Method for recovering at least one optical parameter from an ophthalmic lens, system for implementing this method and non-transient storage means

Abstract

METHOD AND SYSTEM FOR RECOVERING AN OPTICAL PARAMETER FROM AN OPHTHALMIC LENS. The present invention relates to a method for recovering at least one optical parameter from an ophthalmic lens comprising: obtaining (10) an image of a first and a second pattern using an image capture device located in a first position; from that image, obtaining (12) a first data set of at least a part of the first pattern that is seen through the lens by the image capture device and obtaining (14) a second data set of at least a part of the second pattern that is seen directly, i.e., outside the lens by the image capture device; recovering (16) at least one optical parameter using the first and second data sets and taking into account the relative positions of the image capture device, the lens and the first and second patterns.

Description

1 / 53 METHOD FOR RECOVERING AT LEAST ONE OPTICAL PARAMETER FROM AN OPHTHALMIC LENS, SYSTEM FOR IMPLEMENTING THIS METHOD AND NON-TRANSIENT STORAGE MEANS FIELD OF THE INVENTION

[0001] The present invention relates to a method and system for recovering at least one optical parameter of an ophthalmic lens. BACKGROUND OF THE INVENTION

[0002] In order to duplicate an ophthalmic lens, it is necessary to know the optical parameters that define the correction applied by the lens and, in particular, the lens power.

[0003] For this purpose, automatic lens meters are known.

[0004] However, these ophthalmic instruments are mainly used by optometrists or opticians, for example, i.e., professionals in eye health. In fact, they require skills to perform measurements in the correct lens position, are more or less expensive, include specific hardware, and their robustness is not optimized for use by just anyone. Consequently, these instruments are not intended for low-skilled eye health professionals (also called ECPs), nor for consumers for do-it-yourself measurements. SUMMARY OF THE INVENTION

[0005] One objective of the disclosure is to overcome the aforementioned disadvantages of the state of the art.

[0006] To that end, the disclosure provides a method for recovering at least one optical parameter of an ophthalmic lens, comprising: - Obtain an image of a first and a second pattern using an image capture device located in a Petition 870260049400, dated 05 / 25 / 2026, page 7 / 133 2 / 53 first position; - From this image, obtain an initial data set of at least a portion of the first pattern seen by the image capture device through the lens; - From this image, obtain a second set of data from at least a portion of the second pattern that is seen by the image capture device outside the lens; - to recover at least one optical parameter using the first and second datasets and taking into account the positions, relative to each other, of the image capture device, the lens, and the first and second standards.

[0007] In the method according to the revelation, the steps of obtaining the first and second sets of data and recovering at least one optical parameter can be performed automatically, so that if the step of obtaining an image of the first and second standards is performed by a consumer or poorly qualified ECP, the only contribution of that consumer or poorly qualified ECP will be the use of an image capture device, which is much easier to do than using a lens meter.

[0008] In the method according to the revelation, the steps of obtaining an image of the first and second standards can be done semi-automatically, so that usability and accuracy / reproducibility are much greater.

[0009] Thus, at least one optical parameter of the lens can be retrieved by means of a very simple input from the consumer side or from the poorly qualified ECP.

[0010] Thus, the method according to the revelation can be used, for example, to manufacture a duplicate of an ophthalmic lens in a very simple and convenient way for the consumer, without the Petition 870260049400, dated 05 / 25 / 2026, page 8 / 133 3 / 53 need to spend time in an optician's.

[0011] The disclosure also provides a system for implementing a method to retrieve at least one parameter of an ophthalmic lens, wherein the method comprises: - Obtain an image of a first and a second pattern using an image capture device located in a first position; - From this image, obtain an initial data set of at least a portion of the first pattern seen by the image capture device through the lens; - From this image, obtain a second set of data from at least a portion of the second pattern that is seen by the image capture device outside the lens; - to recover at least one optical parameter using the first and second datasets and taking into account the positions, relative to each other, of the image capture device, the lens, and the first and second standards, in which the system comprises: - at least one processor; - a mobile device equipped with an image capture device; and - a reflective device or a computer.

[0012] The disclosure further provides a computer program product comprising one or more sequences of instructions that are accessible to a processor and that, when executed by the processor, cause the processor to: - Obtain an image of a first and a second pattern using an image capture device located in a first position; - From this image, obtain an initial set of data from Petition 870260049400, dated 05 / 25 / 2026, page 9 / 133 4 / 53 at least a part of the first pattern that is seen by the image capture device through the lens; - From this image, obtain a second set of data from at least a portion of the second pattern that is seen by the image capture device outside the lens; - to recover at least one optical parameter using the first and second datasets and taking into account the positions, relative to each other, of the image capture device, the lens, and the first and second standards.

[0013] The revelation also provides a means of non-transient storage, in which it stores one or more sequences of instructions that are accessible to a processor and that, when executed by the processor, cause the processor to: - Obtain an image of a first and a second pattern using an image capture device located in a first position; - From this image, obtain an initial data set of at least a portion of the first pattern seen by the image capture device through the lens; - From this image, obtain a second set of data from at least a portion of the second pattern that is seen by the image capture device outside the lens; - to recover at least one optical parameter using the first and second datasets and taking into account the positions, relative to each other, of the image capture device, the lens, and the first and second standards.

[0014] Since the advantages of the system, the computer program product, and the non-transient storage medium are similar to those of the method, they are not repeated in this document.

[0015] The system, the computer program product and the medium Petition 870260049400, dated 05 / 25 / 2026, page 10 / 133 5 / 53 of non-transient storage are advantageously configured to execute the method in any of its execution modes. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] For a fuller understanding of the description given herein and its advantages, reference is now made to the brief descriptions below, considered in connection with the accompanying drawings and the detailed description, where equal reference numbers represent equal parts.

[0017] FIG. 1 is a flowchart showing the steps of a method for recovering at least one optical parameter of an ophthalmic lens according to the present disclosure, in a particular embodiment.

[0018] FIG. 2 is a schematic view of an ophthalmic lens, an image capture device, patterns and a reflection device used in a particular embodiment of a method for recovering at least one optical parameter of an ophthalmic lens according to the present disclosure.

[0019] FIG. 3 is a schematic view of a reflection device used in the particular embodiment of Figure 2 and shows a coordinate system of the reflection device.

[0020] FIG. 4 is a schematic view illustrating a function involved in calculations comprised in the method according to the present disclosure, in the particular embodiment of Figure 2.

[0021] FIG. 5 is a schematic view illustrating another function involved in the calculations comprised in the method according to the present disclosure, in the particular embodiment of Figure 2.

[0022] FIG. 6 shows an example of a pattern that can be used in the method according to the present disclosure.

[0023] FIGS. 7, 8, 9, 10, 11 and 12 show the processing steps performed on the pattern example in Figure 6 according to the method of the present disclosure. Petition 870260049400, dated 05 / 25 / 2026, page 11 / 133 6 / 53

[0024] FIG. 13 shows another example of a pattern that can be used in the method according to the present disclosure.

[0025] FIG. 14 shows first and second patterns and a structure that can be used in the method according to the present disclosure and arranged according to a particular embodiment.

[0026] FIGS. 15 and 16 illustrate the steps of the method according to the present disclosure, in an embodiment in which the lens is mounted in a spectacle frame.

[0027] FIG. 17 shows examples of patterns that can be used in the method according to the present disclosure.

[0028] FIG. 18 shows other examples of patterns that can be used in the method according to the present disclosure.

[0029] FIG. 19 is a schematic view illustrating other embodiments of the method and system according to the present disclosure, involving a smartphone and a computer.

[0030] FIG. 20 shows other examples of patterns that can be used in the method according to the present disclosure.

[0031] FIG. 21 illustrates the pitch, roll and yaw axes of a smartphone used in an embodiment of the method and system according to the present disclosure.

[0032] FIG. 22 illustrates a portion of a smartphone screen used for smartphone positioning in an embodiment of the method and system according to the present disclosure.

[0033] FIG. 23 illustrates a non-limiting example of a remote positioning pattern used for remote positioning of a smartphone in an embodiment of the method and system according to the present disclosure.

[0034] FIG. 24 illustrates a non-limiting example of a model used for remote positioning of a smartphone in an embodiment of the method and system according to the present Petition 870260049400, dated 05 / 25 / 2026, page 12 / 133 7 / 53 revelation.

[0035] FIG. 25 illustrates a non-limiting example of three different brightness levels of the model in Figure 24, involved in a smartphone screen brightness adaptation process, in an embodiment of the method and system according to the present disclosure.

[0036] FIG. 26 illustrates a non-limiting example of user guidance for eyeglass frame detection in an embodiment of the method and system according to the present disclosure.

[0037] FIG. 27 is a graph illustrating the calculation of lens power in an embodiment of the method and system according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0038] In the following description, the figures in the drawings are not necessarily to scale, and certain features may be shown in a generalized or schematic form for clarity and conciseness or for informational purposes. Furthermore, although the elaboration and use of various embodiments are discussed in detail below, it should be noted that, as described in this document, many inventive concepts are provided that can be incorporated into a wide variety of contexts. The embodiments discussed here are merely representative and do not limit the scope of the invention. It will be equally obvious to a person skilled in the art that all technical features defined in relation to a process can be transposed, individually or in combination, to a device, and conversely, all technical features relating to a device can be transposed, individually or in combination, to a process.

[0039] The terms “compreender” (and any grammatical variation thereof, such as “compreende” and “compreendendo”), “ter” (and any grammatical variation thereof, such as “tem” and “tendo”), “conter” (and Petition 870260049400, dated 05 / 25 / 2026, p. 13 / 133 8 / 53 any grammatical variation thereof, such as “contains” and “containing”) and “include” (and any grammatical variation thereof, such as “includes” and “including”) are indefinite linking verbs. They are used to specify the presence of indicated features, integers, steps, or components, or groups thereof, but do not exclude the presence or addition of one or more other features, integers, steps, or components, or groups thereof. As a result, a method, or a step in a method, that “comprises”, “has”, “contains”, or “includes” one or more steps or elements possesses those one or more steps or elements, but is not limited to possessing only those one or more steps or elements.

