Security device based on a greyscale image

Description

Domaine Technique

[0001] The invention relates to the field of security devices for securely authenticating any objects such as documents, for example identity documents or official documents. The invention relates in particular to security devices formed from a grayscale image representative of pixels of a starting image which may be of various types.

[0002] The invention finds a particular application in the authentication of objects from security devices formed on a support. Technique antérieure

[0003] Document security has undergone many developments in recent years. Various techniques have been developed to secure documents in order to combat falsification, duplication, and illicit reproduction. Thus, identity documents (passports, identity cards, driving licenses, etc.) and other official documents (notarized documents, banknotes, etc.) are generally equipped with more or less complex security features that can be authenticated and are difficult to falsify or reproduce without the appropriate equipment and skills. Known security features are, for example, based on watermarks, color or grayscale images, holograms, or others.

[0004] The technologies on which certain known security devices are based nevertheless remain within the reach of counterfeiters who sometimes have significant resources.

[0005] There is therefore a need today for more complex security devices that can be reliably and securely authenticated, and that are difficult to falsify or reproduce, in particular with the aim of strengthening the security of any objects, in particular documents, such as, for example, identity documents or any other documents.

[0006] US 2008 / 260267 A1 describes a technique for authenticating physical documents using digital imaging systems. US 2014 / 183854 describes a technique for authenticating a printed document containing a barcode. US 2009 / 328143 discloses a method for authenticating a document in which critical content is compressed with a relatively low compression ratio. Exposé de l'invention

[0007] To this end, the present invention relates to a security method according to claim 1 implemented by a security system, the method comprising: acquisition of a first image characterized in at least N dimensions comprising a first and a second spatial dimension and a third dimension, N being an integer greater than or equal to 3, said third dimension defining one of: ∘ a spatial dimension other than the first and second spatial dimensions; ∘ a colorimetric dimension in a colorimetric space; and ∘ a spectral dimension in a spectral space; the first image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two components in said third dimension; compression of the first image into a second grayscale image comprising a plurality of pixels each having a grayscale representative of at least one component in said third dimension of a corresponding pixel of the first image,said compression comprising applying a transfer function to determine, from the components in said third dimension of each pixel of the first image, the gray levels of the corresponding pixels of the second image, the transfer function corresponding to a data matrix comprising, for each pixel of the first image, a respective value (V) defining a transformation of the at least one component in said third dimension (DM3) into a gray level, the matrix comprising different values ​​such that the at least one component in said third dimension of at least one pixel is transformed differently from the at least one component in said third dimension of at least one other pixel; and forming the second gray level image on a medium.

[0008] The invention thus makes it possible to form grayscale images acting as security devices which can be reliably and securely authenticated, and which are difficult to falsify or reproduce, which makes it possible to secure any object or medium.

[0009] The high level of protection thus obtained results in particular from the fact that several technologies of different natures are combined to limit or prevent any falsifications or illicit reproductions. Indeed, to form a second grayscale image according to the concept of the invention, a forger must implement a digital compression of the first source image which implies adequate computer processing means, and must also have the necessary means to physically reproduce (by printing, laser engraving or other as the case may be) this second image on a medium with a sufficient level of quality to be able to be read and exploited subsequently. Without the appropriate transfer function, the generation of the second grayscale image is not possible.

[0010] According to a particular embodiment, the pixels of the second grayscale image each have a grayscale level representative of a single component, in the third dimension, of a corresponding pixel in the first image, said single component being selected by the transfer function for each pixel of said first image.

[0011] According to a particular embodiment, the pixels of the second grayscale image have a grayscale representative of a linear combination of at least two components in the third dimension of a corresponding pixel of the first image, said linear combination being defined by the transfer function for each pixel of said first image.

[0012] According to a particular embodiment, the compression is a lossy compression of data so that among the P components in the third dimension of each pixel of the first image, the transfer function only selects Q components which are represented in the gray level of the corresponding pixel in the second image, P and Q being integers such that 1 ≤ Q < P.

[0013] According to a particular embodiment, N=3 and the third dimension is a colorimetric dimension in a colorimetric space so that: the first image acquired during said acquisition is a color image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two color components in said colorimetric space; and the second image generated during said compression comprises a plurality of pixels each having a gray level representative of at least one color component of a corresponding pixel of the first image, said compression comprising the application of the transfer function to determine, from the color components of each pixel of the first image, the gray levels of the corresponding pixels of the second image.

[0014] According to a particular embodiment, N=3 and the third dimension is a spatial dimension other than the first and second spatial dimensions so that: the first image acquired during said acquisition is a 3D image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two position components in said third spatial dimension; and the second image generated during said compression comprises a plurality of pixels each having a gray level representative of at least one position component in the third spatial dimension of a corresponding pixel of the first image, said compression comprising the application of the transfer function to determine, from the position components in the third spatial dimension of each pixel of the first image, the gray levels of the corresponding pixels of the second image.

[0015] According to a particular embodiment, N=3 and the third dimension is a spectral dimension in a spectral space so that: the first image acquired during said acquisition is a spectral image comprising a plurality of pixels characterized by their respective position in the first and second dimensions and by at least two spectral intensity components in said third spectral dimension; the second image generated during said compression comprises a plurality of pixels each having a gray level representative of at least one spectral intensity component of a corresponding pixel of the first image, said compression comprising the application of the transfer function to determine, from the spectral intensity components of each pixel of the first image, the gray levels of the corresponding pixels of the second image.

[0016] According to a particular embodiment, said second image forms a security device which can be authenticated by comparing the first image with a third image obtained by applying the inverse of the transfer function to the second image present on the support.

[0017] According to a particular embodiment, the second image is formed on the support by at least one of the following formation methods: forming the second image by laser engraving; printing the second image on the support; and forming the second image by micro-perforations.

[0018] According to a particular embodiment, the formation of the second image comprises the projection of laser radiation onto the support to form each pixel of the second image by delivering an energy which is a function of the gray level of said pixel.

[0019] In a particular embodiment, the different steps of the security method of the invention are determined by computer program instructions.

[0020] Consequently, the invention also relates to a computer program on an information medium (or computer programs on the same information medium or separate information mediums), this program being capable of being implemented in an electronic device such as a computer, this program comprising instructions adapted to the implementation of the steps of a security method as defined in this document.

[0021] The invention also relates to a recording medium (or information medium) readable by a computer, and comprising instructions of a computer program as mentioned above.

[0022] The invention also relates to a processing method according to claim 9 for reading a second grayscale image formed on a medium in accordance with the security method of the invention. In particular, the invention relates to a processing method implemented by a processing system, comprising: optical acquisition of a second grayscale image comprising a plurality of pixels formed on a support, to obtain image data defining a grayscale of each pixel of said second image, generation, from said image data, of a third image characterized in at least N dimensions comprising a first and a second spatial dimension and a third dimension, N being an integer greater than or equal to 3, said third dimension defining one of: ∘ a spatial dimension other than the first and second spatial dimensions; ∘ a colorimetric dimension in a colorimetric space; and ∘ a spectral dimension in a spectral space;the third image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two components in said third dimension, said generation comprising the application of an inverse transfer function to determine, from the respective gray levels of each pixel of the second image, at least one component in the third dimension of the corresponding pixels of the third image, the transfer function corresponding to a data matrix comprising, for each pixel of the first image, a respective value (V) defining a transformation of the at least one component in said third dimension (DM3) into a gray level, the matrix comprising different values ​​such that the at least one component in said third dimension of at least one pixel is transformed differently from the at least one component in said third dimension of at least one other pixel;and authenticating the third image by comparing the pixels of the third image with the pixels of a first reference image. ;

[0023] The invention thus makes it possible to reliably and securely authenticate a second grayscale image in accordance with the principle of the invention. To do this, a third party must have the appropriate optical acquisition means to perform an optical capture of the second image formed on a medium and must then use the necessary computer processing means to generate and then authenticate the third image. Without the inverse transfer function, it is not possible to reconstruct the third image from the second grayscale image IMG2, which makes the second grayscale image a reliable security device offering a good level of security.

[0024] According to a particular embodiment, the authentication of the third image comprises a comparison of the components in the third dimension of the pixels of said first and third images to determine whether they coincide.

[0025] According to a particular embodiment, said generation comprises a conversion, according to the inverse transfer function, of the gray level of each pixel of the second image into a single component in the third dimension of a corresponding pixel of the third image.

[0026] According to a particular embodiment, said generation comprises a conversion, according to the inverse transfer function, of the gray level of each pixel of the second image into a linear combination of at least two components in the third dimension of a corresponding pixel of the third image.

[0027] According to a particular embodiment, the generation of the third image further comprises: determining for each pixel of the third image at least one missing component in the third dimension, other than said at least one component in the third dimension obtained by applying said inverse transfer function for said pixel, by interpolating corresponding components in the third dimension of pixels neighboring said pixel in said third image.

[0028] According to a particular embodiment, N=3 and the third dimension is a colorimetric dimension in a colorimetric space so that: the third image generated during said generation is a color image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two color components in said colorimetric space; and the second image acquired during said optical acquisition comprises a plurality of pixels each having a gray level representative of at least one color component of a corresponding pixel of the third image, said generation comprising the application of the inverse transfer function to determine, from the gray levels of the pixels of the second image, at least one color component of each pixel of the third image.

[0029] According to a particular embodiment, N=3 and the third dimension is a spatial dimension other than the first and second spatial dimensions so that: the third image generated during said generation is a 3D image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two position components in said third spatial dimension; and the second image acquired during said optical acquisition comprises a plurality of pixels each having a gray level representative of at least one position component in the third spatial dimension of a corresponding pixel of the third image, said generation comprising the application of the inverse transfer function to determine, from the gray levels of the pixels of the second image, at least one position component in the third spatial dimension of each pixel of the third image.

