WO2024028457A1

WO2024028457A1 - Method for characterising the optical quality of a given region of a vehicle glazing unit

Info

Publication number: WO2024028457A1
Application number: PCT/EP2023/071586
Authority: WO
Inventors: Daouda Keita DIOP; Valentin COMPAIN
Original assignee: Saint-Gobain Glass France
Priority date: 2022-08-04
Filing date: 2023-08-03
Publication date: 2024-02-08
Also published as: FR3138697A1

Abstract

One aspect of the invention relates to a method for characterising the optical quality of a given region of a vehicle glazing unit among a plurality of vehicle glazing units of a glazing unit production line, the given region of each glazing unit being intended to be positioned in the optical path of an image capturing device, the characterisation method being carried out during a period no longer than a predetermined period of operation of the production line, before the arrival of another glazing unit, according to a step of characterising the optical quality of the given region by comparing quality indicators relating to the optical defect map with a predetermined threshold.

Description

DESCRIPTION TITLE: Method for characterizing the optical quality of a given zone of vehicle glazing TECHNICAL FIELD OF THE INVENTION [0001]The technical field of the invention is that of intelligent driving assistance systems. [0002]The present invention relates to a method and a device for characterizing the optical quality of a given zone of vehicle glazing, intended to be placed in the optical path of an image acquisition device. an intelligent driving assistance system. TECHNOLOGICAL BACKGROUND OF THE INVENTION [0003] More and more land transport vehicles, and in particular road vehicles of the automobile or truck type, are equipped with intelligent driving assistance systems (called ADAS, for Advanced Driver Assistance System, in Anglo-Saxon terminology) to limit the risk of accidents and make driving easier for drivers. These ADAS systems are also designed to equip driverless vehicles, called “autonomous vehicles”. [0004] These ADAS systems are on-board systems which provide various information in real time (such as the state of road traffic), detect and anticipate possible threats from the external environment of the vehicle, or even help the driver to realize difficult or risky maneuvers, such as passing other vehicles or parking. To do this, these ADAS systems include numerous detection devices, or sensors, to collect data on the vehicle's environment. Certain systems, for example parking assistance systems, autonomous driving systems or even collision anticipation systems, also implement one or more image acquisition devices, or cameras. [0005]The data acquired by these image acquisition devices are processed by ADAS systems, also called on-board systems, to obtain the desired functionality. For example, a night driving assistance system makes it possible to display in real time, on the vehicle dashboard, a video of the external environment via an infrared camera placed behind the windshield. of the vehicle. In another example, an autonomous driving system processes the images acquired by a camera placed behind the windshield of the vehicle in order to extract the data necessary for automatic piloting of the vehicle. [0006]Generally, the image acquisition devices are arranged inside the vehicle and generally positioned behind one of the windows of the vehicle, such as the windshield, the rear window or even the side windows, so to be protected from external elements such as rain, hail, flying stones, etc. Most of these image acquisition devices are placed behind the windshield to enable the acquisition of information relating to the environment located in front of the vehicle. The data acquired by the on-board systems, and in particular the images, are therefore obtained through the glazing. Indeed, from an optical point of view, the positioning of the image acquisition devices behind the windshield is such that the light rays received by these image acquisition devices first pass through the glazing before 'reach said devices. The glazing must therefore have optimal optical quality or at least sufficient to prevent the image captured by the image acquisition device from being distorted. [0007]However, the glazing often has optical defects whose origins are diverse. One of the characteristics causing optical defects is the inclination of the glazing. Indeed, most vehicle windows, particularly windshields and rear windows, are tilted; the optical beams passing through these glazings can therefore be distorted by this inclination of the glazing. Another characteristic causing optical defects is the area of the glazing called the “camera area” which includes opaque elements intended in particular to hide part of the elements of the image acquisition devices so that they are not visible from the exterior of vehicles. These opaque elements, most often made of enamel, in fact lead to a reduction in the optical quality of the camera zone of the glazing in the area bordering the opaque elements, in particularly in the area of the glazing located at a distance of between 5 and 8mm from the opaque elements. Furthermore, in the particular case of areas delimited by enamel deposited at high temperature on glass glazing, differences in thermal expansion coefficient or physicochemical interactions between the enamel materials and the glass can cause variations. local areas of the surface near their edges, such as variations in refractive index and/or geometric deformations relative to the rest of the glazing surface. In addition, the zones delimited by opaque elements can also include, on their surface, functional elements (such as networks of heating wires or functional layers with optical or thermal properties) which are directly placed in the acquisition field of the image acquisition devices and which generate optical defects. [0008] During the construction of a vehicle, the glazing is always positioned on the vehicle before the ADAS system. The glazing is therefore manufactured before the integration of the image acquisition device. Thus, it is necessary to check the optical quality of the camera zone of the glazing, and in particular of the camera zone, before the glazing is mounted on the vehicle in order to avoid the presence of optical defects. origin of harmful artifacts in the acquired images. For economic reasons, it could be interesting to integrate the measurement of the optical quality of the camera zone of a glazing on a glazing production line so that each glazing can be controlled before the end of its manufacture. [0009]A known method for measuring the optical quality of glazing, in particular vehicle windshields, is deflectometry which measures the refraction of the glazing. This method uses a screen, positioned on one side of the glazing and for which the position of each emitting point is known, and a CCD sensor, positioned on the other side of the glazing. However, this measurement method only makes it possible to determine the distortion introduced by the glazing and does not make it possible to precisely identify and quantify the optical defects which alter the quality of the image captured using this method. This method also does not make it possible to measure the optical quality of a reduced area of glazing, particularly when opaque elements surrounding said area are the cause of optical distortions at their proximity. In fact, this method has a spatial resolution such that the optical quality measurements are limited to a surface portion of said given zone. [0010] Another measurement method, disclosed in patent document WO 2021/110901 A1 filed on behalf of the applicant, proposes to determine the optical quality of a given region using a wavefront analyzer. This analyzer makes it possible to analyze the wavefront of the light rays emitted by a light ray emitter through the camera zone of the glazing. This technique has the advantage of being particularly effective for measuring the optical quality of a given area of glazing. However, the method proposed for analyzing optical defects in the given area of each glazing can be time-consuming, for example increasing glazing delivery times, and can generate significant costs for the glazing manufacturer. [0011] There is therefore a need to analyze the optical defects of the given zone of each glazing of a plurality of glazings in an efficient manner, without increasing glazing delivery times. SUMMARY OF THE INVENTION [0012]The invention offers a solution to the problems mentioned above, by making it possible to determine the optical quality of the given area of a glazing directly on a glazing production line. [0013]A first aspect of the invention relates to a method for characterizing the optical quality of a given zone of a vehicle glazing of a plurality of vehicle glazings of a glazing production line, the given zone of each glazing being intended to be positioned in the optical path of an image acquisition device, the characterization method being carried out during a period less than or equal to a predetermined period of operation of the production line according to the following steps : - Detection of the presence of glazing; - Detection of the given area of glazing in an area of the glazing covered by a wavefront analyzer and including the given area; - Acquisition of the wavefront of the given area and generation of a wavefront error map; - Calculation from the wavefront error map of at least one map of optical defects present in the given zone and determination of at least one quality indicator relating to the optical defect map; - Characterization of the optical quality of the given area by comparison of each quality indicator relating to the optical defect map at a predetermined threshold. [0014]Thanks to the invention, the steps allowing the characterization of the optical quality of the given zone of glazing are carried out directly on a production line, during a period less than or equal to a predefined period, which allows a glazing manufacturer, for example, to save time in characterizing the optical quality of a glazing. State of the art methods propose to characterize the given area of the glazing outside a production line, which