[0040] An ophthalmic lens according to the present disclosure may be a spectacle lens, a contact lens, an instrument lens, or any other type of lens used in ophthalmology or optics. For example, it may be a corrective lens having power of the sphere, cylinder, axis, addition, and / or prism type. The lens power may be defined as the inverse of the lens's focal length. The lens may be a single-vision lens having constant power, or it may be a progressive lens having variable power, or it may be a bifocal or trifocal lens.

[0041] If the lens is a single-vision lens, the lens power is the power at the optical center of the lens, that is, the point on the lens where light is not deflected when passing through the lens.

[0042] If the lens is a progressive lens, the focal length varies across the entire lens, including areas of distance vision, intermediate vision, and near vision. The power of the progressive lens comprises the power at a distance vision point, the power at a near vision point, and the power distribution across the lens.

[0043] If the lens is a bifocal (respectively trifocal) lens, the focal length varies between the two (respectively three) areas. Petition 870260049400, dated 05 / 25 / 2026, p. 14 / 133 9 / 53 different from the lens. The power of a bifocal or trifocal lens comprises the power in each of these areas.

[0044] As shown in Figure 1, in a particular embodiment, a method according to the revelation, for recovering at least one optical parameter of an ophthalmic lens, comprises a first step 10 of obtaining an image of a first and a second pattern using an image capture device located in a first position.

[0045] As a non-limiting example, at least one optical parameter may be the optical center or any of the optical parameters that define the lens power, i.e., any of the optical parameters contained in the lens prescription, namely, sphere and / or cylinder and / or axis and / or addition and / or prism.

[0046] Using an image capture device and a source pattern comprising a first and a second pattern, the general principle of the method according to the revelation consists in knowing the source pattern and the distortion of the source pattern seen through the lens and analyzing the data relating to the source pattern and its distortion to recover at least one optical parameter of the lens.

[0047] Implementing this principle involves at least one processor, which may be contained in a fixed and / or mobile device, such as a desktop or laptop computer and / or a smartphone and / or in the cloud.

[0048] The implementation also involves a fixed or mobile device equipped with the aforementioned image capture device.

[0049] By way of non-limiting example, the mobile device may be a smartphone.

[0050] The image capture device can be included in the smartphone, that is, the smartphone can be equipped Petition 870260049400, dated 05 / 25 / 2026, page 15 / 133 10 / 53 with a camera. As a variant, the image capture device may be a separate image capture device.

[0051] In addition to at least one processor, mobile device and image capture device, various combinations or configurations of elements are possible, provided that at least one of the elements is capable of displaying or exhibiting or reflecting patterns and at least one of the elements is capable of capturing images.

[0052] By way of non-limiting example, the mobile device may be combined with a reflective device, such as a mirror, or with a non-portable or fixed or portable computer. It should be noted that, in the present disclosure, the portable computer may be a lap computer, or a tablet or any other type of portable computer.

[0053] As for the font pattern, it can be a two-dimensional (2D) or three-dimensional (3D) font pattern, available as an object, printed on a piece of paper or displayed on a screen.

[0054] By way of non-limiting example, the source pattern may be a 3D gauge whose dimensions are known, or a credit card, or a target printed on A4 paper, or a target whose size is known in pixels, displayed on the screen of a computer, smartphone or tablet.

[0055] By way of non-limiting example, the image capture device may be a 2D camera or a 3D scanning device, with or without other sensors embedded in it, such as a rangefinder and / or a gyroscope: it may be a 2D camera from a smartphone or tablet, or a combination of a high-definition 2D camera with a 3D sensor, such as, for example, one or more TOF (Time of Flight) sensors (i.e., sensors that emit light towards the source pattern which reflects it, the distance between the source pattern and the TOF sensor being deduced from the light travel time) or structured light sensors (i.e., sensors that project fringes or other patterns). Petition 870260049400, dated 05 / 25 / 2026, page 16 / 133 11 / 53 known towards the source pattern whose deformation is analyzed by the sensor). The image capture device may or may not include additional hardware, such as a support.

[0056] The image capture device is located in a first position and captures an image of the first and second patterns.

[0057] That is, the method according to the revelation is based on the use of the source pattern, one part of which is seen by the image capture device through the lens (the first part) and another part of which is seen directly by the image capture device (the second part).

[0058] During the following steps 12 and 14, from the image of the first and second patterns obtained in step 10, a first set of data is obtained from the first pattern seen through the lens by the image capture device (step 12) and a second set of data is obtained from the second pattern seen outside the lens by the image capture device (step 14). Step 12 can be performed before, after, or at the same time as step 14.

[0059] So, during step 16, using the first and second data and taking into account, in detail below, the relative positions, that is, the positions in relation to each other, of the image capture device, the lens and the first and second standards, at least one optical parameter is recovered, also detailed below.

[0060] Depending on the selected mode, relative positions of the image capture device, the lens, and the first and second standards can be obtained, partially or completely, that is, positions, relative to each other, of the image capture device, the lens, and the first and second standards, using the second data set. Petition 870260049400, dated 05 / 25 / 2026, page 17 / 133 12 / 53

[0061] In a particular embodiment, an approximate estimate and a refined estimate of at least one optical parameter can be obtained, namely: - a rough estimate of at least one parameter can be obtained using the first set of data and the relative positions of the image capture device, the lens, and the first and second standards, that is, the positions, relative to each other, of the image capture device, the lens, and the first and second standards; and - A refined estimate of at least one optical parameter can be obtained by: - Use the first set of data and relative positions of the image capture device, the lens, and the first and second standards, that is, positions, one in relation to the other, of the image capture device, the lens, and the first and second standards; and - Apply an optimization technique based on minimizing a cost function, as described in more detail later, where a value for the cost function is determined using ray tracing.

[0062] In a particular embodiment where the lens 30 is mounted in a frame 140, the method may further comprise detecting a position, i.e. location and orientation, of the frame and deducing from it the axis of the lens cylinder in the frame coordinate system, rather than in the image capture device coordinate system.

[0063] There are several ways to detect the frame.

[0064] In a particular embodiment, frame detection may comprise obtaining a frame model from a database where a plurality of frame types have been stored and defined. Petition 870260049400, dated 05 / 25 / 2026, p. 18 / 133 13 / 53

[0065] As a variant, the frame detection process may involve obtaining information about the frame and then finding the frame in the image of the first and second patterns.

[0066] For example, the frame detection process may comprise obtaining information about the frame using the image capture device 26 located in a second position to take a picture of the frame. For this purpose, the frame may be placed on a flat surface such as a table, with at least one lens in contact with the flat surface. In this case, frame detection will also comprise obtaining a model of the frame image taken as described in the present disclosure with reference to Figure 16.

[0067] If the source pattern (i.e., the first and second patterns 20) is not known (because, for example, the source pattern is not displayed on the smartphone screen), an image of the first and second patterns 20 in front of the reflection device 28 can be taken with the image capture device 26 located at a third position, in order to obtain an image of the first and second patterns 20, so that the source pattern is known in the coordinate system of the image capture device 26.

[0068] In a particular embodiment, an image of the first and second patterns together with a reference object (e.g., a credit card) can be captured.

[0069] As a variant, an image of the first and second patterns can be captured with a camera with known focal length and pixel size, in addition to camera pattern distance information provided by a sensor (e.g., rangefinder).

[0070] As another variant, an image of the first and second patterns can be captured with a 3D camera.

[0071] If the font pattern is already known in pixels and the resolution Petition 870260049400, dated 05 / 25 / 2026, page 19 / 133 14 / 53 and the dimensions of the smartphone 24 are known, the font pattern is already known in the coordinate system of the image capture device 26, so it is not necessary to take a picture of the font pattern with the image capture device 26 located in the first position or the third position.

[0072] Obtaining (i) the first and second data sets, (ii) the relative positions of the image capture device, the lens, and the first and second patterns, and (iii) the approximate and refined estimates of at least one optical parameter, will be described below in detail in a particular embodiment of the method, in which, in step 10, (a) obtaining the image of the first pattern comprises reflecting, by a reflection device, the first pattern before it is viewed by the image capture device through the lens and (b) obtaining the image of the second pattern comprises reflecting, by the reflection device, the second pattern before it is viewed by the image capture device outside the lens. Namely, it can be assumed that the viewing step by the image capture device is performed after the reflection step by the reflection device.

[0073] In this specific embodiment, as shown in Figure 2, the first and second patterns 20 are part of a 2D pattern which is, for example, displayed on the screen 22 of a smartphone 24. By way of non-limiting example, the image capture device 26 is the front camera of the smartphone.

[0074] The patterns 20 can be seen by the image capture device 26 thanks to a reflection device 28 which, by way of non-limiting example, is a mirror. The lens 30 (or a frame, if any, in which the lens 30 is mounted) is located between the image capture device 26 and the reflection device 28 so that the front surface of the lens 30 is tangent to the reflection device 28 at a point of contact P. The first and second Petition 870260049400, dated 05 / 25 / 2026, page 20 / 133 15 / 53 patterns 20 and the image capture device 26 are oriented towards the lens 30.

[0075] For greater stability, the mirror can be placed on the wall, in a vertical position, or on a table, in a horizontal position.