[0030] According to a particular embodiment, N=3 and the third dimension is a spectral dimension in a spectral space so that: the third image generated during said generation is a spectral image comprising a plurality of pixels characterized by their respective position in the first and second dimensions and by at least two spectral intensity components in said third spectral dimension; the second image acquired during said optical acquisition comprises a plurality of pixels each having a gray level representative of at least one spectral intensity component of a corresponding pixel of the third image, said generation comprising the application of the transfer function to determine, from the gray levels of the pixels of the second image, at least one spectral intensity component of each pixel of the third image.

[0031] In a particular embodiment, the different steps of the processing method of the invention are determined by computer program instructions.

[0032] Consequently, the invention also relates to a computer program on an information medium (or computer programs on the same information medium or separate information mediums), this program being capable of being implemented in an electronic device such as a computer, this program comprising instructions adapted to the implementation of the steps of a processing method as defined in this document.

[0033] The invention also relates to a recording medium (or information medium) readable by a computer, and comprising instructions of a computer program as mentioned above.

[0034] Note that the programs mentioned in this disclosure may use any programming language, and may be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0035] In addition, the recording media mentioned above may be any entity or device capable of storing the program. For example, the medium may include a storage medium, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a magnetic recording medium, for example a floppy disk or a hard disk.

[0036] On the other hand, the recording media may correspond to a transmissible medium such as an electrical or optical signal, which can be conveyed via an electrical or optical cable, by radio or by other means. The program according to the invention can in particular be downloaded from a network such as the Internet.

[0037] Alternatively, the recording media may correspond to an integrated circuit in which the program is incorporated, the circuit being adapted to carry out or to be used in carrying out the method in question.

[0038] The invention also relates to a first system (called the security system) configured to implement the security method of the invention as defined in this document, and a second system (called the processing system) configured to implement the processing method of the invention as defined in this document.

[0039] More specifically, the invention relates to a security system comprising: a determination module configured to acquire a first image characterized in at least N dimensions comprising a first and a second spatial dimension and a third dimension, N being an integer greater than or equal to 3, said third dimension defining one of: ∘ a spatial dimension other than the first and second spatial dimensions; ∘ a colorimetric dimension in a colorimetric space; and ∘ a spectral dimension in a spectral space; the first image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two components in said third dimension;a compression module configured to compress the first image into a second grayscale image comprising a plurality of pixels each having a grayscale representative of at least one component in said third dimension of a corresponding pixel of the first image, said compression comprising the application of a transfer function to determine, from the components in said third dimension of each pixel of the first image, the grayscale of the corresponding pixels of the second image; and a formation module configured to form the second grayscale image on a support. ;

[0040] The invention also relates to a treatment system comprising: an optical acquisition module configured to perform an optical acquisition of a second grayscale image comprising a plurality of pixels formed on a support, to obtain image data defining a grayscale of each pixel of said second image; a generation module configured to generate, from said image data, a third image characterized in at least N dimensions comprising a first and a second spatial dimension (DM1, DM2) and a third dimension (DM3), N being an integer greater than or equal to 3, said third dimension defining one of: ∘ a spatial dimension other than the first and second spatial dimensions; ∘ a colorimetric dimension in a colorimetric space; and ∘ a spectral dimension in a spectral space;the third image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two components in said third dimension, said generation comprising the application of an inverse transfer function to determine, from the respective gray levels of each pixel of the second image, at least one component in the third dimension of the corresponding pixels of the third image; and an authentication module configured to authenticate the third image by comparing the pixels of the third image with the pixels of a first reference image.;

[0041] It should be noted that the various embodiments defined in this document in relation to the security method and the processing method of the invention as well as the associated advantages apply in a similar manner to the security system and the processing system of the invention.

[0042] For each step of the security method and for each step of the processing method, the security system and the processing system of the invention may comprise a corresponding module configured to carry out said step.

[0043] According to one embodiment, the invention is implemented in the security system and in the processing system by means of software and / or hardware components. In this regard, the term "module" can correspond in this document to a software component, a hardware component or a set of hardware and software components.

[0044] A software component corresponds to one or more computer programs, one or more sub-programs of a program, or more generally to any element of a program or software capable of implementing a function or a set of functions, as described below for the module concerned. Such a software component can be executed by a data processor of a physical entity (terminal, server, gateway, router, etc.) and is likely to access the hardware resources of this physical entity (memories, recording media, communication buses, electronic input / output cards, user interfaces, etc.).

[0045] Similarly, a hardware component is any element of a hardware assembly capable of implementing a function or set of functions, as described below for the module concerned. It may be a programmable hardware component or one with an integrated processor for running software, for example an integrated circuit, a smart card, a memory card, an electronic card for running firmware, etc. Brève description des dessins

[0046] Other characteristics and advantages of the present invention will emerge from the description given below, with reference to the appended drawings which illustrate exemplary embodiments thereof which are not in any limiting nature. In the figures: [ Fig. 1 ] There figure 1 schematically represents a first source image, according to a particular embodiment of the invention; [ Fig. 2 ] There figure 2 schematically represents a first source image, according to a particular embodiment of the invention; [ Fig. 3 ] There figure 3 schematically represents the principle of a security method and a processing method, according to a particular embodiment of the invention; [ Fig. 4 ] There figure 4 represents, in the form of a diagram, the steps of a security method and a processing method, according to a particular embodiment of the invention; [ Fig. 5 ] There figure 5 schematically represents a security system, according to a particular embodiment of the invention; [ Fig. 6 ] There figure 6 schematically represents functional modules implemented by a security system, according to a particular embodiment of the invention; [ Fig. 7 ] There figure 7 represents, in the form of a diagram, the steps of a security method, according to a particular embodiment of the invention; [ Fig. 8 ] There figure 8 schematically represents a first source image, according to a particular embodiment of the invention; [ Fig. 9 ] There figure 9 schematically represents the arrangement of a first source image, according to a particular embodiment of the invention; [ Fig. 10 ] There figure 10 schematically represents the generation by compression of a second grayscale image during the security process, according to a particular embodiment of the invention; [ Fig. 11 ] There figure 11 schematically represents a transfer function, according to a particular embodiment of the invention; [ Fig. 12 ] There figure 12 schematically represents a second grayscale image generated during the implementation of a security method, according to a particular embodiment of the invention; [ Fig. 13 ] There figure 13 schematically represents the formation of a second grayscale image on a support, according to a particular embodiment of the invention; [ Fig. 14 ] There figure 14 schematically represents a processing system, according to a particular embodiment of the invention; [ Fig. 15 ] There figure 15 schematically represents functional modules implemented by a processing system, according to a particular embodiment of the invention; [ Fig. 16 ] There figure 16 represents, in the form of a diagram, the steps of a treatment method, according to a particular embodiment of the invention; [ Fig. 17 ] There figure 17 schematically represents the generation of a third image during the implementation of a processing method, according to a particular embodiment of the invention; [ Fig. 18 ] There figure 18 schematically represents the intermediate state of a third image being generated during the implementation of a processing method, according to a particular embodiment of the invention; [ Fig. 19 ] There figure 19 schematically represents a third image according to a component in the third dimension, according to a particular embodiment of the invention; [ Fig. 20 ] There figure 20 schematically represents the performance of an interpolation operation during the generation of a third image during the processing method, according to a particular embodiment of the invention; [ Fig. 21 ] There figure 21 schematically represents a third image generated during the implementation of a processing method, according to a particular embodiment of the invention; [ Fig. 22 ] There figure 22 schematically represents a bar code encoded according to the principle of the invention in a particular embodiment; [ Fig. 23 ] There figure 23 schematically represents the application of a security method for encoding a bar code, according to a particular embodiment of the invention; [ Fig. 24 ] There figure 24 schematically represents the implementation of a security method and a processing method for respectively encoding and decoding an SLI type image, according to a particular embodiment of the invention; Description des modes de réalisation

[0047] The invention proposes to form grayscale images acting as a security device that can be reliably and securely authenticated and is difficult to falsify or reproduce.

[0048] The invention provides in particular for compressing any first digital image into a second digital image in grayscale and forming this second image on a support to manufacture an authenticatable security device from the grayscale of the second image.

[0049] The invention further provides a corresponding method for reading the second image physically formed on a medium in order to authenticate the security device by comparing this second image with a digital reference image, namely the first image from which the second grayscale image was created by compression.

[0050] As a preliminary, some reminders are provided below on the notion of image. An image is a visual representation of a pattern or an object. An image can be of various natures as explained below. This document considers pixelated images, namely images formed by a plurality of pixels in any arrangement, for example according to a matrix of pixels (other arrangements are however possible). This arrangement of pixels is arranged in at least two spatial dimensions (2D). In addition, each pixel can be characterized by at least one other third dimension which can be of various natures depending on the type of the image considered. This third dimension can be one of: an additional spatial dimension, other than the first and second spatial dimensions; a colorimetric dimension in a colorimetric space; and a spectral dimension in a spectral space.

[0051] Thus, an image within the meaning of the invention may be a 2D image whose pixels are arranged in two spatial dimensions or a 3D image whose pixels are arranged in three spatial dimensions. In the case of a 3D image, each pixel of the image is therefore characterized by three spatial dimensions.

[0052] Similarly, an image can be defined in grayscale or in color. In the case of a 2D color image, each pixel is therefore characterized in two spatial dimensions and in one colorimetric dimension in a given color space (for example: "RGB" color space also called "RGB" for "Red-Green-Blue", or "CMYK" also called "CMYK" for "cyan-magenta-yellow-black"). Each pixel is defined by its respective position in the 2 spatial dimensions and by color components in the color space considered, for example by 3 color components in the RGB color space or by 4 color components in the CMYK color space.

[0053] In the case of a 3D color image, each pixel is therefore characterized in three spatial dimensions and in one colorimetric dimension in a colorimetric space.

[0054] So, the figure 1 represents the example of a color image 2 characterized in N=3 dimensions noted DM1, DM2 and DM3. The first and second dimensions DM1, DM2 are spatial dimensions according to directions noted x and y, while the third dimension DM3 is a colorimetric dimension in the RGB color space.