requires significant additional time to the production time and costs for the manufacturer unlike the invention which allows you to calculate in real time, when the glazing is in the production line, at least one fault map. [0015] In addition to the characteristics which have just been mentioned in the previous paragraph, the method according to the first aspect of the invention may present one or more complementary characteristics among the following, considered individually or in all technically possible combinations. [0016] According to one embodiment, the method comprises, before the step of characterizing the optical quality of the given zone, the following steps: - display of the optical defect map; and/or - display of the optical quality indicator relating to the optical fault map. Advantageously, this characteristic makes it possible to qualitatively determine optical defects present in the given zone. Advantageously, this characteristic makes it possible to see in real time on the production line, the optical fault map and/or the quality indicators, allowing for example an operator to directly know the glazing to be eliminated from the production line or to be modified. . [0017] According to one embodiment, the method comprises, between the step of detecting the presence of the glazing and the detection of the given zone, a step of acquiring the wavefront of the zone of the glazing covered by the analyzer wave front. [0018] According to one embodiment, compatible with the previous embodiment, the step of detecting the given area of the glazing comprises the following sub-steps: - Generation, from the acquired wave front of the covered area by the wavefront analyzer, an image of an interferogram of the area of the glazing covered by the wavefront analyzer, the area of the glazing covered by the waveform analyzer comprising a plurality of sub-zones including the given zone; - Thresholding of the interferogram image to obtain a first image; - Application of a morphological aperture filter on the first image to obtain a second image, - Detection, on the second image, of the contour of each sub-zone of the glazing area covered by the wavefront analyzer : - When the number of detected contours is non-zero: - Determination, for each contour, of the rotating rectangle of minimum area comprising said contour to obtain a set of rectangles; - Selection, among all the rectangles, of the rectangles included in a predefined zone: -If at least one rectangle is selected: -Selection of the rectangle of maximum area among the at least one rectangle selected; -Recovery of the coordinates of the pixels forming the contour included in the rectangle of maximum area; -From the coordinates of the pixels recovered, calculation of a polygonal shape corresponding to an approximation of the contour included in the rectangle of maximum area, the calculated polygonal shape representing the given area of the glazing, - if no contour is selected, determination on the second image of a polygonal shape corresponding to a predefined area, the polygonal shape representing the given area of the glazing. [0019] According to one embodiment, the method for characterizing the given area according to the first aspect of the invention is implemented by a characterization system comprising a beam emitter of light rays and the front analyzer. wave and the step of generating the wave front error map comprises the following sub-step: - calculation of a phase difference between the wave front of the light rays transmitted by said given zone of the glazing and a reference wavefront for determining a wavefront error used to generate the wavefront error map. [0020] According to one embodiment, the optical defect map is chosen from the following list: - an optical aberration map, - a slope or deflection map, - a map of the point spreading function - a modulation transfer function map, - a vertical distortion map and/or a horizontal distortion map. This characteristic is advantageous because the types of optical defect maps cited are not measured in real time in the state of the art. [0021] According to a variant embodiment, at least two optical defect maps are calculated and: - a first optical defect map among the at least two optical defect maps is a distortion map chosen from a vertical distortion map and a horizontal warp map, and - a second optical defect map among the at least two optical defect maps is a modulation transfer function map, the method comprising, before the characterization step, a step of comparing the first optical defect map and of the second optical defect map and in that the characterization of the optical quality of the given zone is implemented from the comparison step. - the second image, of a polygonal shape corresponding to a predefined area, the polygonal shape representing the given area of the glazing. [0022] According to an embodiment compatible with the previous embodiment, the step of detecting the given area of the glazing further comprises a sub-step of displaying the given area of the glazing. [0023] According to one embodiment, the wavefront error map is a matrix and the step of calculating at least one optical defect map comprises the following substeps: - Creation of a mask binary, the binary mask being a matrix of the same size as the wavefront error map and in which: - Each coefficient whose index corresponds to a coefficient of the non-zero wavefront error map is equal to the same first binary information 0 or 1; - Each coefficient whose index corresponds to a coefficient of the zero wavefront error map is equal to the same second binary information 1 or 0 complementary to the first binary information; - Application of a morphological erosion filter on the binary mask, the optical defect map also being calculated from the binary mask. [0024] According to one embodiment, the step of detecting the given zone, the step of calculating the optical defect map from the wavefront error map and the step of determining the at least quality indicator are implemented according to a programming language capable of executing said steps in a period strictly less than the predetermined period. Advantageously, this This feature makes it possible to respect the times required in a production line. [0025] According to one embodiment, the vehicle is a road or rail vehicle. [0026] According to one embodiment, the predetermined period of operation of the production line is less than 20 seconds inclusive, in particular less than 15 seconds inclusive and preferably less than 12 seconds inclusive. [0027] According to one embodiment, the glazing among the plurality of glazings of the glazing production line comprises a marking associated with an identifier, the identifier being uniquely associated with the glazing, and the method further comprises the steps following: - reading of the identifier by the characterization system, - storage in a memory of: - the identifier associated with the glazing, - the optical quality of the given zone of the glazing determined during the characterization step, - association in the memory of the stored identifier and the stored optical quality. [0028] According to an embodiment compatible with the previous embodiment, the method further comprises the following steps: - storage in the memory of the calculated optical defect map, - association in the memory of the stored identifier and the stored optical defect map. [0029] According to one embodiment of the invention, the image acquisition device is a LIDAR and the given zone is adapted to be fixedly mounted opposite the LIDAR, said LIDAR comprising a light emitter and a light receiver, the given area comprising a first part adapted to be fixedly mounted facing the transmitter, a second part, different from the first part, adapted to be fixedly mounted facing the receiver, the quality indicator being determined by an absolute deviation between an average deflection of the first part and between an average deflection of the second part. [0030] According to one embodiment of the invention, the image acquisition device is a stereoscopic camera and the given area is adapted to be fixedly mounted facing the stereoscopic camera, the stereoscopic camera comprising a first camera and a second camera, the given zone comprising a first part adapted to be fixedly mounted facing the first camera, a second part, different from the first part, adapted to be fixedly mounted opposite the second camera, the quality indicator being determined by an absolute difference between an average deflection of the first part and between an average deflection of the second part. [0031]A second aspect of the invention relates to a system for characterizing the optical quality of at least one given zone of glazing comprising means configured to implement the method according to the first aspect of the invention. [0032] Another aspect of the invention relates to a computer program product comprising program code instructions recorded on a medium usable in a computer, comprising: - computer-readable programming means for carrying out the step of detecting the given area, - computer-readable programming means for carrying out the calculation step from the wavefront error map of at least one optical defect map and the step of determining at least one at least one quality indicator relating to the optical defect map, - computer-readable programming means for carrying out the step of characterizing the optical quality of the given zone; when said program runs on a computer. [0033]The invention and its various applications will be better understood on reading the following description and examining the accompanying figures. BRIEF DESCRIPTION OF THE FIGURES [0034]The figures are presented for information purposes only and in no way limit the invention. [0035] [Fig. 1] is a schematic representation of a road vehicle windshield comprising a given area delimited by an opaque element. [0036] [Fig. 2] is a schematic representation of an image acquisition device placed behind the windshield shown in Figure 1, such that the given area is in the optical path of the image acquisition device. [0037] [Fig.3] is a schematic representation of a characterization system according to one embodiment of the