[0076] In a particular embodiment where the 30 lens is mounted in a frame, the general principle of development mentioned above can be implemented as follows: - the frame can be known, i.e., frame learning can be implemented by obtaining an image of the frame, with the image capture device 26 taking a picture of the frame, for example, with the rear camera of the smartphone 24, if the smartphone 24 is equipped with it, with the frame placed, for example, on a table; - the distortion of the source pattern seen by the image capture device 26 through the lens 30 can be determined by obtaining an image of the source pattern, with the image capture device 26 taking a picture of the frame while a user is holding the frame in contact with the reflection device 28; and - if the font pattern is unknown, it can be known by obtaining an image of the font pattern with the image capture device 26 by taking a picture of the font pattern displayed on the screen 22 of the smartphone 24 and seen by the image capture device 26 by means of the reflection device 28.

[0077] In this mode, the coordinate system of the source pattern is restricted to the coordinate system of the smartphone camera 24, as they are physically linked to each other. The coordinate system of the frame is partially known, because the frame is kept in contact with the reflection device 28.

[0078] Obtaining the first set of data, the second Petition 870260049400, dated 05 / 25 / 2026, page 21 / 133 16 / 53 dataset and the retrieval of at least one optical parameter involves calculations, which can be performed using an algorithm fully embedded in the smartphone or running on a remote computer, or through an application (API) available in the cloud, or with a combination of elements embedded in the smartphone and elements available on a remote computer and / or in the cloud. This combination allows for optimizing the volume of data transferred and the computation time required.

[0079] The calculations mentioned above are detailed below in the particular embodiment of Figure 2.

[0080] The calculations can be done in two parts.

[0081] The first part of the calculations is based on the source pattern points outside the lens 30. It is related to the second set of data mentioned earlier.

[0082] In summary, in the first part of the calculations, points outside the lens are used to determine the relative positions (including orientation and location) between the mirror and the camera, i.e., the positions of the mirror and the camera relative to each other, by using ray tracing and running an optimization algorithm.

[0083] The first part of the calculations is described in more detail below.

[0084] Next, a coordinate system R is a system that uniquely determines the position of points or other geometric elements in a Euclidean space by assigning a set of coordinates to each point. As a non-limiting example, the coordinate set used below is (x, y, z), referring to three axes X, Y, Z that are orthogonal to each other. Qobject,R is an object point expressed in the coordinate system R.

[0085] Figure 3 shows the mirror and the Mirror.

[0086] Since the front surface of lens 30 is tangent to the mirror, Petition 870260049400, dated 05 / 25 / 2026, p. 22 / 133 17 / 53 It is assumed that the coordinate system Rlens of lens 30 is the same as the coordinate system Mirror of the mirror: Rlens = Mirror. The coordinate system of the smartphone 24 (also referred to as the device) is indicated as Rdevice and the coordinate system of the image capture device 26 (also referred to as the camera, by way of non-limiting example) is indicated Rcamera. Since the source pattern (displayed on the device screen) and the image capture device 26 are physically in the same device, which is the smartphone 24, the transformation between Rdevice and Rcamera is known.

[0087] The transformation between Mirror and Device is calculated. This completely determines the transformation between Rcamera and Rlens: Rcamera->lens = Rcamera->device * Rdevice->mirror * Rmirror->lens, where Rmirror->lens is the identity.

[0088] It is assumed that the physical dimensions of the screen 22 are known, so the same notation is used for object points that can be obtained in pixel units and for reference to the corresponding 3D points in the Rdevice.

[0089] Images of Qobject points are invariant with respect to rotations about the mirror's Z-axis and translations along the mirror's X and Y axes. Therefore, only rotations about the mirror's X and Y axes and translations along the mirror's Z-axis can be recovered using the reflected points of the source pattern.

[0090] Let's define the following coordinate system change from the device to the mirror, denoted Kdevice->mirror: Kdispositivo->espelho(θχ,θy,tz) = {PRdispositivo->PRespelho = Py(θy)Px(θχ) PRdispositivo + Tz(tz)}, where: Θχ, θy, and Tz are the parameters for changing the coordinate system from the device to the mirror. PRdevice is a 3D point expressed in the system of Petition 870260049400, dated 05 / 25 / 2026, page 23 / 133 18 / 53 coordinates of the device, PRespeiho is a 3D point expressed in the mirror's coordinate system. Py, px, and Tz are respectively rotation matrices around the Y and X axes and a transition vector along the Z axis.

[0091] The Reflect function: (QMirror, CRepelh) -> ZMirror, calculates the image of an object point QRepelh in the mirror, as seen by the camera point CRepelh, after being reflected in the mirror. The result ZMirror, as well as the object point QRepelh and the camera point CRepelh, are expressed in the Mirror coordinate system of the mirror.

[0092] This is illustrated by Figure 4, where C is a small-diameter hole in the camera, Q is a point in the source pattern displayed on screen 22, Q' is the image point of Q through the mirror, I is the intersection between the mirror plane and the ray connecting Q' and C. Point I is outside the lens. The mirror plane and the camera plane are not necessarily parallel.

[0093] Let's define ZRcamera(QRdevice,θχ,θy,tz) as the image point of the object point Q expressed in the device's Rdevice coordinate system, as seen by the camera after reflection in the mirror. The rotation and translation parameters show the image's dependence on the device's orientation relative to the mirror. The resulting ZRcamera is expressed in the camera's Rcamera coordinate system. The following formula makes explicit how the image point of ZRcamera is calculated: ZRcamera(QRdevice,θχ,θy,tz) (Kcamera->device o Kdispositivo->espelho)1o Reflect(Kdevice->mirrorQRdevice,Kdevice->mirrorCRdevice) where the 'o' sign is the operator performing a composition of functions. In other words, the following operations are performed: to cross the QR object point and the camera point Petition 870260049400, dated 05 / 25 / 2026, page 24 / 133 19 / 53 CR device in the Mirror coordinate system, using the Kdevice->mirror function; Use the Reflect function to calculate the image point in the Mirror coordinate system; to transpose the image into the camera's coordinate system, which requires a Kespelho->camera function; Since the functions Kcamera->device and Kdevice->mirror are known, the function Kmirror->camera can be recovered by combining them and then using the inverse function: Kespelho->câmera = (Kespelho->dispositivo o Kdispositivo->câmera) = (Kcâmera->dispositivo o Kdispositivo->espelho)-1

[0094] The 3D ZR camera point can then be projected onto the 2D camera plane, in pixel units, using an appropriate camera model. By way of non-limiting example, a well-known pinhole camera model that takes radial and tangential distortions into account can be used. Projecting a 3D image point onto the camera plane can use some camera parameters, such as intrinsic parameters fx, fy, Cx, cy and distortion parameters (see below). Such parameters can be obtained in many different ways, such as camera calibration, as detailed below by way of non-limiting example.

[0095] The camera model is defined as follows for an object point (x,y,z) expressed in the camera's R-camera coordinate system: Petition 870260049400, dated 05 / 25 / 2026, page 25 / 133 20 / 53 ( , xx = z / yy, =z .r= Jx'2+ y'2x = x'(1 + k1r2+ k2r4+ k3r6>) + 2p1x'y' + p2(r2+ 2x'2) y'' = y'(1 + k1r2+ k2r4+ k3r6) + 2p2x'y' + p1(r2+ 2y'2) ^ Project(x,y,z')= (u,v) = (fxx + cx,fyy” + Cy) fx and fy are the focal lengths of the camera, in pixel units; assuming that (Ox, Oy, Oz) is the camera coordinate system, cx and cy are the pixel coordinates in the sensor coordinate system of the principal point, which is the intersection of the Oz axis with the image plane; by way of a non-limiting example, in the pinhole model mentioned above, Oz is the axis orthogonal to the camera sensor; k1, k2 and k3 are radial distortion coefficients; Pi and p2 are tangential distortion coefficients;

[0096] Project is a function that projects the 3D object point (x,y,z) expressed in the camera's coordinate system onto the camera sensor. The result is a 2D object point in pixel units.

[0097] This model requires the camera to be precisely calibrated so that fx, fy, cx, cy, k1, k2, and k3 are precisely known.

[0098] However, a camera model different from that described above (more complex or simpler) may be used, depending on the degree of precision required for a particular use of the method according to the present disclosure.

[0099] The orientation of the device relative to the mirror, denoted, can then be estimated by minimizing the following cost function Jorientation: Petition 870260049400, dated 05 / 25 / 2026, page 26 / 133 21 / 53 JorieMa^x.Mz) ·( Project(ZRcamera(Qobject Rdevice, θχ, θγ, tz)) Qimage Project (ZRcamera(Qobject,Rdevice, Χχ> @y> ^))Qimagem where m is an integer greater than or equal to 1. (ex.e^.t-) = argmln(l)xj3y^z)lorieMafão(ex, Oy, D)

[00100] The equation above can be solved using any nonlinear least squares algorithm, such as the Gauss-Newton or Levenberg-Marquardt algorithm.

[00101] In summary, ray tracing and optimization make it possible to know the relative positions of the mirror, frame, and lens in the camera's coordinate system, that is, the positions of the mirror, frame, and lens in relation to each other in the camera's coordinate system.

[00102] The second part of the calculations is based on the points of the source pattern seen by the image capture device 26 through the lens 30.

[00103] In summary, the second part of the calculations uses the points inside the lens and the relative positions (including orientation and distance) between the mirror and the camera, which were determined in the first part of the calculations, executing an optimization algorithm and using ray tracing, to:

[00104] determine an initial lens, which, by way of non-limiting example, may be a plano lens or a random spherical lens, or which may be an estimated geometry based on a rough estimate of the lens magnification; and

[00105] optimize the initial lens to solve a least squares problem, including minimizing a cost function that is calculated using ray tracing on points of the first pattern, where the position of the points in the first pattern is known and its image is Petition 870260049400, dated 05 / 25 / 2026, page 27 / 133 22 / 53 obtained by ray tracing and compared with the points of the first pattern.

[00106] The second part of the calculations is described in more detail below.

[00107] In a particular embodiment, in order to estimate the power of lens 30, the observed magnification is used to calculate the linear magnification, as follows: linear magnification — 1 Power =------------------linear magnification · t* where t* is the distance from the device to the mirror (which is approximately equal to the distance from the device to lens 30), obtained previously.

