light source, the optical axis of said module and the optical axis of said light source having substantially the same orientation with respect to said reference surface (S_REF), for example the same inclination angle β; and - an analysis step of analysing a "redirected" image, said redirected image being obtained by applying a perspective transformation which compensates for the orientation of said acquisition module and said light source, for example a first rotation of said model image (IM_M) by an angle -β; Equipped with The offset image (IM_1) corresponds to the acquired image (IM_0): The method comprises at least the acquisition step (E20), performed by the first module (CAM_1), an illumination step in which the test surface (S_1) is illuminated by a light source, and the sequence of generation of the signature (E90) comprises an acquisition step for obtaining structural features of the test surface (S_1) by detecting an interaction between the test surface (S_1) and the light source, the optical axes of the module and the light source being oriented in substantially the same direction relative to the test surface (S_1), for example at the same tilt angle β; The interaction is detected by analyzing a "flattened image", which is obtained by a perspective transformation that compensates for the orientation of the acquisition module and the light source, e.g. a first rotation of the aligned image (IM_2) by an angle -β; The method according to any one of claims 1 to 9.

11. 10. The method of claim 9, wherein for each acquired image, the second light source (LUM_2) is provided at the same position and in the same direction relative to the first module (CAM_1) to acquire at least two images by the first module (CAM_1).

12. 12. The method according to any one of claims 1 to 11, comprising a step (E130) of reading the protected information, said protected information being in digital form and subjected to a digital process which is the inverse of the process used to protect said information, said process making use of the generated signature.

13. 13. The method of claim 12, wherein the protected information is contained in a visible code (CODE) provided on the inspection surface (S_1) or on a product or packaging containing the inspection surface (S_1).

14. The method according to claim 13, wherein said visible code (CODE) corresponds to a one- or two-dimensional barcode.

15. The method according to any one of claims 1 to 14, comprising a step of defining at least one "search" area in the offset image (IM_1), said at least one search area including said at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4), and based on said at least one search area the template matching method is performed.

16. 16. The method according to claim 15, wherein the template matching method serves to obtain, based on the search area, first estimates of parameters of an affine transformation that transforms predetermined points of the region of interest (ZI_1) to corresponding predetermined points of the equivalent region (ZEQ_1).

17. 17. The method of claim 16, wherein the first estimate is obtained by using a least squares method between the coordinates of the points of the equivalent region (ZEQ_1) and the coordinates of the points of the search region.

18. 17. The method of claim 16, wherein the first estimate is obtained by using a cross-correlation method between the coordinates of the points of the equivalent region (ZEQ_1) and the coordinates of the points of the search region.

19. 19. The method according to any one of claims 16 to 18, wherein the template matching method comprises an obtaining step (E75) for obtaining a second estimate of the parameter, the second estimate being obtained by optimizing the first estimate using an iterative algorithm for maximizing a first enhanced correlation coefficient between the equivalence region (ZEQ_1) and the search region.

20. The method according to any one of claims 1 to 19, wherein the reference surface is a surface whose inclination and position relative to the acquisition plane of the model image is known.

21. The method according to any one of claims 1 to 20, wherein the first perspective transformation (H1) is obtained by using a Random Sample Consensus (RANSAC) algorithm.

22. The method according to any one of claims 1 to 21, wherein the perspective transformation (H1) is obtained by using an iterative optimization algorithm for maximizing a second enhanced correlation coefficient between the offset image (IM_1) and the model image (IM_M).

23. 23. The method according to claim 1, wherein the perspective transformation (H1) is obtained from the coordinates of pairs of points, each pair comprising one point in the equivalent region (ZEQ_1) and another point in the region of interest (ZI_1) defined by the template matching method between the equivalent region (ZEQ_1) and the offset image (IM_1).

24. 24. The method of claim 23, wherein the points include a center of the at least one region of interest (ZI_1) and a center of the at least one equivalent region (ZEQ_1).

25. 25. The method according to claim 1, wherein the at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4) is located near and / or associated with a graphical element (TAG_1, TAG_2, TAG_3, TAG_4) in the inspection surface (S_1), the graphical element (TAG_1, TAG_2, TAG_3, TAG_4) also being in the reference surface (S_REF).

