METHOD FOR QUANTIFYING BURNS GENERATED BY GRINDING A PART

Abstract

The invention relates to a method (100) for quantifying burns generated by grinding a part (10), the method comprising at least: - a step (110) of acquiring images I i, i integer, of at least one zone (S1) of the part (10) to be observed on a background (12) by means of an apparatus (20) comprising an observation device (22) provided with an image sensor (24) and a light source (26) capable of illuminating the part (10), said acquisition apparatus (20) being configured to acquire images in N gray levels k, k = [0…N], N integer, each gray level being associated with a gray value gk, each image I i comprising a first series of pixels associated with the part (10) and a second series of pixels associated with the background (12), - a step (120) of processing the images acquired during the image acquisition step (110), - a step (130) of calculating the surface burn rate ρ on the part (10). Figure for the abstract: Fig. 1

Description

Title of the invention: METHOD FOR QUANTIFYING BURNS GENERATED BY GRINDING A PART Technical field of the invention

[0001] The invention relates to the technical field of methods for quantifying burns generated by grinding a part, in particular made of titanium or titanium alloy, by digital image analysis. Technical background

[0002] Many techniques are known for quantifying the burns of a part that has undergone grinding. Grinding is a machining process during which material is removed using a grinding wheel in order to give a part a desired shape and dimensions, and thus to modify its surface condition. This grinding process is widely used in the aeronautics field to machine (among other things) titanium or titanium alloy parts. On the other hand, the heating generated during grinding can lead to a metallurgical change in the titanium or titanium alloy commonly called "burning".

[0003] Burn detection on titanium or titanium alloy parts is generally carried out by immersion in a nitro-hydrofluoric bath. On this type of part, grinding typically generates local changes in the material properties, because titanium is a material with low thermal conductivity. Thus, during the grinding process of a titanium or titanium alloy part, local heating generally occurs which has the effect of generating a phase change in the material which is the cause of local changes in the mechanical properties of the part. These local changes in the properties of the part are burns. They are likely to weaken the part and reduce its service life. They are identifiable by the presence of dark spots on its surface after nitro-hydrofluoric attack.

[0004] Avoiding the generation of burns during grinding on titanium or titanium alloy parts is complex and not very industrial. It is therefore necessary to quantify the rate of burned surface in order to deduce the influence on the mechanical properties of the part. The quantification of these burns is essential to confirm that the requirements in terms of accepted anomaly rates are verified, and thus confirm that the state of the part corresponds to the use to be made of it. This quantification is conventionally carried out by a visual analysis of the images. In the methods of quantifying burns known from the prior art, the quantification is carried out by comparison with typical images, which makes it subjective because it depends on the analysis and experience of the operator, as well as the working environment.

[0005] According to a first method well known from the prior art, the operator observes the part by means of an observation device, then compares the surface of the rectified part to the typical images in order to conclude on the conformity or not of the part. This technique is however not precise because it is subject to the subjective analysis and experience of the operator. The level of acceptance of the parts can therefore be high due to the lack of experience of the operator and / or lack of objectivity in the analysis technique.

[0006] A second image analysis technique has therefore been developed to enable more precise quantification of the burns generated by grinding the part. It consists of acquiring an image of the ground part in intensity levels on a gray scale and dividing the image into three gray intensity levels. Although this method is more precise than the method described previously, it is also subject to the analysis and experience of the operator. Indeed, it is not possible to use the same gray levels for all the images analyzed because the lighting conditions of the part and the environment in which the part is located fluctuate. Thus, a gray level can, depending on the lighting conditions and the environment of the part, just as easily be associated with a gray level characteristic of a burn as it can be associated with a gray level characteristic of an absence of burn.The operator must therefore readjust the gray levels for each image, which makes the process of quantifying burns using this second method non-repeatable.

[0007] In a third method known from the prior art, a first step consists of acquiring a color image, i.e. in intensity levels on an RGB scale, i.e. red-green-blue, of the part with fixed acquisition parameters, a second step consists of defining an analysis zone, a third step consists of performing thresholding and a fourth step consists of filtering the zones associated with anomalies. If this method effectively takes into account burns, it also quantifies the anomalies generated by scratches and all other anomalies present on the surface. This method therefore requires the analysis of the operator with regard to the choice of the filter to be applied during image processing and is therefore not objective.

[0008] The burn quantification techniques previously stated all depend on the operator's level of expertise, and are also highly dependent on the environment in which the part is located.