[00108] To obtain the linear magnification, the area magnification is first calculated by forming the convex hull of the refracted and reflected object points, denoted respectively Pob]eto and Qob]eto. The corresponding image points are indicated respectively Pimageme Qimagem. Area(Qo0]o]o)A^aÇP^gemm) area enlargement =-----, .--, r Area^PoProject) Area(Qimagem )

[00109] Linear magnification is taken as the square root of the area magnification, which then gives an estimate of the lens power 30.

[00110] This is a rough estimate because it does not take astigmatism into account and the paraxial approximation is implied in the lens power formula, meaning that the rays are assumed to be making a small angle with respect to the optical axis and entering the lens close to the optical center.

[00111] In the following steps, an estimated physical lens is calculated, which will serve as a starting point for the optimization algorithm.

[00112] Using the estimated power, the lens material most Petition 870260049400, dated 05 / 25 / 2026, page 28 / 133 23 / 53 is likely selected. A non-limiting example of classification with respect to the refractive index (hereinafter Index) of the material is given below: If 0 < |Power| < 2, Index = 1.50 If 2 < |Power| < 4, Index = 1.60 If 4^ |Power| < 6, Index = 1.67 If 6 ^ |Power|, Index = 1.74

[00113] Using the estimated power and lens material, a spherical front surface Sfront is chosen, based on a balance between aesthetics and optical performance. This process is called base curve selection and is specific to each lens manufacturer. However, it is considered that the selected front surface will not vary much between manufacturers for a given prescription and a given material.

[00114] In this step, a central thickness for the lens is also selected and is indicated as e.

[00115] Next, a rear spherical surface is calculated to match the estimated power. This can be done using a thin lens model: Index — 1 frontRayRear . SFrontai· Frontal Radius RearRadius = Power — Sentai where Index is the refractive index and FrontRadius and RearRadius are respectively the radii of the front and rear spherical surfaces.

[00116] A least squares optimization based on ray tracing is performed to find a physical lens (hereinafter IdealLens) that produces the same image Pimage of the set of points Pobject as the observed one, i.e., Image(IdealLens,Pobject) = Pimage. Petition 870260049400, dated 05 / 25 / 2026, page 29 / 133 24 / 53

[00117] As mentioned earlier, the front surface of the lens is assumed to be tangent to the mirror at the point of contact.

[00118] For an object point Pobject,Mirror, let's define the function Propagate(Pobject,Mirror,CRemirror,Lens) -> Wreflector,Mirror, which calculates the image of the object point Pobject,Mirror seen by the camera at point CRemirror, after being refracted by lens 30 and reflected in the mirror, then refracted by lens 30 once more, as shown in the Figure 5. The result WRespelho is expressed in the Mirror's Mirror coordinate system. This radius is calculated using a simple Newton's scheme. The image point WRespelho is then the intersection of the output ray with the back surface of the lens.

[00119] At this point, the orientation and distance of the device (i.e., the smartphone 24) from the mirror are known, thanks to the first part of the calculation described earlier.

[00120] Using the same notation as before for the transformation from the device's R-device coordinate system to the mirror's Re-mirror coordinate system, we have Kdevice->mirror(tx,ty) = Kdispositivo->espelho(θχ ,θy ,tz ) + Tx(tx) + Ty(ty).

[00121] The previously estimated physical lens is used as the initial lens, which can then be optimized.

[00122] That is, a toroidal back surface will replace the previously estimated spherical back surface of the physical lens, with both torus radii equal to the sphere radius at the start of the optimization process. The torus radii of the lens back surface are indicated by r1 and r2, and the torus axis of the lens back surface is indicated as the.

[00123] Given an object point Pobject,Rdevice expressed in the device's Rdevice coordinate system, WRcamera is its image point seen through lens 30, expressed in the camera's Rcamera coordinate system: Petition 870260049400, dated 05 / 25 / 2026, page 30 / 133 25 / 53 CRcamera(Pobjeto,Rdispositivo,tx,ty,r1,r2,a) — (Kcamera->dispositivo O Kdispositivo->espelho)1 Propagate(Kdevice->mirrorP object,Rdevice,Kdevice->mirrorCRdevice,lens)

[00124] The translation parameters tx and Ty, which were left undetermined in the preceding steps, are involved here in the device to mirror the coordinate system transformation. The radius and axis parameters are involved in defining the lens.

[00125] Finally, the cost function that defines the least squares problem, which must be minimized to reconstruct a lens that produces the same image as the one observed, is defined as follows: Jlente(tx, ty>r1,r2,o)|2Projeto (WRcâmera(p1bjeto,Rdispositivo,Χχ>ty,r1,r2, ή)- Pimagem Project (WRcamera(P;jbjeto,Rdispositivo, Xx, yyir^ 72, a))-^agem where n is an integer greater than or equal to 1. (tx,ty,ri,r2,O) =or9^in(Lx,Ly,r1,r2,a)Jlens(tx,ty,r1,r2,o)Lenteldeal—Lente(ri*,r2*,a*)

[00126] The optimization procedure above can be applied to other configurations, provided that the coordinate system changes between the camera, the source pattern, and the lens are known. Of course, if no reflection device is involved and the rays from the source pattern hit the camera directly, the propagation function would need to be adapted, removing the reflection.

[00127] The ideal lens is calculated using the back vertex power formula on both meridians of the Straseira,1 and Straseira,2 torus of the back surface of the lens: Index — 1 $ rear,1 = ~*r1 Petition 870260049400, dated 05 / 25 / 2026, page 31 / 133 26 / 53 Index — 1 $rear,2 = *r2

[00128] Both meridians of powers Pi and P2 are then obtained as follows: p _r. ^frontal ' 1 = ^traseira,1 + c .p0frontaleÍndice p _ r . ^frontal '2 = ^traseira,2 + ç .p0frontaleÍndice where e is the thickness of the center.

[00129] It is assumed that Pi < P2 (if this is not the case, these values ​​are swapped).

[00130] The value of the cylinder is P2 - Pi in the positive cylinder convention.

[00131] The prescription axis is the torus axis a*, corrected using the rotation parameter θζ, which is the angle between the X axis in the camera's R-camera coordinate system and the X axis in the mirror's Re-mirror coordinate system, and which is obtained using the frame detected in the image.

[00132] In summary, the method according to the revelation: - takes into account the relative positions of the mirror, frame and lens calculated in the first part of the calculations; - calculates the lens in the camera's R-camera coordinate system, first as a rough estimate based on magnification and, secondly, as a refined estimate based on ray tracing and optimization; and - Corrects the cylinder axis orientation.

[00133] At the end of such calculations, the lens power is obtained in the frame's coordinate system.

[00134] It should be noted that it is not necessary to detect the frame to separate the points that are inside the lens and the points that are outside the lens. However, as frame detection can be used in Petition 870260049400, dated 05 / 25 / 2026, p. 32 / 133 27 / 53 a specific mode for determining the axis of the lens cylinder if the lens is a single vision lens, frame detection can also be used in this specific mode to ensure the separation of points inside and outside the lens.

[00135] As described above, the method according to the revelation is based on the use of a source pattern, one part of which is seen directly by the image capture device and another part of which is seen by the image capture device through the lens. The identification of the source pattern is detailed below.

[00136] A feature matching algorithm can be run to group object points in a known source pattern with the corresponding image points in the photo taken by the image capture device. The frame outline can be used as a mask to separate the points seen through the lens (Pobject, Pimage) from those seen only in the mirror (Qobject, Qimage).

[00137] Therefore, two sets of coincident points are obtained. {Pobject = (Plbject. -.P^). Pimage = (Pimage.-.Pimage)} {Qobject (Qobject. image = (01,...,0™ B(Qimage,.Qimage)} where neither are integers greater than or equal to 1

[00138] By way of non-limiting example, the first and second patterns 20 may be two QR codes displayed on the screen 22 of the smartphone 24. For example, the lower half of the screen 22 may display one of the two QR codes and the upper half of the screen 22 may display the same QR code with a different size (e.g., larger for negative power and smaller for positive power) and possibly other modifications. Then, the lower QR code may be used to calculate the camera position relative to the lens and the upper QR code may be used to calculate the lens power.

[00139] How several key points can be found in a Petition 870260049400, dated 05 / 25 / 2026, page 33 / 133 28 / 53 QR code, i.e., notable points found in the pattern with a feature matching algorithm, key points can be detected in the object (i.e., the pattern shown on screen 22) and in the image (i.e., the distorted pattern in the photo taken by the image capture device 26). The feature matching algorithm then performs a match between the key points of the object and the image. It is then known which key point in the object corresponds to which key point in the image and their respective coordinates are also known.

[00140] As another example, the first and second patterns 20 may comprise concentric black rings and white rings, as shown in Figure 6.

[00141] By way of non-limiting example, such a font pattern can be used for both the bottom and top parts of screen 22, i.e., for both the first pattern and the second pattern. As another example, it can be used only for the top part of screen 22 and a QR code can be used for the bottom part of screen 22.

[00142] Using an image processing algorithm, the four circles of this font pattern (two black circles and two white circles) can be extracted and each circle can be discretized into a predefined number of points.

[00143] In the photo taken by image capture device 26, representing the distorted pattern, an ellipse is fitted into each circle.

[00144] To find the ellipses, a Region of Interest (ROI) can be defined in the image to restrict the search area. The image can be converted from RGB to grayscale (as shown in Figure 7), then to binary (as shown in Figure 8) using a filtering method, in order to obtain the ellipses (as shown in white in Figure 9).

[00145] Next, the projection of each discretized point is Petition 870260049400, dated 05 / 25 / 2026, page 34 / 133 29 / 53 calculated from the object's circles with ray tracing through the simulated lens in the 2D plane of the ellipses, in order to obtain the so-called projected points. An algorithm is then used to find the position of the nearest point, in the corresponding ellipse, to each projected point (as shown in Figure 10).