invention, which makes it possible to characterize the optical quality of a given zone of glazing. [0038] [Fig. 4] is a block diagram of a method for characterizing the optical quality of a given zone of glazing, according to a first aspect of the invention. [0039] [Fig. 5] is a block diagram detailing step 103 of the method according to the first aspect of the invention. [0040] [Fig. 6] is a block diagram detailing step 104 of the method according to the first aspect of the invention. [0041] [Fig. 7] is a block diagram detailing step 105 of the method according to the first aspect of the invention. [0042] [Fig. 8] is a block diagram detailing step 106 of the method according to the first aspect of the invention. [0043] [Fig. 9] is a block diagram detailing step 107 of the method according to the first aspect of the invention. [0044] [Fig.10] is a block diagram detailing step 108 of the method according to the first aspect of the invention. DETAILED DESCRIPTION [0045] Unless otherwise specified, the same element appearing in different figures presents a unique reference. [0046]A first aspect of the invention relates to a method for characterizing the optical quality of a given zone of a vehicle glazing of a plurality of vehicle glazings of a glazing production line. [0047]The process is carried out during a period less than or equal to a predetermined period of operation of the production line. [0048]In particular, the characterization process is carried out before the arrival of the glazing following the glazing whose given zone is characterized on the production line. The predetermined period of operation of the production line is less than or equal to 20 seconds, in particular less than or equal to 15 seconds and preferably less than or equal to 12 seconds. [0050] By “glazing” we mean a plate formed from a transparent material such as glass or plastic. Advantageously, the glazing can be a windshield, a rear window or even side glazing of a road or rail vehicle. [0051]The glazing is preferably road or rail vehicle glazing. [0052] Figure 1 illustrates an example of glazing 10. [0053] With reference to [Fig.1], the glazing 10 is a windshield comprising a sheet 11 of glass 11 and an opaque element 12. The element opaque 12 makes it possible in particular to hide from the outside of the vehicle elements arranged inside said vehicle, for example a part of an image acquisition device. The opaque element 12 covers at least one of the main faces of the glass sheet 11 so as to border the entire glazing 10. The opaque element 12 can be placed on the surface of only one of the two main faces of the sheet 11 of glass or may comprise several portions, each of the portions being arranged on one and the other of the main faces of the sheet 11 of glass. In the case of multiple glazing 10 comprising several sheets of glass, such as laminated glazing 10, the opaque element 12 can also be formed of several portions, each portion being arranged on the surface of two or more sheets of glass depending on the number of servings. Furthermore, the glass sheet 11 can be inclined, for example, by an angle of 30°. In addition, the glass sheet 11 can be curved along one or two axes, so that a radius of curvature of the sheet 11 is for example between 6m and 30m. [0054] Preferably, the opaque element 12 is a layer of enamel deposited on the surface of the sheet 11. Naturally, the layer of enamel can be replaced by any other opaque element which makes it possible to hide certain elements from the outside. elements arranged inside the road vehicle. [0055]A given zone 13 can be delimited by the opaque element 12. As can be seen in Figure 1, the opaque element 12 delimits a given zone 13 of the glazing 10, located at the level of the upper edge of the glazing 10. [0056] Preferably, the surface of the given zone 13 is less than 0.5m². The given zone 13 of each glazing is intended to be positioned in the optical path of an image acquisition device. [0058] Figure 2 shows an example of an image acquisition device 20 placed behind the glazing 10 shown in Figure 1. [0059] As can be seen in Figure 2, the image acquisition device 20 is placed behind the glazing 10 so that the given zone 13 is placed on the optical path of the image acquisition device 20, for example using a suitable support (not illustrated). Advantageously, the image acquisition device 20 is a high-resolution digital camera adapted to operate in the visible, ie in wavelengths between 390nm and 750nm. [0060] According to an embodiment not shown, the image acquisition device 20 is a LIDAR adapted to operate in wavelengths between 620nm and 950nm. [0061] According to an embodiment not shown, the image acquisition device 20 is a stereoscopic camera. [0062] Advantageously, a second aspect of the invention concerns a system 40 for characterizing the optical quality of each glazing. [0063] Figure 3 is a schematic representation of the characterization system according to one embodiment of the invention. [0064] With reference to Figure 3, the characterization system 40 comprises a transmitter 41, a plane mirror 42, a wavefront analyzer included in the same housing as the transmitter in this embodiment. The characterization system 40 may also include a production line shutdown detection module, configured to receive a signal representative of the production line shutdown. When the production line is stopped, the glazing 10 can be placed, statically, between the emitter 41 and the plane mirror 42. [0065]The characterization system 40 further comprises means for implementing implementation of the steps of the process according to the first aspect of the invention which will be described below, these means being for example a digital device comprising a network interface comprising an antenna, a memory, a microprocessor, a data restitution means such as a screen. [0066]The glazing is positioned between the emitter and the plane mirror, for example at a distance between 200mm and 250mm from the emitter 41 and at a distance between 250mm and 300mm from the plane mirror. [0067]The transmitter is configured to emit a beam of light rays through a zone of the glazing comprising the given zone. To do this, the transmitter comprises a light source and a collimator placed after the light source in order to obtain a beam of light rays, for example parallel. Advantageously, the light source of the transmitter is monochromatic. In addition, the light source of the transmitter can be adapted to emit in the visible and/or in a range of infrared wavelengths. The light source can emit a light beam having a wavelength of between 400nm and 1200nm and preferably between 620nm and 950nm. Advantageously, the size of the beam makes it possible to completely cover the area of the glazing comprising the given area 13 while guaranteeing sufficient resolution and a flow making it possible to obtain information in the entirety of the given area 13 called the camera area. [0068]In particular, the given zone 13 may have a width and a height along a main surface of the glazing 10. The given zone 13 may have a trapezoidal shape, formed by a lower base and by an upper base. In this case, the width of the given zone 13 is defined by the size of the longest base, for example the lower base. The width of the given zone 13 can be greater than 20 mm, in particular greater than 30 mm and preferably greater than 50 mm. The width of the given zone 13 may be less than 150 mm and preferably less than 100 mm. [0069]The size of the beam can be greater than or equal to the width of the given zone 13 and preferably greater than or equal to the lower base of the given zone 13. [0070]Preferably, the beam is circular. [0071] According to one embodiment, in which the image acquisition device 20 is a LIDAR, the given zone 13 can be adapted to be fixedly mounted facing said LIDAR. In this embodiment of the invention, the width of the given zone 13 can be greater than 150 mm, in particular greater than 250 mm and preferably greater than 600 mm. The height of the given zone 13 can be greater than 100 mm, in particular greater than 150 mm, and less than 400 mm, in particular less than 300 mm. The size of the beam can be between half the width of the given zone 13 and the width of the given zone 13. [0072] According to the previous embodiment of the invention, in which the device for acquiring images 20 is a LIDAR, the given area 13 can be opaque in the visible, in particular by means of a black camouflage element. In this embodiment of the invention, the LIDAR may comprise a light transmitter and a light receiver. The given zone 13 may comprise a first part adapted to be fixedly mounted facing the transmitter, and a second part, different from the first part, adapted to be fixedly mounted facing the receiver. [0073] According to one embodiment of the invention, in which the image acquisition device 20 is a stereoscopic camera, the given zone 13 can be adapted to be fixedly mounted facing the stereoscopic camera. In this embodiment of the invention, the width of the given zone 13 can be greater than 150 mm, in particular greater than 250 mm and preferably greater than 600 mm. The height of the given zone 13 can be greater than 100 mm, in particular greater than 150 mm, and less than 400 mm, in particular less than 300 mm. The size of the beam can be between half the width of the given zone 13 and the width of the given zone 13. [0074] According to the previous embodiment of the invention, in which the device for acquiring images 20 is a stereoscopic camera, the stereoscopic camera may comprise a first camera and a second camera. The given zone 13 may comprise a first part adapted to be fixedly mounted facing the first camera, and a second part, different from the first part, adapted to be fixedly mounted facing the second camera. [0075]The wavefront analyzer, also called an abberometer, covers the area of the glazing comprising the given area and makes it possible to measure the shape of the front waves of the beam emitted by the transmitter and to determine the deformation undergone by the wave front during its passage through the zone of the glazing comprising the given zone 13 and in particular the deformation undergone by the wave front during of its passage