[0009] The invention aims to overcome at least some of the aforementioned problems and proposes in this regard a method for quantifying the burns generated by rectification of a part that is repeatable, precise and little or not dependent on the operator's level of expertise. Summary of the invention

[0010] The invention proposes for this purpose a method for quantifying the burns generated by grinding a part comprising at least one area to be observed, the method comprising at least:

[0011] - a step of acquiring images of the area to be observed on a background by means of of an apparatus comprising an observation device equipped with an image sensor and a light source capable of illuminating the room, said acquisition apparatus being configured to acquire images in N gray levels k, k = [0.. .N], N integer, each gray level being associated with a gray value gk, each image I; comprising a first series of pixels associated with the zone SI to be observed and a second series of pixels associated with the background,

[0012] - a step of processing the images acquired during the image acquisition step,

[0013] - a step of calculating the surface burn rate p on the area to be observed, said processing and calculation steps being implemented by computer,

[0014] the method being characterized in that the image acquisition step comprises:

[0015] - a first sub-step of positioning the part between the image sensor and a screen such that the image sensor, the part, and the screen are aligned in this order, said screen having a matte surface having a gray value corresponding to a reference black g0 and located opposite the part,

[0016] - a second sub-step of adjusting the exposure time Texp and the intensity Iexp of the light source at predetermined values, as well as the magnification level G of the image,

[0017] - a third sub-step in which a gray value gBc is changed from one gray level, called target white, from a maximum gN to a first intermediate gray value gkl between the reference black g0 and the maximum gN without including these values,

[0018] - a fourth sub-step in which a histogram is produced representing the number of pixels Q k, Q integer, as a function of the gray level k and we adjust the intensity Iexp of the light source so that the gray value gpic to which is associated the maximum number of pixels Q max detected by the acquisition device corresponds to the first intermediate gray value gk[ defined during the third sub-step,

[0019] - a fifth sub-step in which the target blank gBc is passed from the first intermediate gray value gkl to maximum gN and we acquire a first image L,

[0020] - a sixth sub-step in which the third, fourth and fifth sub-steps for second and third intermediate gray values ​​gk2, gk3 distinct from each other and distinct from the first intermediate gray value gkl so as to obtain a second image I2 and a third image I3 respectively,

[0021] in that the image processing step comprises a sub-step during which, for each of the first, second and third images 1;, 12 and 13, a thresholding of the first series of pixels is carried out so as to identify a third series of pixels associated with the burns, and in that, the surface burn rate p on the zone to be observed corresponds to the ratio R of an average of the areas of the third series of pixels associated with the burns in the first series of pixels of the first, second and third images 1 j, 12 and 13 on an average of the areas of the pixels of the first series of pixels in the first, second and third images 1 j, 12 and 13.

[0022] The method according to the invention makes it possible to objectify the quantification of the burns generated by grinding the part since the calculation of the surface burn rate is based on an objective approach during the acquisition of images. Indeed, the lighting parameters of the part, namely the exposure time and the intensity of the light source, are fixed, so that the impact of the environment and the ambient lighting of the place where the part is located on the reflections and the rendering of the part are considerably reduced. Thus, the phenomenon of variability of the gray levels as a function of the parameters of the environment observed in the methods of the prior art is considerably reduced in the method according to the invention. This makes it possible to carry out the acquisition of images on the basis of a controlled environment and therefore makes it possible to improve the repeatability of the image acquisition.

[0023] Furthermore, the acquisition of the first, second and third images at the three fixed intermediate gray values ​​makes it possible to discriminate burns from other anomalies that can be observed on the surface of the part and to retain as a basis for the calculation only the anomalies corresponding to the surface burns generated during the grinding of the part. The image acquisition step of the method according to the invention therefore sets up a precise protocol which substantially improves the reliability of the quantification of the surface burn rate. The fact of using the same intermediate gray values ​​for each part analyzed makes the method according to the invention objective because it no longer depends on the assessment and experience of the operator, unlike what is currently implemented in the methods of the prior art.

[0024] Furthermore, the method according to the invention can be implemented with standard means. Indeed, the method uses an observation device, a sensor of images, a light source and a computer. In addition, the image acquisition protocol implemented in the method according to the invention only uses common means of image acquisition and visualization software used in devices on the market since, notably, it essentially requires the creation of a histogram. It is therefore simple and quick to implement.