[00146] Advantageously, only the two largest ellipses (shown on the left of Figure 10) are used. As Figure 10 shows the beginning of the optimization, the projected points are a circle (shown on the right of Figure 10). The points of the largest ellipse are the closest to each of the points of the larger circle, and the points of the smallest ellipse are the closest to each of the points of the smaller circle.

[00147] The gap in each dimension (xey) between each point and its nearest point on the ellipse is used for optimization. The gap in each dimension between the center of each ellipse and the centroid of the corresponding projected points is also used, for example, with a weight equal to the number of projected points. This allows the centroid of the projected points to converge at the same position as the center of the ellipses, as shown in Figure 11, which is the third iteration (out of a total of twenty-one iterations) of the optimization process.

[00148] Figure 12 shows the last iteration, where the projected points correspond to the ellipses, so the optimization is stopped and the simulated lens is used to calculate the lens power.

[00149] As yet another example, shown in Figure 13, the first and second patterns 20 may comprise a grid comprising at least one colored rectangle 130 and at least one colored rectangular block 132 located within the at least one colored rectangle 130 and containing at least one polka dot pattern 134, the color of the polka dot pattern 134 differing from the color of the block 132.

[00150] By way of non-limiting example, the grid shown in Petition 870260049400, dated 05 / 25 / 2026, page 35 / 133 30 / 53 Figure 13 comprises two coaxial colored rectangles 130, for example red and blue, surrounding its edges. The widths of the rectangles 130 are optimized so that the rectangles can be detected when viewed at a predetermined distance from the grid. The larger the rectangles 130, the farther away they can be detected. The rectangles 130 will be used by the method of the present disclosure to determine the position of the smartphone 24 in 3D space.

[00151] By way of non-limiting example, the grid shown in Figure 13 also comprises eight colored rectangular blocks 132 of different colors, each containing three-by-three dot patterns 134 of different colors. The colors of the dot patterns 134 are chosen so as to be different from the color of the block 132 to which they belong. Optionally, at the bottom of the grid, the colors used for the dot patterns 134 and the blocks 132 are reported. This makes it possible to identify colors if the color reproduction is altered by the smartphone 24, depending on the lighting conditions and the type of smartphone 24 used. Advantageously, the grid resolution is adapted to the resolution of the smartphone 24.

[00152] A portion of the colored dot patterns 134 can be seen through the lens 30 (this is the first pattern) and is used to determine the lens power.A portion of at least one colored rectangle 130 can be seen outside the lens 30 (this is the second pattern) and this portion of at least one colored rectangle 130 is used to determine the relative positions between the smartphone 24 and the reflective device 28, i.e., the positions of the smartphone 24 and the reflective device 28 relative to each other.

[00153] According to the method of the present disclosure, the correspondence between the points on the grid and the points on the image taken by the image capture device 26 must be determined. The Petition 870260049400, dated 05 / 25 / 2026, page 36 / 133 31 / 53 points seen through lens 30 may undergo two transformations: a T1 transformation linked to the fact that the smartphone 24 may not be parallel to the reflecting device 28, and an additional T2 transformation for the points seen by the image capture device 26 through lens 30.

[00154] To determine T1, the two rectangles 130 are used.

[00155] Once T1 is applied, there are two different processing phases: - an identification phase, in which, using the colors of the dot patterns 134 and the colors of the blocks 132, the grid points involved in the image obtained by the image capture device 26 are identified; and - a classification phase (points inside or outside the lens), in which it is determined whether the detected points are inside or outside the lens 30.

[00156] As a preferred possibility, suitable points among those visible within lens 30 can be automatically selected, for example, using, as a source pattern, a specific grid to detect the optical center of lens 30 and selecting points close to the optical center for calculations. That is, the optical center of the lens can be determined based on the image of the first pattern. At least four points that are not aligned with each other in the first pattern are needed to determine the optical center. Such points can be obtained from a wide variety of patterns, such as a square, a QR code, a grid, etc. Several non-limiting examples of patterns are described in the present disclosure, for example, the grid described with reference to Figure 13.

[00157] In modes where a mobile device such as a smartphone is used, to better ensure that a portion of the grid will be visible within the lens, before displaying the grid or any other Petition 870260049400, dated 05 / 25 / 2026, page 37 / 133 32 / 53 pattern as described previously, the portrait mode video with the front camera can be displayed on the smartphone screen 24 and a third pattern (such as a blue square, a logo, or any other pattern deemed appropriate) can be displayed at the top of the smartphone screen 24 over the portrait mode video with the front camera. As a preference, the position of the third pattern displayed on the screen is the same as the position of the first pattern displayed on the smartphone screen 24.

[00158] In a particular embodiment, shown in Figure 20, a first image of the third pattern 50 captured by the image capture device 26 is a colored square, for example an empty blue square. An image comprising a plurality of images of the third pattern with decreasing size is captured by the image capture device 26 in portrait mode with a front camera (also known as mise en abyme effect), among which the first image of the third pattern 50 is the largest without a lens.

[00159] The size and color of the third pattern are selected so that the user is not too disturbed by the patterns displayed on the smartphone screen 24 in portrait mode video with front camera, while the third patterns displayed can be correctly detected by image processing.

[00160] As a preferred possibility, a fourth pattern (such as a flashing red filled square or any other pattern deemed appropriate) may also be displayed on the smartphone screen 24 in portrait mode video with the front camera so as to overlay a second image of the third pattern that is captured by the image capture device 26 after reflection by the reflection device 28. As shown in Figure 20, an image of the fourth pattern 60 on the reflection device is superimposed on the second image of the empty blue square, so that the second image of Petition 870260049400, dated 05 / 25 / 2026, page 38 / 133 33 / 53 empty blue square in reflection device 28 is hidden. That is, the second image of the empty blue square can be detected by image processing and then hidden by displaying a flashing filled red square over it. The fourth pattern 60 is then used to guide the user to look at the correct pattern to position the smartphone correctly, for example, to position the image of the fourth pattern within the image of the frame. By way of non-limiting example, the image capture device 26 is the smartphone's front camera and the smartphone screen displays the direct image taken by the front camera.

[00161] By way of non-limiting example, shown in Figure 20, an image of a fifth pattern 70, such as a rectangle, a QR code or any other pattern deemed appropriate, is captured by the image capture device 26. The fifth pattern is used to calculate the distance from the smartphone to the reflection device 28 using the algorithms described above.

[00162] In a variant of the grid in Figure 13, the dot patterns may be present within the third or fourth pattern used to better ensure the aforementioned approximate positioning. This makes it possible to combine both approximate positioning control and optical center detection.

[00163] In addition, several patterns can be displayed successively to guide the user and obtain the images needed for the calculations. This successive display can be automatic or manual. For example, the user can be guided as follows: - place the frame on the mirror, - Place the smartphone close to the lens, - Move the smartphone back to a certain distance, for example, about 30 cm from the mirror, Petition 870260049400, dated 05 / 25 / 2026, page 39 / 133 34 / 53 using the third or fourth pattern mentioned above (used to better control the approximate positioning mentioned above) and using portrait mode with the front camera to move the smartphone correctly, - Take the photo with the smartphone camera 24.

[00164] As a variant, distance control can be done using the algorithms described above. Then, the user can be prompted to stop moving backward when the expected distance is reached and the photo(s) can be taken using the algorithms described above.

[00165] So, the algorithm would detect that some points (of the first pattern mentioned above) are inside lens 30, analyzing the distance between the patterns of dots, uses these points to detect the optical center of lens 30 and selects the points that are close to the optical center.

[00166] Immediately after taking a photo of the font pattern, the user may be prompted to take another photo while the top part of the font pattern is replaced with a white image (or any other homogeneous background) to see the frame correctly and facilitate frame detection. The bottom part of the grid mentioned above would be maintained, so that it can be verified whether the smartphone 24 has not moved between the two successive images or whether the smartphone's displacement can be taken into account in the calculations.

[00167] By way of a non-limiting example, once the smartphone is correctly positioned in front of the frame / mirror, three different patterns can be used successively, in an order depending on the computation time of the algorithms: for example, the grid in Figure 13 to find the optical center of the lens, a white screen to detect the frame, and the circular pattern in Figure 6 to recover the lens power. Petition 870260049400, dated 05 / 25 / 2026, page 40 / 133 35 / 53

[00168] For the approximate positioning mentioned above, the use of certain types of mobile devices can be particularly advantageous. For example, using a tablet instead of a smartphone 24 can be more advantageous in this respect, as the probability of a part of the grid being seen within the lens is greater than when using a smartphone, since a tablet is generally larger than a smartphone.

[00169] More generally, Figure 14 shows an embodiment where the lens 30 is mounted in a frame 140 (only one lens 30 is shown and therefore only half of the frame 140 is shown) and where any type of first pattern 201 is seen by the image capture device 26 through the lens 30 and any type of second pattern 202 is seen directly by the image capture device 26, i.e., outside the lens 30.

[00170] Even more generally, the first and second patterns may form a single font pattern that is not divided into two patterns, or the first and second patterns may be two patterns that are identical or of two different shapes and / or colors, or each of the first and second patterns may be displayed individually.

[00171] Figures 17 and 18 show other non-limiting examples of patterns that can be used to retrieve optical parameters such as lens power and optical center. As a non-limiting example, the pattern in Figure 17 has two concentric circles at the top and two concentric squares at the bottom, and the pattern in Figure 18 has two concentric squares at the top and a QR code at the bottom. However, various combinations of top and bottom parts of such patterns can be used.