[0055] Image 2 is formed from a plurality of pixels 6 which are distributed along the x and y directions. Each pixel 6 has a color defined by 3 color components in the RGB space. In other words, the pixels 6 of the color image 2 are defined in this example by their respective position in the first and second dimensions DM1, DM2, and by 3 Red / Green / Blue color components in the third colorimetric dimension DM3.

[0056] As represented in figure 1 ,the pixel arrangement 6 of image 2 can therefore be decomposed into three planes 4a, 4b and 4C of pixels in the RGB color space. These planes 4a, 4b and 4c each define a respective color component 6a, 6b and 6c of the pixels in the RGB color space.

[0057] In general, the number of components characterizing each pixel 6 in the third colorimetric dimension DM3 can vary and depends on the color space considered. Thus, the pixels of an image can be characterized for example by 4 color components in a CMYK colorimetric dimension. It is subsequently considered that an image within the meaning of the invention is characterized in particular by at least two components in the third dimension DM3, whether it is a colorimetric dimension or another type as described below.

[0058] There figure 2 represents another example of a 3D image, denoted 8, characterized in 3 spatial dimensions denoted DM1, DM2 and DM3 (N=3). The spatial dimensions DM1, DM2 and DM3 here define a 3-dimensional space according to directions x, y and z respectively. The 3D image 8 is thus formed from a plurality of pixels 6 which are distributed according to the directions x, y and z. In other words, the pixels 6 of the image 8 are defined in this example by their respective position in the three spatial dimensions DM1 (along x), DM2 (along y) and DM3 (along z). It is considered here that the image 8 comprises at least two distinct planes of pixels 6 according to the direction z, which means that the pixels 6 of the 3D image 8 are characterized by at least two components in the spatial dimension DM3 (along z).

[0059] In the case of a 3D grayscale image, each pixel 6 furthermore has a particular grayscale. In the case of a 3D color image, each pixel furthermore has a color in a fourth colorimetric dimension in a given color space, this color being characterized by color components (at least 2) in a given color space (for example 3 color components in the RGB space, 4 color components in the CMYK space, etc.).

[0060] An image within the meaning of the invention may also be a so-called “SLI” image for “Stereo Laser Image”, which comprises a plurality of images, typically images of the same object or pattern from distinct angles. In other words, a grayscale SLI image is also characterized in 3 spatial dimensions, namely first and second dimensions DM1, DM2 along x and y directions, and a third angular dimension DM3.

[0061] An image within the meaning of the invention may also be a 2D spectral image, namely an image characterized in a first and a second spatial dimension (along directions x and y for example) and in a third spectral dimension in a spectral space (“IR” for infrared, “UV” for ultraviolet, visible light range, etc.). Each pixel of a 2D spectral image is then defined by its respective position in the first and second spectral dimensions and by at least two spectral intensity components in a given spectral space.

[0062] In the same way, an image within the meaning of the invention may be a spectral 3D image, characterized in 3 spatial dimensions and in one spectral dimension in a spectral space.

[0063] The invention also applies to images which have 4 or more dimensions, i.e. at least 2 spatial dimensions and at least two other dimensions among the aforementioned types.

[0064] In view of the above, the invention therefore applies to various types of images of at least 3 dimensions, including 2D color images, 3D grayscale images, 3D color images, 2D or 2D spectral images, SLI grayscale or color images, etc.

[0065] The invention, according to its various embodiments, thus implements a first method, called the security method, comprising: the acquisition of a first image of N dimensions as defined above (N being an integer greater than or equal to 3), this first image comprising a plurality of pixels defined by their respective position in first and second dimensions and by at least two components in a third spatial, colorimetric or spectral dimension; a compression of the first image into a second grayscale image comprising a plurality of pixels each having a grayscale representative of one or more components in the third dimension of a corresponding pixel of the first image; and the formation of the second grayscale image on a support. This second image forms a, or is part of a, security device within the meaning of the invention.

[0066] The invention also relates to a second method, called a processing method for reading a second grayscale image according to the invention. The invention provides in particular, according to different embodiments, a processing method comprising: the optical acquisition of a second grayscale image comprising a plurality of pixels formed on a support, to obtain image data defining a grayscale of each pixel of the second image; and the generation, from the image data, of a third image characterized in at least N dimensions (N being an integer greater than or equal to 3) comprising a first and a second spatial dimension and a third dimension among the aforementioned types, the third image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two components in the third dimension.The third image can further be authenticated by comparing the pixels of the third image with the pixels of a first reference image, i.e. the source image from which the second image was formed in accordance with the security method of the invention.

[0067] The invention also relates to corresponding computer programs as well as systems for implementing the methods of the invention, namely a first system (called a security system) for implementing the security method of the invention and a second system (processing system) for implementing the processing method of the invention.

[0068] Other aspects and advantages of the present invention will emerge from the exemplary embodiments described below with reference to the drawings mentioned above.

[0069] Unless otherwise indicated, elements common or similar to several figures bear the same reference signs and have identical or similar characteristics, so that these common elements are generally not described again for the sake of simplicity.

[0070] THE figures 3 And 4 schematically represent the concept of the invention, according to a particular embodiment. A security system (or encoding system) SY1 is configured to implement a security method comprising steps S2-S6 ( figure 4 ). More particularly, the security system SY1 acquires or determines (S2) a first image IMG1 (also called source image) characterized in at least N dimensions comprising a first and a second spatial dimension DM1, DM2 and a third dimension DM3, N being an integer greater than or equal to 3.

[0071] The spatial dimensions DM1 and DM2 define a spatial space according to x and y directions respectively. The third dimension DM3 defines one of: a spatial dimension other than the first and second spatial dimensions DM1, DM2; a colorimetric dimension in a colorimetric space (RGB, CYMK); and a spectral dimension in a spectral space.

[0072] The first image IMG1 may be, in particular, a 2D color image, a 3D grayscale or color image, a 2D or 3D spectral image, etc. as already described above.

[0073] The first source image IMG1 acquired in S2 comprises a plurality of pixels PX defined by their respective position in the first and second spatial dimensions DM1, DM2 and by at least two components in the third dimension DM3.

[0074] During a compression step S4, the security system SY1 performs a digital compression of the first image IMG1 into a second image IMG2 in gray levels (in 2D), this second image IMG2 comprising a plurality of pixels PL each having a gray level NG representative of at least one component in the third dimension DM3 of a corresponding pixel PX of the first image IMG1. In this document, compression (or digital compression) means a compression of data, namely image data in this case. This compression makes it possible to compress image data so as to obtain, from image data of a source image, compressed image data representative of a compressed image.

[0075] To do this, the compression S4 comprises the application of a transfer function F1 to determine, from the components in the third dimension DM3 of each pixel PX of the first image IMG1, the gray levels NG of the corresponding pixels PL of the second image IMG2. As described below, this data compression involves a partial loss of information from the first image IMG1, insofar as, for each pixel PX of the first image IMG1, at least one component (a single component or possibly at least two components) in the third dimension DM3 is lost during the compression, which means that it is not encoded in the gray level of the corresponding pixel PL of the second image IMG2.

[0076] The SY2 security system also proceeds to the formation S6 of the second image IMG2 in grayscale on any support DC1, such as on a card-type document or other ( figure 3 ). This training can be carried out in various ways as described later.

[0077] This grayscale image IMG2 thus forms on the DC1 medium a security device which encodes, or represents, in compressed form the first image IMG1. This second image IMG2 can then be read and decompressed from the inverse of the transfer function F1, then compared to the original image IMG1 for authentication.

[0078] More specifically, a processing system (or reading system) SY2 is configured to implement a processing method comprising steps S10-S14 ( figure 4 ). The processing system SY2 thus performs the optical acquisition (S10) of the second image IMG2 in gray level comprising a plurality of pixels PL formed on the support DC1, to obtain image data DT3 defining a gray level NG of each pixel PL of the second image IMG2.

[0079] The processing system SY2 then generates (S12), from the image data DT3, a third image IMG3 characterized in at least N dimensions comprising the first and second spatial dimensions DM1, DM2 and the third dimension DM3 as already described above. The third image IMG3 comprises a plurality of pixels PI defined by their respective position in the first and second spatial dimensions DM1, DM2 and by at least two components in the third dimension DM3. The third dimension DM3 of the third image IMG3 is the same as that characterizing the first source image IMG1 from which the security system SY1 generated the second image IMG2.

[0080] To do this, the generation S12 of the third image IMG3 comprises the application of an inverse transfer function F1 -1< (i.e. the inverse of the transfer function F1) to determine, from the respective gray levels NG of each pixel PL of the second image IMG2, at least one component in the third dimension DM3 of the corresponding pixels PI of the third image IMG3. This generation S12 amounts to decompressing the second gray level image IMG2 into a third image IMG3 which is characterized in the same dimensions DM1, DM2 and DM3 as the first source image IMG1 from which the second gray level image IMG2 was generated during the securing process.

[0081] In this document, decompression (or digital decompression) means decompression of data, namely image data in this case. This decompression makes it possible to decompress image data so as to obtain, from image data of a source image, decompressed image data representative of a decompressed image.

[0082] As indicated previously, the compression defined by the transfer function F1 is accompanied by a partial loss of information. Thus, in a similar manner, decompression by application of the inverse transfer function F1 -1< generally only allows recovery of a portion of the information initially contained in the first image IMG1 (except in special cases). For each pixel PL of the second image IMG2, at least one component in the third dimension DM3 of a corresponding pixel PI in the third image IMG3 is not defined by the gray level NG of said pixel PL of the second image IMG2. In other words, the gray level NG of each pixel PL of the second image IMG2 encodes only a portion of the components in the third dimension DM3 of the corresponding pixel PI in the third image IMG3 (at least one component in DM3 is not encoded in the gray levels NG of the second image IMG2).As described below, the missing component(s) in the third dimension DM3 for each pixel PI of the third image IMG3 can be obtained by interpolation from the neighboring pixels PI, in order to complete the components of the pixels PI in the third dimension DM3 and thus obtain a complete image IMG3.