through the given zone 13. [0076] As a reminder, a wave front is the three-dimensional wave surface defined so that each light ray coming from the same light source is orthogonal to it. The wavefront analyzer measures the shape of this wave surface. Advantageously, the wavefront analyzer is composed of a system known under the commercial name “Phasics-SID4-HR”, which is based on the principle of four-wave interferometry, and a camera coupled to said system. . This system includes a modified Hartmann mask through which the incident beam propagates and causes it to replicate into four beams. The system generates an interferogram, captured by the camera, which is distorted by wavefront gradients recovered by Fourier analysis. Since the recorded interferogram is primarily sinusoidal, a small amount of pixels are required to recover a phase pixel. This results in increased resolution, at least by a factor of 4, compared to other wavefront analyzers based on gradient recovery such as the so-called Hartmann technique and the so-called Shack-Hartmann technique. [0077]Furthermore, the plane mirror 42 is placed behind the glazing 10 in order to reflect the beam transmitted by the glazing. Advantageously, the plane mirror 42, for example based on silver, is calibrated so as to represent a perfect plane, characteristic of good optical quality, that is to say with low deformation and low roughness of surface. [0078]In a variant embodiment not illustrated, the measuring device does not include a plane mirror. In this case, the transmitter is placed on one side of the glazing while the wavefront analyzer is placed on the other side of the glazing 10. [0079] Figure 4 is a block diagram of the method 100 of characterization according to the first aspect of the invention implemented by the characterization system 40 according to the second aspect of the invention, the method comprising a plurality of steps 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117 described below. [0080]In particular, steps 107 and 108 will be described using several examples. [0081]The method 100 may include a first step 101 of stopping the glazing in the characterization system. [0082]The method 100 comprises a step 102 of detecting the presence of the glazing by the sensor of the characterization system 40 by the production line shutdown detection module. [0083]The method 100 may be devoid of a step of positioning the characterization system 40 in horizontal translation following the shutdown of the production line. “Horizontal” means in the main direction of movement of the line. Indeed, the characterization system 40 can be integrated so as to be centered horizontally in relation to the given zone 13 for different glazing models. [0084]The method 100 may further comprise a step 103 of acquiring the wavefront of the zone of the glazing comprising the given zone 13, the synoptic diagram of which is represented in [Fig.5]. [0085]Step 103 of acquiring the wavefront of the glazing zone comprises a first sub-step 1031 of emitting, by the transmitter 41, a beam of light rays in the direction of said zone of the glazing. glazing. [0086] Step 103 of acquiring the wave front of the glazing zone further comprises a second sub-step 1032 of receiving, by the wave front analyzer, the beam of light rays emitted by the transmitter after its passage through the zone of the glazing comprising the given zone 13. shown in [Fig.6]. [0088] Step 104 of detecting the given zone 13 of the glazing comprises a plurality of sub-steps detailed below. [0089]A first sub-step 1041 of the detection step is a step of generating, from the wave front acquired from the glazing zone, an image of an interferogram of the glazing zone. In particular, the glazing zone comprises a plurality of sub-zones including the given zone 13. [0090]The interferogram generated is preferably a sinusoidal interferogram. [0091]A second sub-step 1042 of the detection step is a step of thresholding the image of the interferogram and in particular the values of the pixels of the image of the interferogram to obtain a first image. [0092]The thresholding of the interferogram is implemented by the digital device of the characterization system 40. Preferably, the thresholding is carried out using the “Threshold” function of the OpenCv ® library. [0093]The first image is a binary matrix, also called a binary mask, of the same size as the image of the interferogram. [0094]For example, the pixel indices (or coefficients) of the image of the interferogram whose value is greater than a threshold S1 and/or less than a threshold S2 correspond to equal pixel indices of the first image to the same binary information. For example, S1 = 1 and S2 = 2000. [0095] A third sub-step 1043 of detection step 104 is a step of applying a morphological aperture filter to the first image, to obtain a second picture. The second image therefore corresponds to the filtered thresholded interferogram image. [0096] Morphological filters are non-linear filters, or kernels, which are used on binary images or gray level images and work on the local neighborhood of each pixel of an image. The shape of this neighborhood is called a structuring element. [0097] Morphological filters make it possible to preserve or delete structures on images having certain characteristics, in particular shape, and to eliminate unwanted noise for example. [0098]A morphological opening filter is obtained by composing a morphological erosion filter and a morphological dilation filter (erosion is followed by dilation). A morphological erosion filter consists of removing from an image all the structures not containing the structuring element and therefore allows example of separating two pasted objects from an image. A morphological dilation filter consists of shifting the structuring element to each pixel of the image, and looking to see if the structuring element "touches" the structure of interest makes it possible to fill in holes or interrupted elements. Advantageously, the aperture filter makes it easy to make isolated elements of a binary or grayscale image disappear, or to fill small holes included in structures. [0099] The substep 1043 of application of the morphological opening filter is preferably carried out using the MorphologyEx Open function of OpenCV® whose core is square and whose size is defined by a user. Preferably, the morphological filter used is a kernel whose size is between 1 and 30. [00100] A fourth sub-step 1044 of the detection step 104 is a step of detection, on the second image, of the contour of each sub-zone of the glazing zone covered by the wavefront analyzer and comprising the given zone 13. [00101] The fourth sub-step 1044 of the detection step is preferably carried out by the FindContours function d 'OpenCV® with an ApproxSimple parameter. [00102] At the end of the fourth sub-step 1044 of the detection step 104, if the number of contours detected is non-zero, the sub-steps 10441 to 1042, which will be described in the remainder of the text, are carried out. [00103] Sub-step 10441 is a sub-step of determining, for each detected contour among the number of detected contours, the rotating rectangle of minimum area comprising said contour. Substep 10441 is carried out using the MinAreaRect function of OpenCV®. At the end of substep 10441, a set of rectangles is obtained. [00104] Sub-step 10442 is a sub-step of selection, among all the rectangles, of the rectangles included in a predefined zone. The predefined zone can be determined by a user for example. [00105] At the end of substep 10442 of the detection step, if at least one rectangle is selected, that is to say if at least one rectangle among all the rectangles is included in the predefined zone, then the sub-steps 104421, 104422, 104423 which will be described in the rest of the writing, are carried out. [00106] Substep 104421 is a step of selecting the rectangle of maximum area relative to the area of the at least selected rectangle. [00107] In particular, if a single rectangle is selected at the end of substep 1443, the rectangle of maximum area is directly the selected rectangle. [00108] Substep 104422 is a step of recovering the coordinates of the pixels forming the contour included in the rectangle of maximum area. [00109] Sub-step 104423 is a step of calculating, from the coordinates of the pixels recovered in sub-step 104422, a polygonal shape corresponding to an approximation of the contour included in the rectangle of maximum area. [00110] Substep 104423 is carried out using the ApproxPolyDP function of OpenCV, with Epsilon parameter. The Epsilon parameter corresponds to the maximum number of sides of the polygon shape approximated by the ApproxPolyDP function and can be set by an operator. Epsilon is for example between 5 and 1500. [00111] The polygonal shape calculated in sub-step 104423 represents the given zone 13 of the glazing. [00112] At the end of substep 10441 of the step of determining at least one rotating rectangle in the predetermined zone, if the number of rectangles detected is zero, substep 10442 described in the rest of the writing is carried out. [00113] Sub-step 10442 is a sub-step of determining a polygonal shape corresponding to a predefined zone, the polygonal shape representing the given zone 13 of the glazing. The determination substep 1045 is carried out by an operator, for example, manually. [00114] At the end of substep 1044 of determining contours, if no contour is selected, substep 1045 described previously is carried out. [00115] The detection step 104 may also include a sub-step 1046 for storing the calculated polygonal shape. [00116] The detection step 104 may also include a sub-step 1047 for displaying the interferogram. [00117] The detection step 104 may further comprise a sub-step 1048 of displaying the stored polygonal shape of the given zone 13 on the interferogram. [00118] The method 100 further comprises a step 105 of acquiring the wave front of the given zone 13 of the glazing, the synoptic diagram of which is shown in [Fig.7], the given zone 13 having been detected at step 104. [00119] Step 105 of acquiring the wavefront of the given zone 13 of the glazing comprises a first sub-step 1051 of emitting, by the transmitter, a beam of light