[00172] In any of the pattern configurations mentioned above: Petition 870260049400, dated 05 / 25 / 2026, page 41 / 133 36 / 53 - at least a part (or portion) of the pattern (or the second pattern if there are two patterns) that is outside the lens, which is the part of the pattern (or the second pattern if there are two patterns) that is seen directly (i.e., not through the lens) by the camera, is used to determine the relative positions (including orientation and distance) between the mirror and the camera, i.e., the positions of the mirror and the camera relative to each other; and - at least a part (or portion) of the pattern (or the first pattern if there are two patterns) that is inside the lens, which is the part of the pattern (or the first pattern if there are two patterns) that is seen through the lens by the camera, is used to recover the lens power.

[00173] As shown in Figure 15, in a particular embodiment where the lens is mounted in a spectacle frame, a method according to the disclosure, for recovering at least one optical parameter of an ophthalmic lens, comprises: - a first step 8 of obtaining an image of the frame; - steps 10, 12, 14 as described with reference to Figure 1; - Step 16 as described in Figure 1, in which at least one optical parameter is recovered in the camera's coordinate system; - a step 18 of detecting the frame's position in the first and second pattern images; and - a step 19 of recovering at least one optical parameter in the frame coordinate system.

[00174] Figure 16 shows a non-limiting example of the result of step 8 of obtaining an image of the frame. The upper portion of the drawing shows a non-limiting example of a pair of glasses. Petition 870260049400, dated 05 / 25 / 2026, page 42 / 133 37 / 53 comprising a frame and at least one ophthalmic lens 30 and to which the method of Figure 15 can be applied and the lower portion of the drawing shows the image obtained from the frame.

[00175] In the frame learning stage, to facilitate the operation of obtaining an image of the frame for a user, image capture can be guided, for example, by displaying centering and / or alignment marks on the screen 22 of the smartphone 24, so that the positioning of the frame on a table with a preferably homogeneous background is ideal (e.g., frame visible across the entire width of the image, centered and aligned with the horizontal axis). By way of non-limiting example, the aforementioned marks may be red at the beginning and turn green when the predefined conditions are met.

[00176] By way of non-limiting example, if the 24-inch smartphone is equipped as usual with a gyroscope, such gyroscope can be used to alert the user if the 24-inch smartphone is not positioned correctly (e.g., horizontal / parallel to the table).

[00177] The background color can then be detected through a histogram analysis of the colors. The background can then be extracted by a flood fill algorithm (also known as seed fill). Then, the frame image can be binarized and the morphology operators, which are known to each other, can be applied to extract the part of the image corresponding to the frame and its mask, i.e., its outline. Any residual rotation of the image can be corrected by known techniques.

[00178] Using the information about the frame (also referred to as a frame model) obtained in the frame learning stage, the outline of the eyeglass frame can be detected in the photo. Petition 870260049400, dated 05 / 25 / 2026, page 43 / 133 38 / 53 taken with the aid of the reflection device 28 during the frame detection stage: the scale factor to be applied to the model can be calculated based on the distance of the smartphone 24 to the frame. The lens to be searched (left or right) is known. The useful part of the frame can be removed and the photo can be enlarged at the edges. A certain number of orientations of the frame model can be tested to find the best position of the frame by studying, for each angle, the correlation between the frame visible in the image of the first and second patterns 20 and the model obtained during the frame learning phase. If the frame is detected, the best position (location and orientation) of the frame in the image will be selected. The technique described above is also valid when the frame is partially visible in the image of the first and second patterns 20.

[00179] A system according to the disclosure, for implementing a method to recover at least one optical parameter of an ophthalmic lens, comprises means adapted to perform the steps of the method mentioned above.

[00180] In a particular embodiment, the system may comprise a reflective device and a mobile device equipped with the aforementioned image capture device.

[00181] The mobile device may comprise a display unit and the first and second patterns may be two-dimensional patterns displayed on the display unit.

[00182] The mobile device can be a smartphone and the image capture device can be a smartphone front camera, as described above in connection with a specific embodiment of the method, shown in Figure 2.

[00183] As also described with reference to Figure 2, the reflecting device can be a mirror. Petition 870260049400, dated 05 / 25 / 2026, page 44 / 133 39 / 53

[00184] The schematic view of Figure 19 encompasses various embodiments of the method and system according to the present disclosure. In these various embodiments, in addition to at least one processor and an image capture device, the system according to the disclosure comprises a smartphone 24 and a computer 180.

[00185] As will be seen below from the detailed description of these various modalities, the computer 180 can be used to display the first and second patterns 20, while the smartphone 24 can be used to capture images. In other words, in such a configuration, two electronic devices are involved.

[00186] On the other hand, in previously described embodiments of the present disclosure not involving any computer, but only the smartphone 24 and the reflective device 28, the smartphone 24 can be used both to display the first and second patterns 20 and to capture images. In other words, in such a configuration, only one electronic device is involved. Furthermore, in such a configuration, if at least one lens 30 is mounted in a frame, the position of the frame 140 can be at least partially known simply by positioning the frame 140 in contact with the reflective device 28. Thus, obtaining the relative positions of the reflective device 28, the frame 140, if any, and the image-capturing device 26 (i.e., the positions of the reflective device 28, the frame 140, and the image-capturing device 26, relative to each other) becomes simplified.

[00187] Therefore, the configuration that combines the use of the smartphone 24 and the reflection device 28 is a simplified configuration compared to the configuration that combines the use of the smartphone 24 and the computer 180.

[00188] According to one of these modalities, the implementation of the method according to the disclosure comprises: Petition 870260049400, dated 05 / 25 / 2026, page 45 / 133 40 / 53 - Display the first and second patterns 20 on the computer screen 180 or print them on a piece of paper, - Use an image capture device, such as a smartphone's rear camera 24, - hold at least one lens 30 and / or the frame 140 between the first and second patterns 20 and the smartphone 24 so that the first pattern is seen through the lens and the second pattern is seen directly (i.e., outside the lens) by the image capture device.

[00189] By way of non-limiting example, the implementation of the method according to the disclosure further comprises: before displaying the first and second patterns 20, displaying the third pattern on the computer screen 180 to better guide the user and replacing it with the first pattern to find the optical center and power.

[00190] In an embodiment encompassed by Figure 19, where the first and second patterns 20 are not known and if (i) the distance of the first and second patterns 20 to the image capture device and (ii) the distance of that one of the lenses 30 to the image capture device are known, at least one optical parameter of that lens 30, for example, sphere and cylinder, can be recovered from the first and second datasets by calculating the magnification between the first pattern and the second pattern.

[00191] In such an embodiment, the upper part of the font pattern is advantageously identical to the lower part of the font pattern. Furthermore, if the upper and lower parts are not the same size, the method according to the disclosure may comprise obtaining and using size information, for example, using the size ratio.

[00192] In this mode, the distance from the standards to the image capture device and from the lens to the image capture device can be obtained by means of a rangefinder, or by means of a ruler, or by Petition 870260049400, dated 05 / 25 / 2026, page 46 / 133 41 / 53 in the middle of a standard card or in any other suitable form.

[00193] In another embodiment encompassed by Figure 19, where the first and second patterns 20 are known, the second dataset can be used to determine the relative positions (including orientation and location) between the smartphone 24 and the computer screen, i.e., the positions of the smartphone 24 and the computer screen 180 relative to each other, using ray tracing and running an optimization algorithm. Then, if the position of the frame 140 is known, at least one optical parameter of one of the lenses 30 (the lens whose at least one optical parameter must be recovered), for example, sphere and cylinder, can be recovered from the first dataset using ray tracing and running an optimization algorithm.

[00194] If the source pattern (i.e., the first and second patterns 20) is not known, an image of the first and second patterns 20 in front of the image capture device 26 can be taken with the image capture device 26 located at another position, in order to obtain an image of the first and second patterns 20, such that the source pattern is known in the coordinate system of the image capture device 26.

[00195] In a particular embodiment, an image of the first and second patterns together with a reference object (e.g., a credit card) can be captured.

[00196] As a variant, an image of the first and second patterns can be captured with a camera with known focal length and pixel size, in addition to camera pattern distance information provided by a sensor (e.g., rangefinder).

[00197] As another variant, an image of the first and second patterns can be captured with a 3D camera.

[00198] In this mode, the position of frame 140 can be Petition 870260049400, dated 05 / 25 / 2026, page 47 / 133 42 / 53 obtained automatically, by means of a frame support or by means of a rangefinder, or by means of a ruler, or in any other appropriate manner.

[00199] In yet another modality encompassed by Figure 19, where the first and second patterns 20 are known and where frame 140 is also known: - The second dataset can be used to determine the relative positions (including orientation and location) between the smartphone and the computer screen, i.e., the positions of the smartphone and the computer screen relative to each other, using ray tracing and running an optimization algorithm; - Some characteristic points of frame 140 can be used to determine the position of frame 140 (including orientation and location), by running an optimization algorithm in the same way as for processing the second pattern; - At least one optical parameter of one of the 30 lenses (the lens whose at least one optical parameter must be recovered), for example, sphere and cylinder, can be recovered from the first dataset using ray tracing and running an optimization algorithm.

[00200] In this type of model, frame 140 may be known by several names: - using the framing learning step described earlier, to learn precise framing information, for example, framing dimensions and / or characteristic framing points, as these are related to distance and orientation; or - using a database that stores appropriate information about frames.

[00201] The learning stage of framing in this modality is Petition 870260049400, dated 05 / 25 / 2026, page 48 / 133 43 / 53 different from the frame learning step described in the embodiment involving a mobile device and a reflective device, where the frame learning step is used to learn the shape of the frame. The frame learning step may involve taking a picture of the frame along with a reference object (e.g., a credit card) in front of the image capture device.

[00202] As a variant, the frame learning step may involve taking a picture of the frame with a camera with known focal length and pixel size, in addition to camera frame distance information provided by a sensor (e.g., rangefinder).

[00203] As another variant, the frame learning stage may involve taking a picture of the frame with a 3D camera.