[0083] The processing system SY2 can then authenticate (S14) the third image IMG3 by comparing the pixels PI of the third image IMG3 with the pixels PX of the first image IMG1 which serves as a reference image.

[0084] As described above, various types of source image IMG1 are possible within the scope of the invention. The invention applies in particular to particular cases in which the first image IMG1 is one of: a 2D grayscale image; a 2D color image; a 3D image (grayscale or color); a spectral image (2D or 3D); and an SLI image (grayscale or color).

[0085] The concept of the invention is now described below in particular embodiments. Premier exemple de réalisation

[0086] THE figures 5 et 6 schematically represent the security system (or encoding system) SY1 according to a particular embodiment. More precisely, it is considered here that the system SY1 comprises a first electronic device DV1 and a training device LS1.

[0087] The SY1 security system is configured to implement a security method (or encoding method), as described for example with reference to figures 3-4 .

[0088] The device DV1 comprises a processor 10, a rewritable volatile memory (RAM type) 12 and a rewritable non-volatile memory MR1. The memory MR1 here constitutes a recording medium (or information medium) conforming to a particular embodiment, readable by the device DV1, and on which is recorded a computer program PG1 conforming to a particular embodiment. This computer program PG1 comprises instructions for the execution of at least part of the steps of a security method according to a particular embodiment.

[0089] The MR1 memory is also used to store image data DT1 defining a first image IMG1, image data DT2 defining a second grayscale image IMG2, and a transfer function F1 that forms a data mask MK1. The nature and use of these elements will be described in more detail later.

[0090] The device DV1 is further capable of cooperating with the training device LS1, the latter being configured to form, from the data DT2 transmitted by the device DV1, a second image IMG2 on a medium as described below. In this example, the training device LS1 also comprises a processor 15 and a computer program PG2 stored in a non-volatile memory, although other examples not using such a program PG2 are possible. The computer programs PG1 and PG2 collectively form a computer program for implementing the security method according to a particular embodiment of the invention.

[0091] Instead of sending the image data DT2, the first device DV1 can send instructions to control the forming device LS1 so that it forms the second image IMG2 on a medium.

[0092] In a particular example, the LS1 training device is included in, or is part of, the DV1 device.

[0093] Various image formation techniques can be implemented by the formation device LS1. It is considered here that the formation device LS1 is configured to project laser radiation LS1 onto the support DC1 to form each pixel PL of the second image IMG2, by delivering an energy which is a function of the desired gray level of said pixel PL.

[0094] Alternatively, the second image IMG2 may be formed on the medium DC1 by at least one of the following formation techniques: formation by laser engraving; formation by printing on the support; and formation by micro-perforations of the support.

[0095] The IMG2 image can in particular be formed by printing, using any suitable technique (inkjet, offset, thermal transfer, etc.).

[0096] As represented in figure 6 according to a particular embodiment, the processors 2 and 15 controlled respectively by the computer programs PG1 and PG2 here implement a certain number of modules, namely: an MD2 determination module, an MD4 generation module and an MD6 training module.

[0097] More specifically, the determination module MD2 is configured to acquire the first image IMG1 in the form of image data DT1.

[0098] The MD4 generation module is configured to generate a second grayscale image IMG2 by compressing the first image IMG1.

[0099] The MD6 training module is configured to train the second image IMG2 on a DC1 medium.

[0100] The configuration and operation of the MD2-MD6 modules of the SY1 security system will appear more precisely in the implementation examples described below. It is important to note that the MD2-MD6 modules as shown in figure 6 represent only a non-limiting example of implementation of the invention. Generally speaking, for each step of the security method of the invention, the security system SY1 of the invention may comprise a corresponding module configured to carry out said step.

[0101] A particular embodiment is now described with reference to figures 7-13 . More precisely, a security process is implemented by the security system represented in figures 5-6 by running the computer programs PG1 and PG2.

[0102] It is assumed that the security system SY1 acquires (S22) a first 2D color image, denoted IMG1, in the form of image data DT1. As shown in figure 8 , the color image IMG1 is characterized in 3 dimensions (N=3), namely a first spatial dimension DM1 (along the x direction), a second spatial dimension DM2 (along the y direction) and a third colorimetric dimension DM3 in a given colorimetric space.

[0103] In general, the first image IMG1 thus comprises a plurality of pixels PX defined by their respective position in the spatial dimensions DM1 and DM2 and by P color components in the third dimension DM1, P being a natural integer greater than or equal to 2. In this example, it is considered that the third dimension DM3 is defined in the colorimetric space CYMK, so that P=4. Each pixel PX of the first image IMG1 is thus characterized by a color CL defined by 4 color components CP1, CP2, CP3 and CP4 in the third colorimetric dimension DM3. In this example, the components CP1, CP2, CP3 and CP4 correspond to the color intensities in the fundamental colors cyan / yellow / magenta / black of the CYMK space, respectively.

[0104] For example, pixel PX1 of the color image IMG1 has a particular position along the x and y directions, as well as a color CL1 defined by components CP1, CP2, CP3 and CP4 in the CYMK space.

[0105] Examples of implementation in other color spaces are however possible. Other examples are notably possible in which P=3 (in RGB space for example), or P=2 or any other appropriate values ​​greater than or equal to 2, depending on the color space considered.

[0106] Note that the SY1 security system can acquire the DT1 image data in any suitable manner. The SY1 system can thus determine the IMG1 image by consulting its non-volatile memory MR1 in which the IMG1 image is stored, or receive the IMG1 image from the outside.

[0107] The SY1 security system realizes (S24, figure 7 ) then a compression of the first image IMG1 into a second grayscale image IMG2. In other words, the image data DT1 is compressed so as to obtain compressed image data DT2 which defines the image IMG2 in grayscale.

[0108] As represented in figure 10 ,this second image IMG2 comprises a plurality of pixels PL each having a gray level NG representative of a single color component (among CP1-CP4) in the third dimension DM3 of a corresponding pixel PX of the first color image IMG1. In other words, the gray levels NG of the second image IMG2 generated in S24 encode in a compressed manner the color CL of the pixels PX of the first image IMG1. This is a compression with loss of information insofar as a single component among CP1-CP4 is retained for each pixel PX of the first image IMG1 so as to be encoded by a gray level NG representative in the pixel PL located at a corresponding position in the second image IMG2.

[0109] For purely illustrative purposes, we consider that the first image IMG1 comprises the pixels PX noted respectively PX1 to PX16, as represented in figure 9 .For example, pixel PX1 of image IMG1 has a color CL defined by the following color components: CP1=41 (cyan); CP2=166 (yellow); CP3=146 (magenta) and CP4=118 (black). Thus, a single color component among CP1-CP4 of pixel PX1 in CYMK space is represented by the gray level NG of a pixel PL1 located at a position corresponding to PX1 in the pixel matrix PL of the second image IMG2. The same applies to the other pixels PX of the first image IMG1.

[0110] As represented in figure 10 ,the security system SY1 applies, during the compression step S24, a transfer function F1 to determine, from the components CP1-CP4 in the third colorimetric dimension DM3 of each pixel PX of the first image IMG1, the gray levels NG of the corresponding pixels PL of the second image IMG2. In the example considered here, the application of the transfer function F1 thus causes the selection, for each pixel PX of the first image IMG1, of a single color component (from CP1-CP4) and the transformation of this single component into a gray level NG of a corresponding pixel PL of the second image IMG2. As already indicated, this compression involves a loss of information insofar as among the 4 color components CP1-CP4 of each pixel PX of the first image IMG1, only one component is found coded in the gray level NG of the corresponding pixel PL in the second image IMG2.This means that the color components not selected by the transfer function F1 for each pixel PX of the first image IMG1 are lost during compression.

[0111] More generally, the transfer function F1 defines for each pixel PX of the first image IMG1 a compression of the P color components in the third dimension DM3 into a single color component among the P color components, which is coded by the gray level NG of the corresponding pixel PL in the second image (where P = 4 in this example). The selection of the single color component by the transfer function F1 can be random, which makes it possible to strengthen the security level as will appear below, although other implementation examples are possible.

[0112] The transfer function F1 thus defines a correspondence between the color component selected for each pixel PX of the first image IMG1 and the corresponding gray level NG in the associated pixel PL of the second image IMG2. The function F1 defines, for example, a calculation for converting a color component included in a first value range into a gray level NG included in a second value range. For example, 1000 different levels of a color component can be compressed by the transfer function F1 into corresponding gray levels NG coded over a range of 256 different gray levels (coded from 0 to 255).

[0113] As represented in figures 10-11 ,the function F1 can be presented for example in the form of a data mask (or data matrix) MK1 which includes for each pixel PX of the first image IMG1 a respective value V which defines the transformation of a single component among CP1-CP4 into a representative gray level NG. The transfer function F1 can however be presented in other forms.

[0114] For example, the figures 11 et 12 illustrate the compression of the first image IMG1 represented in figure 9 by applying the transfer function F1. More precisely, we assume that the transfer function F1 defines the mask MK1 represented in figure 11 .The transfer function F1 comprises values ​​V1-V16 (collectively denoted V), each of which defines which of the color components CP1-CP4 of a corresponding pixel PX of the image IMG1 is converted into a gray level NG of an associated pixel PL of the second image IM2. For example, it is assumed that the values ​​V are integers between 0 and 4 so that the values ​​0, 1, 2 and 3 cause the selection of the color components CP1, CP2, CP3 and CP4 respectively. For example, the pixel PL1 of the second image IMG2 thus has a gray level NG which is representative of the component CP1 of the corresponding pixel PX1 of the first image IMG1 (cf. figure 9 ). According to a particular example, the transfer function F1 defines for example for the pixel PL1 a gray level NG such that: NG = α 1 ⋅ CP 1 where α1 is a positive real coefficient that defines the conversion of the component CP1 into a corresponding gray level NG. In a particular example, the coefficient α1 is such that α1 = 1 (identity function) so that the pixel PL1 has a gray level of 41, representative of the level of the color component CP1 (which is also of value 41) of the pixel PX1, as represented in figure 12 . The same principle applies to all PL pixels in the second image IMG2.