[0025] According to different characteristics of the invention which can be taken together or separately: - the number of gray levels N is equal to 256, the maximum gN being equal to 255, the first gkb second gk2 and third gk3 intermediate gray values ​​being between 110 and 140; - the first intermediate gray value gkl is equal to 110, the second intermediate gray value gk2 is equal to 130 and the third intermediate gray value gk3 is equal to 140; - the second processing step includes a first masking sub-step in which: • a mask corresponding to a binary image is generated in which the pixels of the areas of interest of the first series of pixels have a first binary value equal to 1 and the rest of the pixels have a second binary value equal to 0, • the mask is applied to the first, second and third images 1, 12 and 13 so as to obtain a second series of images I1M, I2M and I3M comprising only the areas of interest of the first series of pixels; - the second processing step comprises, following the first masking sub-step, a second contrast adjustment sub-step by applying the CLAHE method to the second series of images I1M, I2M and I3M; - the thresholding sub-step is performed by applying the Otsu method; - the thresholding sub-step is implemented after the second sub-step contrast adjustment - in the second adjustment sub-step of the image acquisition step, the sharpness of the image f, the dimensions of the image and / or the resolution of the image sensor are further adjusted; - the observation device is a binocular, the image sensor is a CCD camera and the light source is a ring of LEDs; - the part is a titanium or titanium alloy part machined by grinding. Brief description of the figures

[0026] Other objects, characteristics and advantages of the invention will appear more clearly in the description which follows, made with reference to the appended figures, in which:

[0027] - [Fig.l] is a schematic view illustrating the different stages of a process according to the invention,

[0028] - [Fig.2] is a schematic view illustrating the different stages of a process according to an exemplary embodiment of the invention,

[0029] - [Fig.3] is a schematic view illustrating the different images obtained after sub-steps of the processing step according to an example implementation of the invention,

[0030] - [Fig.4] is a schematic view of an installation for acquiring images according to the acquisition step of the method according to the invention. Detailed description of the invention

[0031] The invention relates to a method 100 for quantifying the burns generated by grinding a part 10. Definitions - general comments

[0032] Throughout the description of the present application, the term grinding designates the machining process during which local heating is generated during the removal of material by means of a grinding wheel on the part in order to give it a desired shape and dimensions. This process is capable of generating a change in the surface condition of the part which, depending on the material from which the part is made, is capable of causing local modifications to the hardness of the part. In the context of the invention, the part 10 is a part whose surface condition has been modified following a grinding process.

[0033] The part 10 for which the burns generated by grinding are to be quantified may be any part, for example a part of an aircraft. This part defined in a three-dimensional space is not limited by its shape, nor by its dimensions, nor by its color, etc. This part 10 comprises an external surface S and at least one zone SI to be observed. The zone SI to be observed may be a specific zone of the part 10 where it is desirable to measure the burn rate. It may also be the entire part of the part 10 that is visible from an observation device 22 and which will be better described below. An exemplary embodiment is illustrated in [Fig.4]. In the context of the invention, the part 10 is preferably made of titanium or titanium alloy. In the case of a titanium alloy, part 10 is predominantly composed of titanium and may include other metals such as aluminum, vanadium, zirconium, molybdenum, chromium, etc.

[0034] As indicated in the preamble to the present description, titanium is a material with low thermal conductivity. The thermal conductivity of titanium is more precisely 20 Wm '.K1, at 20°C, which is more than 11 times lower than the conductivity of aluminum for example. Titanium alloys, for their part, have a thermal conductivity generally between 10 and 30 Wm '.K1, at 20°C. Due to their low thermal conductivities, titanium and titanium alloys respond to local heating by a phase change which is the cause of local modifications of the hardness of the part. These local modifications of the properties of the part 10, called "burns" are likely to weaken the part 10 and reduce its lifetime. They are identifiable by the presence of dark spots on the surface S of the part. The method according to the invention aims to objectively quantify the rate of these burns.

[0035] The grinding of titanium or titanium alloy parts is carried out by means of a rotating grinding wheel carrying out material removal by abrasion. Conventionally, this grinding operation is carried out under lubrication. The surface of the raw part, i.e. of the part before grinding, may be previously prepared mechanically by various methods known to those skilled in the art, such as for example by milling or turning, or prepared chemically by various methods known to those skilled in the art, such as for example cleaning, degreasing, in order to avoid degradation of the properties of the finished part 10, i.e. of the part after grinding, and a significant modification of its physicochemical properties.The use of organic solvents makes it possible to solubilize the majority of greases and oils present on the surface of the part, and therefore to degrease it, which promotes the good holding of the part during the grinding process.

[0036] The revelation of the burns after rectification is carried out by immersing the part in a bath of nitro-hydrofluoric acid. The surface of the part must be previously chemically prepared by various methods known to those skilled in the art, such as for example cleaning, degreasing. In the remainder of this description, the part 10 designates the part after the implementation of the rectification and etching with nitro-hydrofluoric acid.