26. 26. The method according to any one of claims 1 to 25, wherein the digital signature is generated from at least one structural feature of the test surface (S_1), the test surface (S_1) being made of material elements selected from all or part of the following: textile materials, plastic materials, metal materials, leather, wood, composite materials, glass or minerals, in particular those having a crystalline structure.

27. A method according to any one of the preceding claims, comprising a preliminary step (E35) of defining said at least one equivalent region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4) in said model image (IM_M).

28. 28. The method according to claim 2, wherein the inspection surface (S_1) comprises a symbol (SYMB), and an acquisition step (E20) of acquiring the acquired image is started automatically depending on a determination of an orientation of the first acquisition module (CAM_1) relative to the inspection surface, said determination being made on the basis of an image (IM_SYMB) of the symbol (SYMB).

29. 29. The method according to claim 28, further comprising a display step of displaying on a screen of a terminal including the at least one acquisition module (CAM_1) an image of an acquisition area of ​​the first module (CAM_1) on which a virtual symbol (SYMB_V) is superimposed, and the acquisition step (E20) of acquiring the acquired image is started automatically depending on the relative position of the image (IM_SYMB) of the symbol (SYMB) in the acquisition area and the position of the virtual symbol (SYMB_V).

30. 30. The method of claim 29, wherein the acquisition step (E20) for acquiring the acquired image is automatically initiated when the image (IM_SYMB) of the symbol (SYMB) in the acquisition area matches the virtual symbol (SYMB_V).

31. A system (SYS) for generating at least one digital signature of at least one surface of a material element (wherein said surface does not include a physical embedding of an authentication pattern incorporating identification data by transforming said authentication pattern into a relief structure on said surface), said surface being called "test surface" (S_1), said system (SYS) comprising: an acquisition module (MOD_OBT1) for obtaining, for each test surface (S_1), an "offset" image (IM_1) having at least a portion representative of said test surface (S_1); an acquisition module (MOD_OBT2) responsible for obtaining, for each test surface (S_1), at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4) in said offset image by means of a template matching method between said offset image (IM_1) and at least one predefined "equivalent" region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4), said at least one equivalent region being contained in a model image (IM_M) having at least a part representative of a "reference" surface (S_REF); a registration module (MOD_RECAL) responsible for registering, for each inspection surface (S_1), said offset image (IM_1) with said model image (IM_M), said registration comprising repositioning said inspection surface (S_1) in the same plane as the plane with said reference surface (S_REF), said registration being carried out by applying a first perspective transformation (H1) to said offset image (IM_1), said perspective transformation (H1) being obtained from said at least one region of interest (ZI_1, ZI_2, ZI_3, ZI_4) and said at least one equivalent region (ZEQ_1, ZEQ_2, ZEQ_3, ZEQ_4); and a generation module (MOD_GEN) responsible for generating, for each test surface, from said aligned image (IM_2), said digital signature characterizing the structure of said test surface (S_1); Equipped with The system (SYS) performs, for each test surface (S_1), an authentication process to authenticate the test surface (S_1), the authentication process being performed by comparing the generated signature with an authentication digital signature, the authentication signature characterizing the structure of the reference surface (S_REF), system (SYS).

32. The system (SYS) comprises a first acquisition module (CAM_1) and a second acquisition module (CAM_2), The system (SYS) comprises: a first module (T1) having a first camera (CAM_2) as said second acquisition module (CAM_2) and a first light source (LUM_1) forming an angle of attack (α) relative to said reference surface (S_REF) corresponding to a grazing incidence angle, said angle of attack (α) preferably lying in the range of 16° to 45°, more preferably lying in the range of 16° to 25°, even more preferably lying in the range of 16° to 20°; and / or a second module comprising a communication terminal (T2), a second camera (CAM_1) as said first acquisition module (CAM_1) and a second light source (LUM_2); 32. The system (SYS) of claim 31 , comprising:

33. The system (SYS) of claim 32, wherein the communication terminal (T2) is a mobile phone or a tablet, the second camera (CAM_1) is a camera of the mobile phone or the tablet, and the second light source (LUM_2) is a flash of the mobile phone or the tablet.

34. A computer program (PG) comprising instructions for carrying out the steps of the method for generating at least one digital signature according to any one of claims 1 to 30, when said instructions are executed by a computer.

35. A computer readable data medium (SUP) storing a computer program comprising instructions for carrying out the steps of the method for generating at least one digital signature according to any one of claims 1 to 30.

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