[00204] As described earlier, the methods involving a reflective device allow the use of only one device for displaying patterns and capturing images. In addition, these methods allow partial determination of the frame's position simply by blocking the frame against the mirror.

[00205] To facilitate the use of the system according to the disclosure by any user without the use of glasses, automatic user assistance, also called user guidance in the present disclosure, may be provided, as described above, as a non-limiting example, in connection with the frame learning stage.

[00206] In one embodiment, to facilitate for a user the operation of obtaining an image of the source pattern, with the image capture device 26 taking a picture of the frame while keeping the frame in contact with the reflection device 28, the user's orientation may consist, as a non-limiting example, in: Petition 870260049400, dated 05 / 25 / 2026, page 49 / 133 44 / 53 - display a third pattern (such as a blue square, a logo, or any other pattern deemed appropriate) as described previously for the user to position the smartphone approximately 24 times. - Use the algorithms as described above, for example, through an application running on the smartphone 24 to control the distance between the smartphone and the reflecting device and prompt the user to stop when the smartphone is at the correct distance, - Use the algorithm as described above, for example, through an application running on a smartphone 24, to place the source pattern in the optical center or display several determined patterns successively and then take the necessary images.

[00207] In one embodiment, positioning the smartphone 24 comprises the following steps: - Step 1: 24-hour smartphone orientation - Step 2: Remote positioning of the smartphone 24, - Step 3: Adjusting the brightness of the smartphone screen.

[00208] In addition, in this mode, the positioning of the glasses includes the following steps: - Step 4: Frame detection, - step 5: automatic photo capture.

[00209] The steps for positioning the smartphone and glasses are detailed below. Step 1: 24-hour smartphone orientation

[00210] For smartphone positioning, the user opens and runs an application available on the smartphone 24 while holding the smartphone 24 in front of a mirror with the screen of Petition 870260049400, dated 05 / 25 / 2026, page 50 / 133 45 / 53 smartphone facing the mirror.

[00211] Advantageously, the 24-inch smartphone has a predetermined tilt angle relative to the mirror. This simplifies the user experience, as described below.

[00212] By way of non-limiting example, the smartphone gravimeter, which calculates the gravitational attraction of the Earth on the three axes X, Y, Z, respectively, pitch, roll and yaw axes of the smartphone 24 as shown in Figure 21, can be used for this purpose.

[00213] Having a tilt angle causes the smartphone 24 to have a predetermined portion of the Earth's gravitational attraction on the Z yaw axis and the remainder of the attraction on the roll axis. Thus, the smartphone 24 is oriented relative to the mirror in such a way that the top of the smartphone 24 is closer to the mirror than the bottom of the smartphone 24. In other words, the smartphone is tilted forward.

[00214] In this mode, as shown in Figure 22, a first fixed object 220, which, by way of non-limiting example, may have a first predetermined color, is displayed at the top of the smartphone screen.

[00215] By way of non-limiting example, the first fixed object 220 may be a colored geometric shape, for example a blue rectangle.

[00216] In addition, a first moving object 222 of a second predetermined color different from the first color and having a size smaller than or equal to the size of the first fixed object 220, is also displayed on the smartphone screen.

[00217] By way of non-limiting example, the first moving object 222 may have a geometric shape identical to the shape of the first fixed object 220, for example the first moving object 222 may be a Petition 870260049400, dated 05 / 25 / 2026, page 51 / 133 46 / 53 white rectangle.

[00218] The first moving object 222 is moving in accordance with the tilt of the smartphone 24. Having the first moving object 222 displayed inside the first fixed object 220, as shown in Figure 22, means that the smartphone 24 is tilted forward.

[00219] As a variant, both the first objects 220 and 222 may be moving relative to each other, although this may be less ergonomic for the user. Step 2: Remote smartphone positioning 24

[00220] For remote positioning, i.e., to ensure that the smartphone 24 is at the correct distance from the mirror, one or more remote positioning patterns 230 may be displayed at the bottom of the smartphone screen. If multiple remote positioning patterns 230 are displayed, for example, two remote positioning patterns 230, they may be identical to each other.

[00221] Figure 23 shows a non-limiting example of a 230 distance positioning pattern. Any of the 230 distance positioning patterns is detected, for example, by model matching, i.e., by determining whether the 230 distance positioning pattern matches a 240 model that is, for example, a smaller internal part of the 230 distance positioning pattern.

[00222] Figure 24 shows a non-limiting example of a model 240. The model matching process makes it possible to obtain the center position of the distance positioning patterns 230 and then track the smartphone 24 in the camera stream.

[00223] How the position of the 230 distance positioning patterns on the smartphone screen can be independently fixed Petition 870260049400, dated 05 / 25 / 2026, page 52 / 133 47 / 53 of the smartphone type, this position will thus be known, which makes it possible to calculate the distance between two adjacent distance positioning patterns 230 at various distances from the mirror, so that the distance between the smartphone 24 and the mirror is known, and is known when the smartphone 24 is at an appropriate distance from the mirror, for example, 30 cm, for carrying out the subsequent steps of the method.

[00224] A message, such as a mirrored character or a sequence of characters, may be displayed on the smartphone screen if the smartphone is too close to the mirror, to prompt the user to move the smartphone back.

[00225] Similarly, a message such as a mirrored character or a sequence of characters may be displayed on the smartphone screen if the smartphone is too far from the mirror, in order to encourage the user to move the smartphone forward. Step 3: Adjusting the screen brightness of your smartphone.

[00226] Adjusting the brightness of your smartphone screen can be helpful, as ambient lighting can vary. To do this, the following steps can be implemented.

[00227] During a loop, the brightness of the smartphone screen is first increased in small steps until it reaches a predetermined maximum value, and then decreased in the same way in small steps until it reaches a predetermined minimum value.

[00228] As soon as all the distance positioning patterns 230 are detected in an image during the loop, the loop stops and the brightness of the smartphone screen is adjusted in small steps until the average color of the combined model 240 is in the range [120; 140] in the grayscale color space [0; 255].

[00229] Figure 25 shows the brightness of model 240 from Figure 24 with, Petition 870260049400, dated 05 / 25 / 2026, page 53 / 133 48 / 53 from left to right, three views showing a brightness that is respectively correct, too high, and too low.

[00230] Thus, the user will see the smartphone screen alternate between light and dark during the loop and, as soon as all 230 distance positioning patterns are detected, a predetermined signal, such as a stop sign, will be displayed and / or voice guidance will prompt the user to stop moving the smartphone.

[00231] At this moment, the 24-inch smartphone is ideally tilted and positioned at the right distance, and the ideal brightness has been achieved. Step 4: Frame detection

[00232] In one embodiment, to detect the eyeglass frame 140 in the camera stream, an object detection and recognition model based on a neural network is used to detect the lens 30 in the camera stream. By way of non-limiting example, a Yolo v3-Tiny type neural network can be used. The model is trained using a predetermined number of photos of a frame against a mirror and photos of a frame on a person's face.

[00233] The neural network returns the position and size, called the Region of Interest (ROI), of all lenses it detects in the camera stream. For example, it may return at least two lenses, which correspond to the left and right lenses in the 140 eyeglass frame.

[00234] Figure 26 illustrates the corresponding user orientation.

[00235] As shown in Figure 26, a second fixed object 260, which, by way of non-limiting example, may have a predetermined first color, is displayed in the center of the smartphone screen. It represents the center of the top of the smartphone screen in the camera stream.

[00236] By way of non-limiting example, the second fixed object 260 could be a colored geometric shape, for example a circle. Petition 870260049400, dated 05 / 25 / 2026, page 54 / 133 49 / 53 red.

[00237] Furthermore, a second moving object 262 of a second predetermined color different from the first color and having a shape and size equal to the shape and size of the first fixed object 260, is also displayed on the smartphone screen. This represents the lens 30 from which at least one optical parameter must be recovered by the method and system according to the present disclosure.

[00238] By way of non-limiting example, if the second fixed object 260 is a red circle, the second moving object 262 could be a green circle.

[00239] The user is prompted to move the smartphone 24 so that the second moving object 262 coincides with the second fixed object 260, which means that the frame 140 and the smartphone 24 are positioned correctly.

[00240] As a variant, both second objects 260 and 262 may be moving relative to each other, although this may be less ergonomic for the user. Step 5: Automatic photo capture

[00241] When the second moving object 262 coincides with the second fixed object 260, a predetermined object or message is displayed on the smartphone screen, so that the user knows that the frame 140 and the smartphone 24 should not be moved. By way of non-limiting example, a white circle on a green background may be displayed as a predetermined object.

[00242] At this moment, the photos are automatically taken by the smartphone camera 24 for processing according to the present disclosure in order to recover at least one optical parameter of the lens 30.

[00243] A variant of the step for obtaining a rough estimate of at least one parameter is described below, in a Petition 870260049400, dated 05 / 25 / 2026, page 55 / 133 50 / 53 particular modality where at least one parameter is the lens power.

[00244] In this variant, the following three steps are performed, detailed below: Step A: Estimating the distance between a target and the smartphone camera. Step B: Estimation of horizontal, vertical, and diagonal expansions. Step C: Estimating the lens power based on the estimate obtained in Step A and the estimates obtained in Step B. Step A: Estimating the distance between a target and the smartphone camera. - Calibration data is provided as an input; - Coincident points are determined between a target, for example, pattern 20 displayed on the smartphone screen (the object) and pattern 20 in the mirror (the image). By way of non-limiting example, pattern 20 used for this step could be a QR code displayed at the bottom of the smartphone screen as in Figure 18; - The relative positions of the smartphone 24 and the mirror, and therefore the estimated distance d between the target and the camera, are determined through an optimization process, using the distance denoted Tz between the smartphone 24 and the mirror, as well as the orientation of the smartphone 24 defined by its rotation by a pitch angle Rx and by a roll angle Ry, referring to the pitch and roll axes X, Y shown in Figure 21. Step B: estimation of horizontal, vertical and diagonal magnifications

[00245] Note that, in this variant, the relative positions of the camera, the lens and the pattern 20 are not used in this step, as detailed below.