[0037] Of course, as follows from the above, the invention can be implemented on any part other than a titanium or titanium alloy part that has undergone grinding. Indeed, the method can be applied to any part whose surface condition has been modified by grinding and which has burns. It should nevertheless be specified that the composition of the chemical bath for revealing the burns after grinding can be adapted according to the material of which makes the part. For example, grinding burns on case-hardened steels are revealed by Nital attack (nitric acid and alcohol).

[0038] At this stage, it should be noted that in Figures 1 and 2, the steps associated with dotted rectangles are optional within the scope of the invention. Description of the general embodiment

[0039] With reference to [Fig. 1] and as already indicated previously, the invention relates to a method 100 for quantifying the burns generated by grinding a part 10. The method 100 comprises the following steps:

[0040] - a step 110 of acquiring images 11, i integer, of the zone SI to be observed on a background 12,

[0041] - a step 120 of processing the images acquired during the acquisition step 110 of images,

[0042] - a step 130 of calculating the surface burn rate p on the zone SI to be observed.

[0043] With reference to [Fig.4], the image acquisition step 110 f is implemented by means of an apparatus 20 comprising the observation device 22. The observation device 22 is advantageously a binocular magnifier. The binocular magnifier makes it possible to carry out the observation and acquisition of images I;. In this regard, the binocular magnifier 22 is provided with an image sensor 24 and a light source 26 capable of illuminating the part 10. The binocular magnifier 22 makes it possible to adapt the magnification, the sharpness, the size of the acquisition zone for constant image acquisition. The acquisition zone corresponds at least to the zone SI of the part 10 as well as a part of the environment of the part 10 likely to be, partially or entirely, captured by the image sensor 24.

[0044] The image sensor 24 is preferably a CCD camera, namely a camera using photographic sensors based on a charge-coupled device (Charge Coupled Device). The CCD camera 24 has an acquisition frequency suitable for observing the burns present on the surface S of the part 10. A standard CCD camera capable of acquiring a few images per second is sufficient for implementing the method according to the invention. A camera capable of acquiring several thousand images per second, although more efficient, does not confer more advantages than a standard camera.

[0045] The light source 26 used to illuminate the room 10 and, more generally, the acquisition zone may be a ring of light-emitting diodes or a ring of LEDs (Light Emitting Diodes in English). It allows the brightness and reflections of the room 10 to be precisely controlled, and thus reduces the impact of the light coming from the environment in which the room 10 is located. The lighting may be carried out continuously or in synchronization with the image sensor. 24. When the lighting is used continuously, this allows the frequency of the LED ring to be decorrelated from that of the CCD camera 24.

[0046] Let us now return to [Fig. 1]. Prior to the actual acquisition step 110, a calibration step 105 may be implemented. This calibration step may comprise the calibration of the parameters of the CCD cameras 24. For example, the calibration of the parameters of the CCD camera may be carried out by a white balance.

[0047] The acquisition device 20 is configured to acquire images in N gray levels k,k = [0.. .AQ, N integer, each gray level k being associated with a gray value gk. The gray levels k are advantageously distributed between a minimum gray value, noted g0 and called reference black, and a maximum gray value, noted gN and called maximum. The reference black g0 is so called because it corresponds to the gray level k associated with the darkest shade. Conversely, the maximum gN corresponds to the gray level k associated with an absence of shade or a white.

[0048] In the context of the invention, the gray values ​​gk located between the reference black go and the maximum gN are called intermediate gray values. According to an advantageous embodiment, the number of gray levels A is equal to 256, which makes it possible to carry out image processing by associating a byte with each gray level k. In this case, the gray value associated with the reference black g0 is equal to 0 while the gray value associated with the maximum gN is equal to 255.

[0049] Step 110 of acquiring images according to the invention is described in more detail in the following sections.

[0050] According to a first aspect of the method 100 according to the invention, the image acquisition step 110 comprises a first sub-step 111 of positioning the part 10 between the image sensor 24 and a screen 30 of the apparatus 20 so that the image sensor 24, the part 10, and the screen 30 are aligned in this order. Thus, from the point of view of the image sensor 24, the screen 30 is positioned in the background of the part 10, so that in practice it is identifiable in the background 12 of the images L

[0051] In this regard, in the context of the invention, the screen 30 has a matte surface 31 having a gray value corresponding to the reference black g0 and located opposite the part 10. The screen 30 is therefore not glossy and, in this case, it absorbs at least 70% of the visible light. Due to its matte tone, the screen 30 reflects very little of the incident light, in particular emitted by the light source 26, as will be seen below. The orientation of the surface 31, namely opposite the part 10, and its characteristics, in this case its matte tone and its gray value g0, contribute to better control of the variability of the gray levels in the acquisition zone, and incidentally, in the analysis zone. This also guarantees neutrality colorimetric analysis of the background 12 of the images f acquired by means of the image sensor 24. In addition, since the surface 31 has a gray value corresponding to the reference black g0, it is easy to distinguish and differentiate from the part 10 and the burns in the image obtained at the end of the image acquisition step 110, which facilitates subsequent processing during the image processing step 120.