rays in the direction of the given zone 13. The light beam is preferably parallel. [00120] Step 105 of acquiring the wave front of the given zone 13 of the glazing further comprises a second sub-step 1052 of receiving, by the wave front analyzer, the wave front of light rays transmitted by said given zone 13. [00121] According to the embodiment according to which the system comprises the plane mirror on one side of the glazing and the transmitter and the forehead analyzer on the other side of the glazing, the beam emitted by the transmitter passes through the given area 13 before reaching the plane mirror which reflects the beam towards the given area 13 again. The light beam therefore crosses the given area 13 of the glazing twice before reaching the wavefront analyzer. [00122] According to the embodiment in which the image acquisition device 20 is a LIDAR, the step 105 of acquiring the wavefront of the given zone 13 may include sub-steps of acquiring the wave front of the first part and the second part given zone 13. The glazing 10 can be moved between the different sub-stages, so as to measure the wave front of the different parts of the given zone 13. Thus, it is possible to acquire the wavefront of the given zone 13 adapted to be fixedly mounted opposite a LIDAR using the same transmitter and wavefront analyzer as for a given zone 13 adapted to be fixedly mounted in view of an image acquisition device 20 in the visible, such as a thermal camera for example. [00123] The method 100 comprises a step 106 of generating a wavefront error map, the synoptic diagram of which is shown in [Fig. 8]. The wavefront error map is a matrix also called an optical path difference matrix or OPD (English: Optical Path Difference). [00124] The step 106 of generating a wavefront error map comprises a first substep 1061 of calculating the phase difference between the wavefront of the beam received by the front analyzer. wavefront and a reference wavefront to determine an intermediate wavefront error. For example, the reference wavefront corresponds to the wavefront of a light beam emitted by the transmitter and received by the wavefront analyzer, without passing through the glazing or any other diopter. [00125] Step 106 of generating a wavefront error map is implemented by the microprocessor of the wavefront analyzer. [00126] Step 106 of generating an error map may include a sub-step 1062 of dividing the intermediate error map by two. Indeed, to the extent that the beam crosses the given zone 13 of the glazing twice, a first time during the emission of the beam by the transmitter and a second time during the reflection of the beam by the plane mirror, the The intermediate wavefront error determined in substep 161 corresponds to the wavefront error resulting from the two passages of the beam through the given zone 13 of the glazing. Thus, sub-step 1062 makes it possible to determine the wave front error corresponding to a single passage of the beam through the given zone 13. Naturally, the division sub-step 1062 is not carried out when the dividing device measurement does not include a plane mirror and that the transmitter and the wavefront analyzer are placed on either side of the glazing. Indeed, in this case the intermediate wavefront error calculated during the calculation sub-step 1061 corresponds to the wavefront error relating to a single passage of the beam through the given zone 1313. 00127] The method 100 further comprises a step 107 of calculating from the wavefront error map, at least one map of optical defects present in the given zone 13 and a step 108 of determining at least one quality indicator relating to the optical defect map. [00128] The block diagram detailing examples of embodiments of step 107 is shown in [Fig.9]. [00129] The block diagram detailing examples of embodiments of step 108 is shown in [Fig.9]. [00130] According to one embodiment, the optical defect map is a map from at least the following list: an optical aberration map, a slope or deflection map, a map of the point spread function, a modulation transfer function map, a vertical distortion map and/or a horizontal distortion map. [00131] According to an embodiment in which a single optical defect map is calculated, the optical defect map is a map from at least the following list: an optical aberration map, a slope or deflection map, a point spread function map, a modulation transfer function map. [00132] According to one embodiment, the optical defect map is directly the wavefront error map. [00133] According to one embodiment, a plurality of at least two different optical defect maps are calculated and are chosen from an optical aberration map, a slope or deflection map, a spreading function map point, a modulation transfer function map, a vertical distortion map and/or a horizontal distortion map. [00134] In particular, according to an embodiment in which at least two optical defect maps are calculated, a first optical defect map is a distortion map chosen from a vertical distortion map and a horizontal distortion map. The second optical defect map is a map of the modulation transfer function of the given zone 13 of the glazing. [00135] According to one embodiment, step 107 of calculating the optical defect map includes substeps 1071 and 1072 described below. [00136] Substep 1071 is a step of creating a binary mask, the binary mask being a matrix of the same size as the wavefront error map. [00137] The binary mask includes the same number of coefficients as the wavefront error map. Each coefficient of the binary mask whose index corresponds to a coefficient of the error map of the non-zero wavefront is equal to the same first binary information 0 or 1. Each coefficient of the binary mask whose index corresponds to a wavefront error map coefficient zero is equal to the same second binary information 1 or 0 complementary to the first binary information. [00138] Substep 1072 is a step of applying a morphological erosion filter to the binary mask to obtain a filtered binary mask. [00139] According to the embodiment in which the optical defect map is a horizontal distortion map or a vertical distortion map, the optical defect map is calculated from the wavefront error map and from the filtered binary mask. [00140] According to the embodiment in which the optical defect map is a vertical distortion map, the step 107 of calculating the optical defect map comprises the substeps 107-1 to 107-11 described below . [00141] Sub-step 107-1 is a sub-step of creating a so-called result matrix of size equal to the binary mask or the error map of the wavefront (the binary mask and the map of 'error having the same size). The coefficients of the result matrix are preferably NaN values (from English “Not a Number”). [00142] Substep 107-2 is a substep of determining a first gradient matrix representing the vertical gradient of the wavefront error map. [00143] The sub-step of determining the first gradient matrix is carried out from the wavefront error map and includes a plurality of sub-steps 107-3, 107-4, 107-5, 107- 6, 107-7 described in the rest of the editorial. Substep 107-3 of the substep of determining the first gradient matrix is a step of creating a matrix G1 of the same size as the wavefront error map. [00145] In particular, substeps 107-4 to 107-7 are carried out for each line i of the wavefront error map. [00146] For each line i of the wavefront error map, substep 107-4 is a step of recovering the index p of the first coefficient of said line i which is not equal to a NaN value, p being an integer and the index d of the last coefficient of said line which is not equal to a NaN value. It is possible that the line does not include any NaN value, in this case, p represents the index of the first coefficient of the line and d represents the index of the last coefficient of the line. Substep 107-4 is carried out using the binary mask, making it possible to distinguish the coefficients of the wavefront error map different from NaN. [00147] Substep 107-5 is a step of subtracting the coefficient of line i of index p+1 from the coefficient of index p, the difference obtained being stored at the coefficient of index p of line i of the G1 matrix. [00148] Substep 107-6 is a step of storing the index p in a variable x. [00149] Substep 107-7 is a step of modifying the coefficients of line i of matrix G1 (or result matrix) according to a condition on the variable x. [00150] Let us denote {gi_j}j≥n the coefficients of line i of matrix G1. [00151] As long as the variable x is strictly less than the index d, substep 17-7 includes a substep 107-7-1 for incrementing the variable x by 1 and modifying the coefficient value gi_x of index x of line i of matrix G1, with gx equal to half the difference between the coefficient of index x+1 and the coefficient of index x-1 of line i of the error map of the wave front. [00152] When the variable x becomes equal to the index d, the substep 107-7 includes a substep 107-7-2 of modifying the coefficient _{gi_} matrix G1, with gi_ _x equal to the difference between the index coefficient x-1 and the index coefficient x of the wavefront error map. [00153] Matrix G1 is the first gradient matrix. [00154] Substep 107-8 is a substep of determining a second gradient matrix representing the horizontal gradient of the first gradient matrix. [00155] Substep 107-8 of determining the second gradient matrix comprises the same substeps as substep 107-7 of determining the first gradient matrix, the wavefront error being in this case replaced by the first gradient matrix G1. [00156] The step of calculating the vertical distortion map further comprises a substep 107-9 of multiplying all the values of the second matrix ^.^ of gradient by the term (^∗^^ ^{^^} )² to obtain a second modified gradient matrix. [00157] The term X represents the size of a pixel of the wavefront analyzer, and is preferably 295 microns. [00158] The step of calculating the vertical distortion map further comprises a substep 107-11 of applying a Gaussian filter to the second modified gradient matrix to obtain a second filtered gradient matrix. The Gaussian filter has the parameter σ, the parameter σ representing the standard deviation of the Gaussian distribution. Preferably, σ is between 1 and 100. [00159] The second filtered gradient matrix represents the vertical distortion map. [00160] When the calculated optical defect map is a vertical distortion map, step 108 of determining at least one quality indicator relating to the distortion map may include a substep 1081 of extracting the coefficient of maximum value and the minimum value coefficient of the horizontal distortion map and calculation of the difference between said maximum value and said minimum value, said difference being commonly called "Peak to Valley". [00161] The maximum value coefficient, the minimum value coefficient and the Peak to Valley are quality indicators. The Peak to Valley is an absolute measurement in the worst case of the irregularities of an optical surface and in this case of the given zone 13. [00162] When the calculated optical defect map is a horizontal distortion map, the step 108 for determining at least one quality indicator relating to the distortion map may further comprise a sub-step 1082 for calculating the root mean square value of the second filtered gradient matrix, more commonly called RMS (Root Mean Square). in English. Let {x _i } _{i≥n denote} the coefficients of the second gradient matrix, with n the number of coefficients. The root mean square value of the second filtered gradient matrix is given by the following formula: ^^ ^{^} _^ ^^ ^{^} _^ ^⋯^^ ^{^ ^} _^ ^