[0115] Thus, in the same way, the pixel PL2 of the second image IMG2 presents for example a gray level NG representative of the component CP2 of the corresponding pixel PX2 of the first image IMG1, so that: NG = α 2 ⋅ CP 2 where α2 is a positive real coefficient that defines the conversion of the CP2 component into a corresponding gray level NG. In a particular example, the coefficient α2 is such that α2 = 1 (identity function) so that the PL2 pixel has a gray level NG of 169, representative of the level of the CP2 color component (which is also of value 41) of the PX2 pixel, as represented in figure 12 .

[0116] According to a particular example, during generation step S24 ( figure 7 ), the security system SY1 (namely the security device DV1 in this example) further inserts into the second grayscale image IMG2 one or more positioning marks (markers) in and / or around the second image IMG2. As explained below, these positioning marks can subsequently be used to read the second image IMG2 during the processing method.

[0117] As represented in figure 13 , once the second image IMG2 is generated in S24 ( figure 7 ), the security system SY1 forms the second image IMG2 in grayscale on a support DC1. The second image IMG2 thus forms on the support DC1 a security device which can be authenticated by comparing the first image IMG1 (from which the second image IMG2 was obtained) with a third image IMG3 which, as described below, is obtained by applying the inverse of the transfer function F1 to the second image IMG2 present on the support DC1 (cf. figure 3 ).

[0118] The second IMG2 image can thus be reliably and securely authenticated with appropriate means. In addition, the second IMG2 image is difficult to falsify or reproduce, which makes it possible to secure the DC1 medium.

[0119] In the example considered here, the medium is a card although other mediums are possible.

[0120] The second image IMG2 is for example produced by laser engraving on the DC1 support, other formation techniques being possible as already indicated (printing, microperforations, etc.).

[0121] More precisely, in this example, it is considered that the forming device LS1 used to form (S26) the second image IMG2 projects laser radiation RY1 onto the support DC1 so as to form each pixel PL of the second image IMG2 by delivering energy which is a function of the gray level NG of said pixel PL.

[0122] As already indicated, the invention also relates to a processing method (or reading method) making it possible to read and authenticate the second image IMG2 present on the medium DC1.

[0123] THE figures 14 et 15schematically represent the processing system (or reading system) SY2 according to a particular embodiment. More precisely, it is considered here that the system SY2 comprises an optical acquisition device CR1 and a processing device DV2.

[0124] The SY2 processing system is configured to implement a processing method (or reading method), as described for example with reference to figures 3-4 .

[0125] The optical acquisition device CR1 is configured to perform the optical acquisition of images, such as the image IMG2 located on the support DC1 as shown in figure 13 .The device CR1 is for example a shooting device (camera, sensor or other) capable of optically capturing the second image IMG2 formed on the support DC1. Image data DT3 representative of the second optically captured image IMG2 are thus generated by the optical acquisition device CR1 and then transmitted to the processing device DV2.

[0126] The processing device DV2 comprises a processor 20, a rewritable volatile memory (RAM type) 22 and a rewritable non-volatile memory MR2. The memory MR2 here constitutes a recording medium (or information medium) conforming to a particular embodiment, readable by the device DV2, and on which is recorded a computer program PG3 conforming to a particular embodiment. This computer program PG3 comprises instructions for the execution of at least part of the steps of a processing method according to a particular embodiment.

[0127] The memory MR2 is also used to store the image data DT3 transmitted by the optical acquisition device CR1, image data DT4 generated by the processing device DV2 from the image data DT3, and an inverse transfer function F1 -1< which is the inverse of the transfer function F1 mentioned above. The nature and use of these elements will be described in more detail later.

[0128] In a particular example, the optical acquisition device CR1 is included in, or is part of, the processing device DV2.

[0129] As represented in figure 14 according to a particular embodiment, the processor 20 controlled respectively by the computer program PG3 here implements a certain number of modules, namely: an acquisition module MD10, a generation module MD12 and, possibly, an authentication module MD14.

[0130] More specifically, the acquisition module MD10 is configured to carry out an optical acquisition of a second grayscale image IMG2 comprising a plurality of pixels PL formed on a support DC1, to obtain image data DT3 defining a grayscale level of each pixel of the second image IMG2.

[0131] The generation module MD12 is configured to generate, from the image data DT3 obtained by the optical acquisition module MD10, a third image IMG3 characterized in at least N dimensions comprising a first and a second spatial dimension DM1, DM2 and a third dimension DM3, N being an integer greater than or equal to 3. This third dimension DM3 corresponds to that of the first image IMG1 from which the second image IMG2 originates. In the example considered here, the third dimension DM3 is therefore a colorimetric dimension in the colorimetric space CYMB.

[0132] Generally, the third dimension DM3 of the third image IMG3 may vary depending on the case and depends on the nature of the first image IMG1 from which it was generated (step S24, figure 7 ) the second image IMG2 formed on the support DC1. As already indicated, the third dimension DM3 of the first image IMG1, and therefore also of the third image IMG3, defines one of: a spatial dimension other than the first and second spatial dimensions DM1, DM2; a colorimetric dimension in a colorimetric space; and a spectral dimension in a spectral space.

[0133] The third image comprises a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 and by at least two components in the third dimension DM3.

[0134] The authentication module MD14 is configured to carry out an authentication of the third image IMG3 generated by the generation module MD12, by comparing the pixels of the third image IMG3 with the pixels of a first reference image, namely the source image IMG1 from which it was generated (step S24, figure 7 ) the second image IMG2 located on the DC1 support.

[0135] The configuration and operation of the MD10-MD14 modules of the SY2 security system will appear more precisely in the implementation examples described below. It is important to note that the MD10-MD14 modules as shown in figure 15 represent only a non-limiting example of implementation of the invention. In general, for each step of the processing method of the invention, the SY2 processing system of the invention may comprise a corresponding module configured to carry out said step.

[0136] A particular embodiment is now described with reference to figures 13 et 17 -21. More specifically, a processing method is implemented by the processing system represented in figures 14-15 by running the PG3 computer program.

[0137] It is assumed that the optical acquisition device CR1 performs the optical acquisition (S30, figure 16 ) of the second grayscale image IMG2 which comprises a plurality of pixels PL formed on the support DC1, to obtain image data DT3 defining a grayscale level NG of each pixel PL of the second image IMG2. To do this, a user takes, for example, using a camera, a photo or a “scan” of the physical image IMG2 located on the support DC1. According to a particular example, the processing system SY2 (or at least the device CR1) is included in a mobile phone of the “smartphone” type (or any other equivalent devices) which is equipped with a camera for capturing an image of the support DC1.

[0138] The device CR1 generates image data DT3 representative of the second image IMG2 present on the medium DC1, and transmits this data DT3 to the processing device DV2. In this example, the image data DT3 thus received is stored in the non-volatile memory MR2 of the processing device DV2.

[0139] As indicated previously, the second image IMG2 whose optical acquisition was made on the support DC1 may comprise one or more positioning marks (marks) in and / or around said second image IMG2, although implementations without such marks are also possible. These positioning marks may be used to read the second image IMG2 during the processing method. More precisely, in a particular example, after the optical acquisition step S30, the processing device DV2 processes the received image data DT3 and, if such marks are detected, the processing device DV2 determines the position of the positioning marks in and / or around the second image IMG2. The processing device DV2 then compares the position of the positioning marks with predefined positions (their theoretical positions) and resizes the second image IMG2 from a result of this comparison.This step makes it possible in particular to correct optical and perspective defects which may occur during the shooting (optical acquisition S30) and / or which may be induced previously during the training step S26 (. figure 7 ) , for example in the case of laser engraving.

[0140] During a generation step S32, the processing device DV2 then generates, from the received image data DT3, a third image IMG3 characterized in the same dimensions DM1, DM2 and DM3 as those of the first image IMG1 from which it was generated (S24, figure 7 ) the second image IMG2 during the securing process. In the example considered here, the third image IMG3 is therefore characterized in the first and second spatial dimensions DM1, DM2 and in the third colorimetric dimension DM3 in the colorimetric space CYMB. The third image IMG3 is generated and stored in the non-volatile memory MR2 in the form of image data DT4.

[0141] The third image IMG3 thus generated (S32) comprises a plurality of pixels defined by their respective position in the first and second spatial dimensions DM1, DM2 and by one of the P components in the third dimension DM3, where P=4 in this example since the colorimetric space considered is the CYMB space.

[0142] To do this, during the generation step S32, the processing device DV2 applies an inverse transfer function F1 -1< to determine, from the respective gray levels NG of each pixel PL of the second image IMG2, a single color component in the third dimension DM3 of the corresponding pixels PI of the third image IMG3 ( figure 17 ) . The inverse transfer function F1 -1< is the inverse of the transfer function F1 previously used in S24 ( figure 7 ) by the SY1 security system to generate the second image IMG2.

[0143] Thus, the processing device DV2 converts (S32), according to the inverse transfer function F1 -1< , the gray level NG of each pixel PL of the second image IMG2 into a single color component (among CP1-CP4) in the third colorimetric dimension DM3 of a corresponding pixel PI of the third image IMG3. In other words, the inverse transfer function F1 -1< defines, for each pixel PL of the second image IMG2, a transformation of the gray level NG of said pixel PL into a single color component in the colorimetric space CYMB for a corresponding pixel PI of the third image IMG3. The application of the inverse transfer function F1 -1< thus causes a selection, for each pixel PL of the second image IMG2, of a single component in the third colorimetric dimension DM3 for a corresponding pixel PI of the third image IMG3. Other implementations are however possible as explained below.