[00246] Using the part of pattern 20 that is only visible to the camera, Petition 870260049400, dated 05 / 25 / 2026, page 56 / 133 51 / 53, that is, outside the lens 30 (for example, the QR code in Figure 18), and considering that the vertical direction is defined by the Y-axis of the smartphone 24, as shown in Figure 21, three magnifications are determined between the object and the image mentioned above for the camera: - the horizontal magnification for the camera, denoted MCh; - the vertical magnification of the camera, denoted MCv; and - the diagonal magnification for the camera, denoted MCd, which is defined in one of the two diagonal directions, that is, at a 45° angle between the pitch and roll axes X, Y.

[00247] So, using the part of pattern 20 that is seen by the camera through lens 30 (for example, the circular target in Figure 17) and considering that the vertical direction is defined by the Y-axis of the smartphone 24 as shown in Figure 21, three magnifications are determined between the object and the image mentioned above for the set consisting of the camera and lens 30: - the horizontal magnification for the lens + camera assembly, denoted MLCh; - vertical magnification for the lens + camera assembly, called MLCv; and - the diagonal magnification for the lens + camera assembly, denoted MLCd, which is defined in one of the two diagonal directions, that is, at an angle of 45° between the pitch and roll axes X, Y.

[00248] Next, the horizontal, vertical, and diagonal magnifications for lens 30, respectively denoted Mh, Mv, and Md, are extracted as follows: Mh = MLCh / MCh Mv = MLCv / MCv Md = MLCd / MCd Petition 870260049400, dated 05 / 25 / 2026, page 57 / 133 52 / 53 Step C: Estimation of lens power based on the estimate obtained in step A and the estimates obtained in step B.

[00249] Using the estimated distance d obtained in step A and the magnifications Mh, Mv, and Md obtained in step B, the lens power in the horizontal direction, denoted Power_h, the lens power in the vertical direction, denoted Power_v, and the lens power in the diagonal direction, denoted Power_d, are determined as follows: Power_h = (Mh - 1) / (Mh x d) Power_v = (Mv - 1) / (Mv x d) Power_d = (Md - 1) / (Md x d)

[00250] In more detail, the above formulas are obtained as follows, referring to Figure 27.

[00251] The enlargements M are defined as A'B' / AB = OA' / OA.

[00252] The power P is defined as (1 / OA') - (1 / OA).

[00253] Thus, OA' = (1 / (P(1 / OA))), which gives OA' / OA = (1 / (P.OA 1)).

[00254] As OA = -d, M = 1 / (1 - dP).

[00255] As a result, P = (M - 1) / (Md).

[00256] If lens 30 is a progressive lens, lens 30 will have to be sufficiently covered by the source pattern to recover the full energy distribution. Furthermore, it is necessary to know where the powers are measured. To obtain information about the position within the lens, there are two options: - or detect the permanent markings on the lens, so that the power distribution is known in the lens's R-coordinate system (several known techniques are available in this regard); - or detect the position of the user's eyes within the frame (known tools are available for this purpose), so that the power distribution is known in the coordinate system of the user's face. Petition 870260049400, dated 05 / 25 / 2026, page 58 / 133 53 / 53

[00257] For both options, at least one additional acquisition may be necessary to retrieve the new coordinate system that must be taken as a reference. For example, in the second option, a portrait taken with a front-facing camera by the user could be used.

[00258] At least some of the steps of the various embodiments of the method described above can be executed by a processor, in the form of one or more instruction sequences of a computer program product accessible to the processor.

[00259] One or more instruction sequences can be stored in a non-transient storage medium.

[00260] The processor and / or the non-transient storage medium may be part of a computer device that may be partially or wholly comprised within the aforementioned system.

[00261] The method for recovering at least one optical parameter of an ophthalmic lens as described above may be used to manufacture a duplicate of the lens.

[00262] Although representative methods, systems, products and devices have been described in detail herein, those skilled in the art will recognize that various substitutions and modifications may be made without departing from the scope of what is described and defined by the appended claims. Petition 870260049400, dated 05 / 25 / 2026, page 59 / 133

Claims

1 / 6 CLAIMS 1. Method for recovering at least one optical parameter of an ophthalmic lens, characterized in that it comprises: obtaining (10) an image of a first and a second pattern simultaneously, using an image capture device located in a first position, the image including both the first and second patterns, with the second pattern being fully uncovered by the lens, the first and second patterns being different; from said image, obtaining (12) a first data set of at least a part of said first pattern that is seen by said image capture device through said lens; from said image, obtaining (14) a second data set of at least a part of said second pattern that is seen by said image capture device outside said lens;recover (16) the said at least one optical parameter using the said first and second datasets and taking into account the positions, relative to each other, of the said image capture device, the said lens and the said first and second standards.; 2. Method, according to claim 1, characterized in that said recovery comprises obtaining said positions, relative to each other, of said image capture device, said lens and said first and second standards, using said second dataset.

3. Method, according to any one of claims 1 or 2, characterized in that said recovery further comprises: Petition 870260049400, dated 05 / 25 / 2026, p. 60 / 133 2 / 6 obtaining an approximate estimate of said at least one parameter, using said first dataset and said positions, relative to each other, of said image capture device, said lens and said first and second standards; to obtain a refined estimate of said at least one optical parameter, using said first dataset and said positions, relative to each other, of said image capture device, said lens and said first and second standards and applying an optimization technique based on minimizing a cost function, a value of said cost function being determined using ray tracing.

4. A method, according to any one of claims 1 or 2, characterized in that said recovery further comprises obtaining an approximate estimate of said at least one parameter by: estimating a distance between said image-capturing device and at least a part of said second pattern that is seen by said image-capturing device outside said lens; estimating the magnifications in the horizontal, vertical, and diagonal directions between an object and an optical image of said object; recovering said at least one optical parameter using said estimated distance and said estimated magnifications.

5. Method, according to any of the preceding claims, characterized in that said obtaining of said image of said first pattern comprises reflecting said first pattern by a reflective device before being seen by said image capture device through said lens and said obtaining of said image of said second pattern comprises reflecting said second pattern by said reflective device before being seen by said image capture device outside said lens.

6. A method, according to any of the preceding claims, characterized in that said lens is mounted in a frame, which further comprises detecting a position of said frame and deducing it from a cylinder axis of said lens.

7. Method, according to claim 6, characterized in that the detection consists of obtaining an image of said frame using said image capture device located in a second position.

8. A method, according to any of the preceding claims, characterized in that said first and second patterns are unknown, further comprising obtaining an image of said first and second patterns using said image capture device located in a third position.

9. Method, according to any one of claims 5 or 6, characterized in that the obtaining of said images of said first and second patterns comprises: positioning said frame against said reflective device so that a front surface of said lens is tangent to said reflective device at a point of contact; orienting said first and second patterns toward said lens; orienting said image capture device toward said lens.

10. Method, according to claim 9, characterized in that said first and second patterns are displayed on a screen of a mobile device equipped with said image capture device, wherein: said orientation steps comprise tilting said mobile device by a predetermined angle of inclination relative to said reflection device; said obtaining of said images of said first and second patterns further comprises: determining a distance between said screen and said reflection device by displaying on said screen at least one distance positioning pattern and moving said mobile device forward or backward relative to said reflection device until said distance reaches a predetermined value;adapt the brightness of said screen by repeatedly increasing and decreasing said brightness between a predetermined maximum value and a predetermined minimum value, until said at least one distance positioning pattern is detected in a stream from said image capture device; detect said ophthalmic lens in said stream using a neural network; automatically capture, by said image capture device, said images of said first and second patterns as soon as said orientation, distance determination, brightness adaptation, and lens detection steps are completed.

11. A method according to any one of claims 6, 7, 9 or 10, characterized in that the detection of the frame position consists of applying an optimization technique based on minimizing a cost function, the value of the cost function being determined by using ray tracing.

12. Method, according to any of the preceding claims, characterized in that it further comprises Petition 870260049400, dated 05 / 25 / 2026, page 63 / 133 5 / 6 determination of an optical center of said lens based on said image of said first pattern.

13. System for implementing a method for retrieving at least one parameter from an ophthalmic lens, characterized in that said method comprises: obtaining an image of a first and a second pattern simultaneously, using an image capture device located in a first position, the image including both the first and second patterns, with the second pattern being fully uncovered by the lens, the first and second patterns being different; from said image, obtaining a first data set of at least a part of said first pattern that is seen by said image capture device through said lens; from said image, obtaining a second data set of at least a part of said second pattern that is seen by said image capture device outside said lens;recover said at least one optical parameter using said first and second datasets and taking into account the positions, relative to each other, of said image capture device, said lens and said first and second standards, wherein said system comprises: at least one processor; a mobile device equipped with said image capture device; and a reflective device or a computer.

14. Non-transient storage medium, characterized by the fact that it stores one or more sequences of instructions that are accessible to a processor and that, when executed by said processor, causes said processor to: Petition 870260049400, dated 05 / 25 / 2026, page.64 / 133 6 / 6 obtain an image of a first and a second pattern simultaneously using an image capture device located in a first position, the image including both the first and second patterns, with the second pattern being fully uncovered by the lens, the first and second patterns being different; from said image, obtain a first data set of at least a portion of said first pattern that is seen by said image capture device through said lens; from said image, obtain a second data set of at least a portion of said second pattern that is seen by said image capture device outside said lens; recover said at least one optical parameter using said first and second data sets and taking into account the positions, relative to each other, of said image capture device, said lens and said first and second patterns.Petition 870260049400, dated 05 / 25 / 2026, p. 65 / 133.

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