[00164] The RMS is a quality indicator, making it possible to quantify the irregularities of an optical surface and in this case of the given zone 13 of the glazing. [00165] According to the embodiment in which the optical defect map is a horizontal distortion map, the step of calculating the optical defect map comprises the same substeps 107-1 to 107-11 described previously, with in particular steps 107-4 to 107-7 applied to the columns of the wavefront error map and not to the rows. [00166] According to the embodiment in which the optical defect map is the wavefront error map, step 108 of determining a quality indicator relating to the distortion map may further comprise in in addition to a sub-step 1083 of extracting the maximum value coefficient and the minimum value coefficient from the wavefront error map and calculating the difference between said maximum value and said minimum value to obtain the "Peak to Valley.” [00167] The maximum value coefficient, the minimum value coefficient and the Peak to Valley are quality indicators. [00168] When the calculated optical defect map is a horizontal distortion map, the step 1084 of determining at least one quality indicator relating to the distortion map may further comprise a sub-step 1084 of calculating the mean square value of the second filtered gradient matrix, more commonly called RMS (Root Mean Square) in English. [00169] Let us denote {x _i } _i≥n the coefficients of the wavefront error map, with n the number of coefficients. The root mean square value of the second filtered gradient matrix is given by the following formula: ^^ ^{^} _^ ^^ ^{^} _^ ^⋯^^ ^{^ ^} _^ ^

[00171] As described previously, the RMS is a quality indicator, making it possible to quantify the irregularities of an optical surface and in this case of the given zone 13 of the glazing. [00172] According to the embodiment in which the optical fault map is a modulation transfer function map, the modulation transfer function map represents data relating to the modulation transfer function. modulation of the given area 13 and the step of calculating the modulation transfer function map comprises substeps 107-12 to 107-33 described below. [00173] The modulation transfer function makes it possible to obtain a quantitative description of the image quality of an optical surface, in this case the given zone 13 of the glazing, by considering all the optical aberrations of the given zone 13. The modulation transfer function of the given zone 13 of the glazing makes it possible to evaluate the capacity of the given zone 13 of the glazing to reproduce different details of an observed scene. [00174] Sub-step 107-12 of the step of calculating the modulation transfer function is a sub-step of calculating the diameter D of the exit pupil of the given zone 13, included in the given zone 13 , to analyze. The diameter D of the pupil is calculated from an effective focal distance f' image of all the optics of the image acquisition device 20 (for example the objective of the image acquisition device 20) , the width of a pixel of a sensor included in the image acquisition device 20 and the aperture number of the image acquisition device 20. The diameter D is given by the following formula: ^ ^[00175]D=^. [00176] Sub-step 107-13 of the step of calculating the modulation transfer function is a sub-step of extracting a matrix comprising the pixel values corresponding to the exit pupil in the given zone 13, from the calculated diameter D and coordinates determined by an operator. [00177] Sub-step 107-14 of the step of calculating the modulation transfer function is a sub-step of creating an MTF2D matrix whose size is equal to three times the size of the matrix of the exit pupil extracted. Sub-step 107-15 of the step of calculating the modulation transfer function is a sub-step of copying the coefficients of the pupil to the center of the matrix MTF'. [00179] Let us note in the sequence {yi}i≥n the non-zero coefficients of the MTF2D matrix. [00180] Sub-step 107-16 of the step of calculating the modulation transfer function is a sub-step of replacing, in the MTF matrix, each coefficient yi by ^ ^{^^ ∗^ ∗^∗^ ^} . [00181] Sub-step 107-17 of the step of calculating the modulation transfer function is a sub-step of applying an inverse transform to the MTF matrix. [00182] The new coefficients of the MTF2D matrix at the end of substep 107-17 are denoted {y'i}i≥n [00183] Substep 107-18 of the step of calculating the modulation transfer function is a sub-step of replacing each coefficient y'i of the _2D MTF matrix by |y′i|². [00184] Sub-step 107-19 of the step of calculating the modulation transfer function is a sub-step of normalization of the MTF2D matrix. [00185] Sub-step 107-20 of the step of calculating the modulation transfer function is a sub-step of applying a Fourier transform to the MTF2D matrix. [00186] The new coefficients of the _2D MTF matrix at the end of substep 17-23 are denoted {y'' _i } _i≥n [00187] Substep 107-21 of the calculation step of the modulation transfer function is a sub-step of replacing each coefficient y''i of the MTF2D matrix by ^| y′′i ^| . The new coefficients of the MTF2D matrix are thus denoted mi = ^| y′′i ^| . [00188] Sub-step 107-22 of the step of calculating the modulation transfer function is a sub-step of creating a Diffraction Limit matrix whose size is equal to three times the size of the pupil extracted. [00189] Sub-step 107-23 of the step of calculating the modulation transfer function is a sub-step of copying the coefficients of a binary mask of the pupil at the center of the Diffraction Limit matrix. [00190] Let us note in the sequence {ai}i≥n the non-zero coefficients of the Diffraction Limit matrix. [00191] Sub-step 107-24 of the step of calculating the modulation transfer function is a sub-step of replacing, in the MTF matrix, each coefficient a _i by ^ ^{^^ ∗^ ∗^∗ ^^} . [00192] Sub-step 107-25 of the step of calculating the modulation transfer function is a sub-step of applying an inverse transform to the Diffraction Limit matrix. [00193] The new coefficients of the Diffraction Limit matrix at the end of sub-step 17-25 are denoted {a'i}i≥n [00194] Sub-step 107-26 of the calculation step of the modulation transfer function is a sub-step of replacing each coefficient a'i of the Diffraction Limit matrix by |a′i|². [00195] Sub-step 107-27 of the step of calculating the modulation transfer function is a sub-step of normalization of the Diffraction Limit matrix. [00196] Sub-step 107-28 of the step of calculating the modulation transfer function is a sub-step of applying a Fourier transform to the Diffraction Limit matrix. [00197] The new coefficients of the Diffraction Limit matrix at the end of sub-step 17-29 are denoted {a'' _i } _i≥n [00198] Sub-step 17-30 of the step of calculation of the modulation transfer function is a sub-step of replacing each coefficient a''i of the Diffraction Limit matrix by ^| a′′i ^| . The new coefficients of the Diffraction Limit matrix are thus denoted ni = ^| a′′i ^| . The Diffraction Limit matrix represents the transfer function of the given zone 13 in the absence of aberrations on the given zone 13 of the glazing. [00199] According to one embodiment, the step of calculating the map of the modulation transfer function comprises a substep 17-31 of calculating a map of the modulation transfer function reduced in two dimensions. [00200] The sub-step of calculating a modulation transfer function consists of creating a reduced MTF2D matrix of the same size as the MTF2D matrix (or the Diffraction Limit matrix, the two matrices having the same size) each of which ^^ coefficient is equal to the term (1- in the case where ni is different from 0, and by 0 in the case where ni = 0. The matrix

represents the reduced modulation transfer function in two dimensions. [00201] According to one embodiment, the step of calculating the map of the modulation transfer function comprises a sub-step 107-32 of calculating a map of a horizontal cut of the reduced modulation transfer function. Sub-step 107-32 is carried out by extracting the central line of the MTF matrix and the central line of the Diffraction Limit matrix, representing respectively the horizontal section of the modulation transfer function of the given zone 13 and the function modulation transfer of the given zone 13 in the absence of aberrations. Let {mi} i≥m denote the coefficients of the central line of the MTF matrix and {ni} i≥m the coefficients of the central line of the Diffraction Limit matrix. Substep 107-32 is further carried out by creating a _{reduced horizontal-cut} MTF matrix of the same size as the central line of the MTF matrix (or the Diffraction Limit matrix, the two matrices having the same size) each of which ^^ coefficient is equal to the term (1- in the case where ni is different from 0, and by 0 in the case where ni = 0.