[0144] As already described, the application of the transfer function F1 causes a loss of information during compression (S24, figure 7 ) from the source image IMG1 to the second image IMG2 in grayscale. Therefore, the application of the inverse transfer function F1 -1< only allows to recover (decompress) a sub-part of the color components CP1-CP4 of the pixels PX of the first source image IMG1, namely a single component among CP1-CP4 in the example considered here (other examples are possible where more than one component is recovered in the third dimension DM3). The single component thus recovered can vary according to the pixel PL considered in the second image IMG2. The missing color components in each pixel PI of the third image IMG3, i.e. the color components which were deleted during compression (S32, figure 7 ) and which are therefore not recovered by applying the inverse transfer function F1 -1< to the gray levels of the corresponding PL pixels of the second image IMG2, are obtained by interpolation from the color components obtained for the PI pixels of the third image IMG3 by applying the inverse transfer function F1 -1<.

[0145] For purely illustrative purposes, it is assumed in this example that during generation step S32 ( figure 16 ), the processing device DV2 determines the gray level NG of each pixel PL of the second image IMG2 and generates, by applying the inverse transfer function F1 -1< on these gray levels NG, image data DT4 representative of the third color image IMG3, as illustrated in figure 18 .At this stage, the third image IMG3 is incomplete since the application of the inverse transfer function F1 -1< from the gray levels NG of each pixel PL of the second image IMG2 only allows determining a single color component (among CP1-CP4) for each corresponding pixel PI of the third image IMG3.

[0146] As represented in figure 18 , the third image IMG3 here comprises pixels PI successively noted PI1 to PI16, corresponding respectively to the pixels PL1 to PL16 of the second image IMG2. The application of the inverse transfer function F1 -1< only allows for example to determine the first color component CP1 (cyan) of the pixel PI1 of the image IMG3 from the gray level NG of the corresponding pixel PL1 of the second image IMG2. The components CP2 (yellow), CP3 (magenta) and CP4 (black) are therefore missing at this stage insofar as the prior compression carried out in S24 ( figure 7 ) caused the suppression of these color components. This principle applies analogously to the other PI pixels of the third image IMG3.

[0147] Also, still during the S32 generation stage ( figure 16 ), the processing device DV2 performs an interpolation from the color components CP1-CP4 obtained by applying the inverse transfer function F1 -1< to determine the other missing color components in the pixels PI of the third image IMG3. More precisely, the processing device DV2 determines for each pixel PI of the third image IMG3 the missing color components, other than the single color component obtained by applying the inverse transfer function F1 -1< for said pixel PI, by interpolating corresponding color components, in the third dimension DM3, of pixels neighboring said pixel PI in the third image IMG3.

[0148] There figure 19 represents for example, the first color component CP1 (cyan) of the pixels PI1, P13, PI10 and PI11 of the third image IMG3 which is recovered in S32 ( figure 16 ) by applying the inverse transfer function F1 -1< from the gray level NG of the corresponding pixels PL of the second image IMG2 acquired in S30. As illustrated in figure 19 , the first color component CP1 (cyan) is missing in the other pixels PI of the third image IMG3 since, in the present case, the inverse transfer function F1 -1< defines only one component in the third dimension DM3 for each pixel PI of the third image IMG3, from a gray level NG of a corresponding pixel PL of the second image IMG2.

[0149] To complete the third-dimensional components DM3 obtained by applying the inverse transfer function F1 -1< , the missing color components of each pixel PI of the third image IMG3 are thus calculated by interpolation from the same components, of neighboring pixels, obtained by applying the inverse transfer function F1 -1< . As shown as an example in figure 20 , the first missing component CP1 of pixel PI2 of the third image IMG3 is determined by interpolation from the first component CP1 of neighboring pixels PI1 and PI3 obtained by applying the inverse transfer function F1 -1< (the value 42 equal to the average of 41 and 43 is assigned to the color component CP1 of pixel PI2 of the third image IMG3). According to the same principle, each missing first color component CP1 is thus completed in the third image IMG3.

[0150] Various interpolation techniques are possible to complete the missing third-dimensional components DM3 in the third image IMG3, the choice of which one is used being left to the discretion of the person skilled in the art. This interpolation is based, for example, on calculating an average of the corresponding components of X neighboring pixels PI according to the same fundamental color of the color space considered (X being an integer greater than or equal to 2).

[0151] As represented in figure 20 , this interpolation operation makes it possible to obtain for each pixel PI of the third image IMG3 a first color component CP1 close to that of the corresponding pixel PX of the first source image IMG1.

[0152] The other color components CP2, CP3 and CP4 of the PI pixels of the third image IMG3 are completed in a similar manner by interpolation from the corresponding color components CP2, CP3 and CP4 obtained by applying the inverse transfer function F1 -1< for neighboring PI pixels. The interpolation makes it possible to complete the color components obtained by applying the inverse transfer function F1 -1< to define all the color components CP1-CP4 defining the respective color of each PI pixel of the third color image IMG3.

[0153] The DV2 processing device generates (S32, figure 16 ) so the third color image IMG3 as shown in figure 21 by applying the inverse transfer function F1 -1< , the result of this interpolation being completed by interpolation as described above.

[0154] The third image IMG3 is usually a degraded quality version of the first source image IMG1 from which it was generated (S24, figure 7 ) the second grayscale image IMG2, this is due to the fact that the compression carried out during the security process is accompanied by a partial loss of information. However, in certain special cases, it is possible that the interpolation carried out during generation (S32, figure 16 ) during the processing process results in exactly the first image IMG1.

[0155] The second image IMG2 formed in grayscale on the support DC1 thus acts as a security device insofar as this second image IMG2 can be authenticated from the inverse of the transfer function F1 used to form the second image IMG2 during the security process.

[0156] Thus, according to a particular example, the processing method further comprises a step S34( figure 16 )authentication during which the processing system SY2 authenticates the third image IMG3. This authentication is based on a comparison of the third image IMG3 generated in S32 with the first image IMG1 serving as a reference image. More precisely, the processing system SY2 performs a comparison of the components in the third dimension DM3 of the pixels (PI, PX) of the first image IMG1 and the third image IMG3 to determine whether these components coincide. As indicated above, a degradation in image quality may impact the third image IMG3 compared to the first source image IMG1. This is why the processing system SY2 does not necessarily seek a perfect match between the colors of the corresponding pixels of the images IMG1 and IMG3 for the third image IMG3 to be successfully authenticated.According to a particular example, the third image IMG3 is successfully authenticated if the degree of similarity between images IMG1 and IMG3 reaches a predetermined threshold level.

[0157] The invention thus makes it possible to form grayscale images acting as security devices which can be reliably and securely authenticated, and which are difficult to falsify or reproduce, which makes it possible to secure any object or medium.

[0158] The high level of protection thus obtained results in particular from the fact that several technologies of different natures are combined to limit or prevent any falsifications or illicit reproductions. Indeed, to form a second grayscale image IMG2 according to the concept of the invention, a forger must implement a digital compression of the first source image IMG1 which implies adequate computer processing means, and must also have the necessary means to physically reproduce (by printing, laser engraving or other as the case may be) this second image IMG2 on a medium with a sufficient level of quality to be able to be read and exploited subsequently. Without the appropriate transfer function, the generation of the second grayscale image IMG2 is not possible.

[0159] Similarly, to authenticate a second grayscale image IMG2 in accordance with the principle of the invention, a third party must have the appropriate optical acquisition means to perform an optical capture of the second image IMG2 formed on a medium and then must use the computer processing means necessary to generate and authenticate a third image IMG3, as described above. Without the inverse transfer function, it is not possible to reconstruct the third image IMG3 from the second grayscale image IMG2.

[0160] According to a particular example illustrated in figures 22-23 , the first source image IMG1 from which is generated (S24, figure 7) the second grayscale image IMG2 may be, or include, any barcode such as a 1D (one-dimensional) barcode or a 2D (two-dimensional) code. The second grayscale image IMG2 may thus include in encrypted form a barcode whose reading and interpretation is only possible with the appropriate inverse transfer function F1 -1<.

[0161] Furthermore, as indicated previously, the nature of the first source image IMG1 within the meaning of the invention (and therefore also of the third image IMG3) may vary depending on the case. In the exemplary embodiments described above, the first image IMG1 is a 2D color image which therefore comprises pixels characterized in two spatial dimensions DM1, DM2 and in a third colorimetric dimension DM3. The invention, however, applies in a similar manner to other types of source images IMG1 whose pixels are characterized in at least three dimensions, including two spatial dimensions DM1, DM2 and a third dimension DM3 whose nature may vary depending on the case. As already indicated, it is considered here that the source image IMG1 comprises a plurality of pixels defined by their respective position in the first and second spatial dimensions DM1, DM2 and by at least two components in the third dimension DM3.

[0162] Thus, the principle of the invention can be applied in particular to a source image IMG1 conforming to one of the following types: 2D color images (as already described in the examples above); 3D grayscale images; 3D color images; spectral images (in 2D or 3D); and SLI images (in grayscale or color).

[0163] Whatever the nature of the source image IMG1 considered, it is digitally compressed in the form of a 2D grayscale image - denoted IMG2 - by the security method of the invention. Each pixel of the second image IMG2 thus generated has a grayscale level NG which represents or encodes a single component in the third dimension DM3 of a corresponding pixel of the source image IMG1. The grayscale levels NG of the second image IMG2 represent for example a component in a third spatial dimension, or in a third spectral dimension, of the source image IMG1.