[00202] According to one embodiment, the step of calculating the map of the modulation transfer function comprises a sub-step 107-33 of calculating a map of a vertical section of the modulation transfer function scaled down. The sub-step includes the same steps as sub-step 107-32 but applied to the columns and not to the rows in this case, to obtain a reduced MTF_verticalcut matrix. [00203] Thus, in the embodiment in which the optical defect map is a modulation transfer function map, the modulation transfer function map comprises or is equal to at least one matrix among the following: _2D MTF, _{reduced MTF2D,} _{reduced MTF_horizontalcut} and _{reduced MTF_verticalcut.} [00204] When the calculated optical fault map is a modulation transfer function map, step 108 of determining at least one quality indicator relating to the modulation transfer function map may further comprise a sub -step 1085 of calculating a term relating to the horizontal Nyquist frequency f _NH and/or a term relating to the vertical Nyquist frequency f _NV . [00205] The term relating to the horizontal Nyquist frequency f _NH is the quality indicator and may be equal to the horizontal Nyquist frequency fNH or may be equal to the half-horizontal Nyquist frequency fNH/2. [00206] The term relating to the vertical Nyquist frequency fNV is the quality indicator and can be equal to the vertical Nyquist frequency f _NV or the half-vertical Nyquist frequency f _NV /2. [00207] The Nyquist frequency (horizontal or vertical) is the highest spatial frequency at which a digital sensor can capture real information, any information higher than the Nyquist frequency which reaches the sensor is aliased to lower frequencies, thus creating potentially distracting moiré patterns. In general, the horizontal (respectively vertical) Nyquist frequency f _N is calculated from the following formula f _N = 0.5 cycles/pitch_pixel, the pitch_pixel value corresponding to the horizontal (respectively vertical) distance separating the centers of two pixels of the device image acquisition 20. [00208] The Nyquist frequency or a parameter relating to the Nyquist frequency is a quality indicator. [00209] Depending on the embodiment in which the image acquisition device 20 is a LIDAR, the optical defect map calculated in step 107 may be a horizontal deflection map and/or a vertical deflection map. The horizontal deflection map corresponds to the deviation of the wavefront by the first part of the given zone 13 and by the second part of the given zone 13. [00210] According to an embodiment compatible with the previous embodiment, the step 108 of determining a quality indicator relating to the optical defect map, which is for example the horizontal deflection map, may include a step of calculating a pointing error following the horizontal field of view of the LIDAR from said horizontal deflection map. The pointing error corresponds to the absolute difference between an average deflection of the first part and between an average deflection of the second part. In this case, the quality indicator is the pointing error and is preferably less than 150 µrad, in particular less than 100 µrad and preferably less than 50 µrad. [00211] According to an embodiment compatible with the previous embodiment, step 108 of determining a quality indicator relating to the optical defect map which is for example the vertical deflection map, can comprise a step of calculating a pointing error following the vertical field of view of the LIDAR from said vertical deflection map. The pointing error corresponds to the absolute difference between an average deflection of the first part of the given zone 13 and between an average deflection of the second part of the given zone 13. In this case, the quality indicator is pointing error and is preferably less than 150 µrad, in particular less than 100 µrad and preferably less than 50 µrad. [00212] The method 100 may further comprise a step 109 of displaying the optical defect map calculated in step 107. According to the embodiment in which a plurality of optical defect maps are calculated, the plurality of maps optical faults is displayed. [00213] The method 100 may further comprise a step 110 of displaying each quality indicator relating to the optical defect map determined in step 18. According to the embodiment in which a plurality of optical defect maps are calculated, at least one quality indicator per optical defect map is displayed. [00214] According to one embodiment, only one of the steps 109 or 110 of the method 100 is carried out. [00215] According to another embodiment, the two steps 109 and 110 of the method 100 are carried out. [00216] According to the embodiment in which at least two optical defect maps are calculated, and according to which a first defect map is a vertical distortion map or a vertical distortion map, and the second defect map is a map of the modulation transfer function, and according to which the quality indicators relating to each fault map are qualities, the method 100 may comprise a step 111 of comparing the two optical fault maps and/or their fault indicators. [00217] The method 100 further comprises a step 112 of characterizing the optical quality of the given zone 13 by comparing each quality indicator relating to the optical defect map to a predetermined threshold. [00218] For example, the predetermined threshold corresponds to a reference value of the quality indicator or a value of a quality indicator different from the quality indicator considered. [00219] According to one embodiment of the invention, the characterization step 112 is further carried out by comparing the calculated optical defect map to a reference optical defect map of the same type as the calculated optical defect map , the reference optical defect map representing the optical behavior of the given zone 13 in the theoretical/ideal case where it is devoid of optical aberrations. The comparison between the calculated optical defect map and the reference optical defect map can be visual. [00220] According to the embodiment in which step 111 is carried out, characterization step 112 is further carried out from the comparison of the two calculated optical maps and/or their optical indicators. [00221] For example, during the characterization step 112, an operator can receive an alert in real time if the quality indicators relating to one or more optical defect cards exceed predetermined thresholds, an operator can receive a specific alert concerning the glazing considered, each predetermined threshold being specific to a quality indicator. [00222] For example, during the characterization step 112, an operator can receive an alert in real time if the quality indicators relating to one or more optical defect cards are lower than predetermined thresholds, an operator can receive an alert. particular alert concerning the glazing considered, each predetermined threshold being specific to a quality indicator. [00223] According to one embodiment, the glazing is associated with a unique identifier. [00224] The method 100 may further comprise a step 113 of reading the identifier of the glazing by the characterization system. [00225] The method 100 may further comprise a step 114 of storing in a memory, for example the memory of the digital device, the identifier associated with the glazing and the optical quality of the given zone 13 of the glazing determined during the step 112. [00226] The method 100 may further comprise a step 115 of association in the memory of the stored identifier and the stored optical quality. [00227] The method 100 may further comprise a step 116 of storing in the memory the optical fault map associated with the glazing and a step 117 of associating in the memory the identifier of the stored glazing and the fault map stored optics. According to the embodiment in which a plurality of optical defect maps are calculated, the plurality of optical maps are stored and associated with the glazing identifier. [00228] At least steps 103, 107, 109, 110, 111, 112, 113, 114, 115 are implemented according to a programming language capable of executing said steps in a period strictly less than the predetermined period. [00229] For example, the programming language is C#. According to one embodiment, C# uses, thanks to a “wrapper library” called “OpenCVSharp”, the C++ functions of OpenCV.

Claims

CLAIMS [Claim 1] Method (100) for characterizing the optical quality of a given zone (13) of a vehicle glazing (10) of a plurality of vehicle glazings of a glazing production line, the given area (13) of the glazing being intended to be positioned in the optical path of an image acquisition device (20), the characterization method (100) being carried out during a period less than or equal to a predetermined period of operation of the production line, before the arrival of the glazing following the glazing whose given zone (13) is characterized on the production line, according to the following steps: - Detection (102) of the presence of the glazing; - Detection (104) of the given area (13) of glazing in an area of the glazing covered by a wavefront analyzer and comprising the given area (13); - Acquisition (105) of the wavefront of the given area (13) and generation (106) of a wavefront error map; - Calculation (107) from the wavefront error map of at least one map of optical defects present in the given zone (13) and determination (108) of at least one relative quality indicator to the optical defect map; - Characterization (112) of the optical quality of the given zone (13) by comparison of each quality indicator relating to the optical defect map at a predetermined threshold. [Claim 2] Method (100) according to the preceding claim characterized in that it comprises, before the step of characterizing the optical quality of the given zone (13), the following steps: - display (109) of the map of optical defects; and/or - display (110) of the optical quality indicator indicator relating to the optical fault map. [Claim 3] Method (100) according to any one of the preceding claims characterized in that it comprises, between the step of detecting the presence of the glazing and the detection of the given zone (13), an acquisition step of the wavefront of the area of the glazing covered by the wavefront analyzer. [Claim 4] Method (100) according to claim 3, characterized in that the step (104) of detecting the given zone (13) of the glazing comprises the following sub-steps: - Generation (1041), from the wave front acquired from the area covered by the wave front analyzer, an image of an interferogram of the area of the glazing covered by the wave front analyzer, the area of the glazing covered by the the waveform analyzer comprising a plurality of sub-zones including the given zone (13); - Thresholding (1042) of the interferogram image to obtain a first image; - Application (1043) of a morphological aperture filter on the first image to obtain a second image, - Detection (1044), on the second image, of the contour of each sub-zone of the area of the glazing covered by the wavefront analyzer: oWhen the number of detected contours is non-zero: 1. Determination (10441), for each contour, of the rotating rectangle of minimum area comprising said contour to obtain a set of rectangles; 2. Selection (10442), among all the rectangles, of the rectangles included in a predefined zone, if at least one rectangle is selected: a. Selection (104421) of the rectangle of maximum area among the at least one rectangle selected, b. Recovery (104422) of the coordinates of the pixels forming the contour included in the rectangle of maximum area, c. From the coordinates of the pixels recovered, calculation (104423) of a polygonal shape corresponding to an approximation of the contour included in the rectangle of maximum area, the calculated polygonal shape representing the given area (13) of the glazing, - if no contour is selected, determination (1045) on the second image of a polygonal shape corresponding to a predefined zone, the polygonal shape representing the given zone (13) of the glazing. [Claim 5] Method (100) according to any one of the preceding claims, characterized in that said method (100) for characterizing the given zone (13) is implemented by a characterization system comprising a beam emitter of light rays and the wavefront analyzer and in that the step (106) of generating the wavefront error map comprises the following substep: - calculation (1061) of a difference phase between the wave front of the light rays transmitted by said given area (13) of the glazing and a reference wave front to determine a wave front error used to generate the wave front error map waves. [Claim 6] Method (100) according to any one of the preceding claims characterized in that the optical defect map is chosen from the following list: - an optical aberration map, - a slope or deflection map, - a map of the point spread function - a map of the modulation transfer function, - a vertical distortion map and/or a horizontal distortion map. [Claim 7] Method (100) according to any one of the preceding claims characterized in that at least two optical defect maps are calculated and in that: - a first optical defect map among the at least two defect maps optical is a distortion map chosen from a vertical distortion map and a horizontal distortion map, and - a second optical defect map among the at least two optical defect maps is a map of the modulation transfer function, the method (100) being further characterized in that it comprises, before the characterization step, a step of comparing (111) the first optical defect map and the second optical defect map and in that the characterization of the optical quality of the given area (13) is implemented from the comparison step. [Claim 8] Method (100) according to the preceding claim characterized in that the step of detecting the given zone (13) of the glazing further comprises a sub-step of displaying (1046) the given zone (13) glazing. [Claim 9] Method (100) according to any one of the preceding claims characterized in that the wavefront error map is a matrix and in that the step of calculating (107) at least one map of optical defects comprises the following sub-steps: - Creation (1071) of a binary mask, the binary mask being a matrix of the same size as the wavefront error map and in which: oEach coefficient whose index corresponds to a coefficient of the error map of the non-zero wave front and is equal to the same first binary information 0 or 1; oEach coefficient whose index corresponds to a coefficient of the zero wavefront error map is equal to the same second binary information 1 or 0 complementary to the first binary information; - Application (1072) of a morphological erosion filter on the binary mask, and characterized in that the optical defect map is also calculated from the binary mask. [Claim 10] Method (100) according to any one of the preceding claims characterized in that the step of detecting (104) the given zone (13), the step of calculating (107) the optical defect map from the wavefront error map and the step of determining (108) the at least quality indicator are implemented according to a programming language capable of executing said steps in a period strictly less than the predetermined period. [Claim 11] Method (100) according to any one of the preceding claims, characterized in that the vehicle is a road or rail vehicle. [Claim 12] Method (100) according to any one of the preceding claims characterized in that the predetermined period of operation of the production line is less than 20 seconds inclusive, in particular less than 15 seconds inclusive and preferably less than 12 seconds inclusive . [Claim 13] Method (100) according to any one of the preceding claims characterized in that the glazing among the plurality of glazings of the glazing production line comprises a marking associated with an identifier, the identifier being uniquely associated to the glazing, the method (100) further comprising the following steps: - reading (113) of the identifier by the characterization system, - storage (114) in a memory, of: o the identifier associated with the glazing, o the optical quality of the given area (13) of the glazing determined during the characterization step, - association (115) in the memory of the stored identifier and the stored optical quality. [Claim 14] Method (100) according to the preceding claim characterized in that the method (100) further comprises the following steps: - storage (116) in the memory of the calculated optical defect map, - association (117) in the memory of the stored identifier and the stored optical fault map. [Claim 15] System for characterizing (40) the optical quality of at least one given zone (13) of glazing comprising means configured to implement the method (100) according to any one of claims 1 to 14. [Claim 16] Computer program product comprising program code instructions recorded on a medium usable in a computer, comprising: - computer-readable programming means for carrying out the step of detecting (104) the area data (13) according to claim 1, - computer-readable programming means for carrying out the calculation step (108) from the wavefront error map of at least one optical defect map and for determining (108) at least one quality indicator relating to the optical defect map according to claim 1, - computer-readable programming means for carrying out the step of characterizing (112) the optical quality of the zone data (13) according to claim 1; when said program runs on a computer.