[0164] Similarly, regardless of the nature of the source image IMG1 from which the second grayscale image IMG2 was generated, the implementation of the processing method of the invention makes it possible to generate, from this second grayscale image IMG2, a third image IMG3 which is characterized in the same dimensions DM1, DM2 and DM3 as the source image IMG1. The third image IMG3 thus generated is similar (or even identical in certain particular cases) to the source image IMG1. It is then possible to authenticate the third image IMG3 by comparing it with the first source image IMG1 which serves as a reference image.

[0165] The principle of the invention described above in particular examples relating to the compression and decompression of a 2D color source image IMG1 applies analogously to the other types of images mentioned above. Particular implementations of the invention are described above purely as examples. Unless otherwise indicated, the steps of the security method and the processing method of the invention are implemented by the security system SY1 ( figures 5-6 ) and by the SY2 processing system ( figures 14-15 ) previously described, in the same way as in the particular examples described above. Second example of realization (first variant):

[0166] Thus, according to a second particular example, the first image IMG1 is characterized in 3 dimensions (N=3), namely two spatial dimensions DM1, DM2 (along x and y directions) and in a third spatial dimension DM3 other than the dimensions DM1 and DM2. This third dimension DM3 can correspond to a third direction z, in a Cartesian reference frame for example (case where the source image IMG1 is a 3D image), or can correspond to an angular dimension (case where the source image IMG1 is of the SLI type).

[0167] According to a first variant, the first source image IMG1 acquired in S22 ( figure 7 )during the securing method is for example a 3D image comprising a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 (according to the x and y directions respectively) and by at least two position components in a third spatial dimension DM3 (according to the z direction). The second grayscale image IMG2 generated in S24 ( figure 7 ) during compression then comprises a plurality of pixels each having a gray level NG representative of a single position component in the third spatial dimension DM3 of a corresponding pixel of the first source image IMG1.

[0168] During step S24 of generating the security method, the security system SY1 performs a compression of the first 3D image IMG1 by applying a transfer function F1 as already described above, to determine, from the position components in the third spatial dimension DM3 of each pixel of the first source image IMG1, the gray levels NG of the corresponding pixels of the second image IMG2.

[0169] Furthermore, during the processing process, the third image IMG3 generated in S32 ( figure 16 ) by the processing system SY2 is also a 3D image characterized by the three spatial dimensions DM1, DM2 and DM3 following the x, y and z directions respectively. The third image IMG3 thus comprises a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 and by at least two position components in the third spatial dimension DM3.

[0170] The second grayscale image IMG2 previously acquired during optical acquisition S30 ( figure 16 ) comprises a plurality of pixels each having a gray level NG representative of a position component in the third spatial dimension DM3 of a corresponding pixel of the third image IMG3.

[0171] During the step S32 of generating the processing method, the processing system SY2 performs a decompression of the second image IMG2 by applying an inverse transfer function F1 -1< as already described above, so as to determine, from the gray levels NG of the pixels of the second image IMG2, a position component in the third spatial dimension DM3 of each pixel of the third image IMG3. The missing position components in the third image IMG3 can be completed by interpolation from the position components obtained by applying the inverse transfer function F1 -1< as already described above. Second example of implementation (second variant):

[0172] According to a second variant, the first source image IMG1 acquired in S22 ( figure 7) during the securing process is for example an SLI image comprising a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 (according to the x and y directions respectively) and by at least two angular position components in a third spatial dimension DM3. The second grayscale image IMG2 generated in S24 ( figure 7 ) during compression then comprises a plurality of pixels each having a gray level NG representative of at least one angular position component in the third spatial dimension DM3 of a corresponding pixel of the first image IMG1.

[0173] During the generation step S24, the security system SY1 performs a compression of the first SLI image IMG1 by applying a transfer function F1 as already described above, to determine, from the angular position components in the third spatial dimension DM3 of each pixel of the first source image IMG1, the gray levels NG of the corresponding pixels of the second image IMG2.

[0174] In addition, the third image IMG3 generated by the SY2 processing system during S32 generation ( figure 16 ) of the processing method is also an SLI image comprising a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 (according to the x and y directions respectively) and by at least two angular position components in the third spatial dimension DM3. The second image IMG2 previously acquired during the optical acquisition S30 ( figure 16 ) comprises a plurality of pixels each having a gray level NG representative of at least one angular position component in the third spatial dimension DM3 of a corresponding pixel of the third image IMG3.

[0175] During the generation step S32 of the processing method, the processing system SY2 performs a decompression of the second image IMG2 by applying an inverse transfer function F1 -1< as already described above, to determine, from the gray levels NG of the pixels of the second image IMG2, an angular position component in the third spatial dimension DM3 of each pixel of the third image IMG3. The missing angular position components in the third image IMG3 can be completed by interpolation from the angular position components obtained by applying the inverse transfer function F1 -1< as already described above.

[0176] For example, the figure 24illustrates the implementation of the invention for compressing a source image IMG1 of SLI type, comprising 4 sub-images IMG10-IMG13 of the same object (a face in this example) according to different angular positions, into a second grayscale image IMG2. Each pixel of the source image IMG1 is thus defined by its respective position in the first and second dimensions DM1, DM2 (according to the respective directions x and y) and by at least two components in said third angular dimension DM3. The application of the inverse transfer function F1 -1< makes it possible to obtain, from the second grayscale image IMG2, a third image IMG3 of SLI type also comprising 4 sub-images IMG30-IMG33 according to different angular positions. The angular sub-images IMG30, IMG31, IMG32 and IMG33 of the third image IMG3 are respectively representative of the angular sub-images IMG10, IMG11, IMG12 and IMG13 of the source image IMG1. Third example of realization:

[0177] According to a third exemplary embodiment, the first image IMG1 acquired in S22 ( figure 7 ) during the securing process is a spectral image characterized in 3 dimensions (N=3), namely two spatial dimensions DM1, DM2 (along x and y directions) and in a third spectral dimension DM3 in a spectral space (UV, IR, visible, etc. spectral space). The first source image IMG1 comprises a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 and by at least two spectral intensity components in the third spectral dimension DM3. The second image IMG2 thus generated in S24 ( figure 7 ) during compression comprises a plurality of pixels each having a gray level NG representative of at least one spectral intensity component of a corresponding pixel of the first source image IMG1.

[0178] During step S24 of generating the security method, the security system SY1 performs a compression of the first spectral image IMG1 by applying a transfer function F1 as already described above, to determine, from the spectral intensity components of each pixel of the first source image IMG1, the gray levels NG of the corresponding pixels of the second image IMG2.

[0179] Furthermore, during the processing process, the third image IMG3 generated in S32 ( figure 16 )is also a spectral image characterized by the two spatial dimensions DM1, DM2 (along the x and y directions respectively) and by the spectral dimension DM3 in the aforementioned spectral space. The third image IMG3 thus comprises a plurality of pixels defined by their respective position in the first and second dimensions DM1, DM2 and by at least two position components in the third spectral dimension DM3.

[0180] The second grayscale image IMG2 acquired during optical acquisition S30 ( figure 16 ) then comprises a plurality of pixels each having a gray level NG representative of a single position component in the third spatial dimension DM3 of a corresponding pixel of the third image IMG3.

[0181] During the generation step S32 of the processing method, the processing system SY2 performs a decompression of the second image IMG2 by applying the inverse transfer function F1 -1< as already described above, to determine, from the gray levels NG of the pixels of the second image IMG2, a spectral intensity component in the third dimension DM3 of each pixel of the third image IMG3. The spectral intensity components missing in the third image IMG3 can be completed by interpolation from the spectral intensity components obtained by applying the inverse transfer function F1 -1< as already described above. Generalization of the concept of the invention:

[0182] In the embodiments described above, the second grayscale image IMG2 generated during compression S24 ( figure 7) comprises a plurality of pixels each having a gray level NG representative of a single component CP in the third dimension DM3 of a corresponding pixel of the first source image IMG1. For example, the gray level NG is such that NG = α.CP, where α is a positive real coefficient and CP is a single component (in the third dimension DM3) selected by the transfer function F1. Thus, in the examples illustrated in the Figures 7-13 And 16-21 , the gray level NG of each pixel PL of the second image IMG2 encodes only one of the color components CP1-CP4 in the color space CYMB. However, the invention is not limited to this particular case.

[0183] Thus, more generally, the transfer function F1 used during the compression step S24 represented in figure 7 (or at step S4 in figure 4) is a bijective function applied to the components in the third dimension DM3 of each pixel PX of the first source image IMG1 to obtain a corresponding gray level NG in the corresponding pixel PL of the second grayscale image IMG2. Thus, in the considered case where there are 4 components CP1-CP4 in the third dimension DM3, for each pixel PX of the first image IMG1, the gray level NG of the corresponding pixel PL in the second image IMG2 is such that: NG = F 1 CP 1 , CP 2 , CP 3 , CP 4

[0184] As already indicated, the number P of components in the third dimension DM3 that each pixel PX of the first source image IMG1 comprises can vary depending on the case, it being understood that P ≥ 2. Also, in general, the gray levels NG of the pixels PL of the second image IMG2 in gray levels are such that: NG = F 1 CP 1 , … , CPP

[0185] For example, in the case where the first source image IMG1 is a 2D color image defined in the RGB color space, then each pixel PX of the first image IMG1 has 3 color components CP1, CP2 and CP3 according to the colors red, green and blue. In this case, the gray levels NG of the pixels PL of the second grayscale image IMG2 are such that: NG = F 1 CP 1 , CP 2 , CP 3

[0186] In essence, the bijective function F1 is a function that can be inverted. This function defines a transformation from an input space corresponding to the first source image IMG1 to an output space corresponding to the second grayscale image IMG2.

[0187] The transfer function F1 can be, for example, a linear function or an affine function. Various types of mathematical function F1 are possible depending on the application considered.

[0188] according to a particular example, the second grayscale image IMG2 may comprise a plurality of pixels having a grayscale level NG representative of a linear combination of at least two components in the third dimension DM3 of a corresponding pixel of the first source image IMG1, this linear combination being defined by the transfer function F1 for each pixel of the first source image IMG1. This variant may apply regardless of the nature of the third dimension DM3 among those mentioned above.

[0189] Thus, in the particular case where there are 4 different components CP1-CP4 in the third dimension DM3, the transfer function F1 can define a representative gray level NG for each pixel PX of the first source image IMG1 so that: NG = α 1 ⋅ CP 1 + α 2 ⋅ CP 2 + α 3 ⋅ CP 3 + α 4 ⋅ CP 4 where α1, α2, α3 and α4 are real coefficients (weights) defining a linear transformation of the components CP1-CP4 in the third dimension DM3 into a corresponding gray level of a corresponding pixel PL of the second gray-level image IMG2.

[0190] According to a particular example, at least one coefficient among α1-α4 is zero for each pixel PX of the first source image IMG1.

[0191] For example, it is possible to encode several color components of each pixel PX of a first color image IMG1 in the gray level of the corresponding pixel PL in the image IMG2 generated in S24 ( figure 7 ).The gray level NG of each pixel PL of the second image IMG2 is for example representative of a linear combination of two color components in the color space CYMB of the corresponding pixel PX of the first color image IMG1. The pixels PL of the second image IMG2 may for example have a gray level NG successively representing the following linear combinations of the corresponding pixels PX: NG=CP1+CP2 (for the pixel PX1), NG=CP2-CP3 (for the pixel PX2), NG=CP3-CP4 (for the pixel PX3),...

[0192] The transfer function F1 then defines, for each pixel PX of the first source image IMG1 (or for at least a non-zero part of these pixels), a compression of the components in the third dimension DM3 of said pixel PX, into a linear combination of at least two of these components, this combination being represented by a gray level NG in the corresponding pixel PL of the second image IMG2. To do this, the transfer function F1 assigns non-zero weights to certain components (at least 2) in the third dimension DM3 to combine them together in order to obtain a representative gray level. Note however that the transfer function F1 assigns a zero weight (suppression) to at least one component in the third dimension DM3 of each pixel of the first source image IMG1.

[0193] Generally, the compression carried out during the security method of the invention is a lossy compression of data so that among the P components characterizing in the third dimension DM3 each pixel of the first source image IMG1 (with P ≥ 2), the transfer function F1 only selects Q components which are represented (or encoded) in the gray level NG of the corresponding pixel of the second image IMG2, P and Q being integers such that 1 ≤ Q < P. Thus, among the P components in the third dimension DM3 of each pixel of the first source image IMG1, at least one component is not encoded in the gray levels of the corresponding pixel of the second image IMG2. The gray level of each pixel in the second image IMG2 is therefore representative of Q components in the third dimension DM3, the selected components being able to vary for each pixel of the first source image IMG1.

[0194] According to a particular example, Q=1 (selection of a single component in DM3) or Q = 2 (selection of two components in DM3) for each pixel of the first source image IMG1.

[0195] It should also be noted that the order in which the steps of the security process and the processing process are carried out as described above constitutes only an example of implementation, with variations being possible.

[0196] A person skilled in the art will understand that the embodiments and variants described above constitute only non-limiting examples of implementation of the invention. In particular, a person skilled in the art may envisage any adaptation or combination of the embodiments and variants described above in order to meet a very specific need.

Claims

1. A securing method implemented by a security system (SY1), the method comprising: - acquiring (S2) a first image (IMG1) characterized in at least N dimensions comprising a first and a second spatial dimension (DM1, DM2) and a third dimension (DM3), N being an integer greater than or equal to 3, said third dimension defining one of: o a spatial dimension other than the first and second spatial dimensions; o a colorimetric dimension in a color space; and ∘ a spectral dimension in a spectral space; the first image comprising a plurality of pixels (PX) defined by their respective position in the first and second dimensions and by at least two components (CP1-CP4) in said third dimension; - compressing (S4) the first image into a second grey-scale image (IMG2) comprising a plurality of pixels (PL) each having a grey scale (NG) representative of at least one component in said third dimension (DM3) of a corresponding pixel of the first image, said compression comprising applying a transfer function (F1) to determine, from the components in said third dimension of each pixel of the first image, the grey scales of the corresponding pixels of the second image, the transfer function corresponding to a data matrix comprising, for each pixel of the first image, a respective value (V) defining a transformation of the at least one component in said third dimension (DM3) into a grey scale, the matrix comprising different values such that the at least one component in said third dimension of at least one pixel is transformed differently from the at least one component in said third dimension of at least one other pixel; and - forming (S6) the second grey-scale image on a support (DC1).

2. The method according to claim 1, wherein the pixels of the second grey-scale image each have a grey-scale representative of a single component, in the third dimension, of a corresponding pixel in the first image, said single component being selected by the transfer function for each pixel of said first image.

3. The method according to claim 1, wherein the pixels of the second grey-scale image have a grey scale representative of a linear combination of at least two components in the third dimension of a corresponding pixel of the first image, said linear combination being defined by the transfer function for each pixel of said first image.

4. The method according to any one of claims 1 to 3, wherein the compression is a lossy compression such that among the P components in the third dimension of each pixel of the first image, the transfer function selects only Q components which are represented in the grey scale of the corresponding pixel in the second image, P and Q being integers such that 1 ≤ Q < P.

5. The method according to any one of claims 1 to 4, wherein N=3 and the third dimension is a colorimetric dimension in a colorimetric space such that: - the first image acquired during said acquisition is a color image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two color components in said color space; and - the second image generated during said compression comprises a plurality of pixels each having a grey scale representative of at least one color component of a corresponding pixel of the first image, - said compression comprising the application of the transfer function to determine, from the color components of each pixel of the first image, the grey scales of the corresponding pixels of the second image.

6. The method according to any one of claims 1 to 4, wherein N=3 and the third dimension is a spatial dimension other than the first and second spatial dimensions such that: - the first image acquired during said acquisition is a 3D image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two position components in said third spatial dimension; and - the second image generated during said compression comprises a plurality of pixels each having a grey scale representative of at least one position component in the third spatial dimension of a corresponding pixel of the first image, - said compression comprising the application of the transfer function to determine, from the position components in the third spatial dimension of each pixel of the first image, the grey scales of the corresponding pixels of the second image.

7. The method according to any one of claims 1 to 6, wherein said second image forms a security device which is authenticatable by comparing the first image with a third image obtained by applying the inverse of the transfer function to the second image present on the support.

8. The method according to any one of claims 1 to 7, wherein the second image is formed on the support by at least one of the following formation methods: - formation of the second image by laser engraving; - printing the second image on the support; and - formation of the second image by micro-perforations.

9. A treatment method implemented by a treatment system (SY2), comprising: - optically acquiring (S10) a second grey-scale image (IMG2) comprising a plurality of pixels (PL) formed on a support (DC1), to obtain image data (DT3) defining a grey scale (NG) of each pixel of said second image; - generating (S12), from said image data, a third image (IMG3) characterized in at least N dimensions comprising a first and a second spatial dimension (DM1, DM2) and a third dimension (DM3), N being an integer greater than or equal to 3, said third dimension defining one of: o a spatial dimension other than the first and second spatial dimensions; o a colorimetric dimension in a colorimetric space; and ∘ a spectral dimension in a spectral space; the third image comprising a plurality of pixels (PI) defined by their respective position in the first and second dimensions and by at least two components (CP1-CP4) in said third dimension, said generation comprising applying an inverse transfer function (F1-1) to determine, from the respective grey scales of each pixel of the second image, at least one component in the third dimension of the corresponding pixels of the third image, the inverse transfer function corresponding to an inverse function of a data matrix comprising, for each pixel of the third image, a respective value (V) defining a transformation of the at least one component in said third dimension (DM3) into a grey scale, the matrix comprising different values such that the at least one component in said third dimension of at least one pixel is transformed differently from the at least one component in said third dimension of at least one other pixel; and - authenticating (S14) the third image by comparing the pixels of the third image with the pixels (PX) of a first reference image (IMG1).

10. The method according to claim 9, wherein authenticating the third image comprises comparing the components in the third dimension of the pixels of said first and third images to determine whether they match.

11. The method according to claim 9 or 10, wherein said generation comprises a conversion, according to the inverse transfer function, of the grey scale of each pixel of the second image into a single component in the third dimension of a corresponding pixel of the third image.

12. The method according to claim 9 or 10, wherein said generation comprises a conversion, according to the inverse transfer function, of the grey scale of each pixel of the second image into a linear combination of at least two components in the third dimension of a corresponding pixel of the third image.

13. The method according to any one of claims 9 to 12, wherein generating the third image further comprises: - determining for each pixel of the third image at least one missing component in the third dimension, other than said at least one component in the third dimension obtained by applying said inverse transfer function for said pixel, by interpolating corresponding components in the third dimension of the pixels neighboring said pixel in said third image.

14. The method according to any one of claims 9 to 13, wherein N=3 and the third dimension is a colorimetric dimension in a colorimetric space such that: - the third image generated during said generation is a color image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two color components in said color space; and - the second image acquired during said optical acquisition comprises a plurality of pixels each having a grey scale representative of at least one color component of a corresponding pixel of the third image, said generation comprising the application of the inverse transfer function to determine, from the grey scales of the pixels of the second image, at least one color component of each pixel of the third image.

15. The method according to any one of claims 9 to 13, wherein N=3 and the third dimension is a spatial dimension other than the first and second spatial dimensions such that: - the third image generated during said generation is a 3D image comprising a plurality of pixels defined by their respective position in the first and second dimensions and by at least two position components in said third spatial dimension; and - the second image acquired during said optical acquisition comprises a plurality of pixels each having a grey scale representative of at least one position component in the third spatial dimension of a corresponding pixel of the third image, said generation comprising the application of the inverse transfer function to determine, from the grey scales of the pixels of the second image, at least one position component in the third spatial dimension of each pixel of the third image.