[0052] According to a second aspect of the method 100 according to the invention, the image acquisition step 110 comprises a second sub-step 112 of adjusting the exposure time T exp and the intensity 1 exp of the light source 26 to predetermined values, as well as the magnification level G of the image.

[0053] The exposure time T exp and the intensity 1 exp of the light source 26 are determined prior to the image acquisition step 110 and applied during the implementation of this step 110, so that the lighting conditions of the room 10 remain stable regardless of the illumination provided by daylight, i.e. the intensity of the daylight. This contributes to better control of the variability of the gray levels in the acquisition zone, and incidentally, in the analysis zone. The impact of daylight is also considerably limited thanks to the predetermined values ​​of T exp and 1 exp. In this regard, it can be noted that the method 100 can advantageously be implemented in a room or hall which is not exposed to daylight.

[0054] The magnification G of the image can be adjusted in order to maximize the presence of the area SI to be observed in the acquired images h and therefore that the background 12 constitutes only a tiny part of the image I;. The adjustment of the magnification G makes it possible to adjust the content of the analysis area. The analysis area corresponds to the part of the acquisition area which is actually captured by the image sensor 24 and which, consequently, becomes an image L Although each image f illustrates the area SI to be observed, it necessarily comprises a part of the background 12 representing the background surrounding the part 10. Each image h therefore comprises a first series of pixels associated with the part 10, in particular with the area SI to be observed, and a second series of pixels associated with the background 12.

[0055] Preferably, each image f comprises at least 60% pixels of the first series of pixels (associated with the area SI to be observed) and less than 40% of pixels of the second series of pixels (associated with the background 12). Even more preferably, each image h comprises at least 80% of pixels of the first series of pixels and less than 20% of the second series of pixels. This makes it possible to better see the area SI to be observed and makes it possible to better identify the burns and other anomalies present on the surface S of the part 10.

[0056] According to a particular implementation, during the second sub-step 112 of adjusting the image acquisition step 110, it is also advantageous to adjust the sharpness of the image, the dimensions of the image and / or the resolution of the image sensor 24. These parameters make it possible to further improve the quality of the images obtained and make it possible to facilitate the image processing step 120 subsequent to the image acquisition step 110.

[0057] According to a third aspect of the method 100 according to the invention, the image acquisition step 110 comprises a third sub-step 113 during which a gray value g BC is changed from a gray level, called target white, from a maximum g N to a first intermediate gray value gu between the reference black g 0 and the maximum g N without including these values. The target white is so called because it is the target gray level for which it is desired to maximize the number of pixels of the image k to be acquired having this gray level in proportion to the total number of pixels contained in the image k to be acquired. In other words, it is the gray level k having the gray value gk with which a maximum number of pixels Q max is to be associated. This makes it possible to avoid over-saturation of the image of the room 10 and to highlight the most interesting pixels.This will be better described with reference to the description relating to the following sub-steps of the image acquisition step.

[0058] In addition to the observation device 22 and the screen 30, the apparatus 20 also advantageously comprises a computer 40 for implementing the third sub-step 113. The target white gBc, initially associated with the maximum gray value g N, is modified so as to be associated with a gray value between the reference black g 0 and the maximum g N, without including g0 and gN, called the first intermediate gray value g u. The third sub-step 113 is therefore an assignment step in which a new gray value is assigned to the target white. Preferably, the first intermediate gray value g kl is between 110 and 140 for a gray level dynamic of 8 bits. Generally, this value g kl will be between 40% and 60% of the average value of the maximum gray level following the encoding of the image.In the example shown here, the grayscale dynamic range is 8 bits and the maximum grayscale is 255, the intermediate grayscale value gk] is for example between 110 and 140. We will come back to this later.

[0059] According to a fourth aspect of the method 100 according to the invention, the image acquisition step 110 further comprises a fourth sub-step 114 during which a histogram is produced representing the number of pixels Q k, Q integer, as a function of the gray level k and the intensity I exp of the light source 24 is adjusted so that the gray value g peak with which the maximum number of pixels Q is associated max detected by the acquisition device 20 corresponds to the first intermediate gray value gk[ defined during the third sub-step 113.

[0060] The production of the histogram is also advantageously implemented by the computer 40. As indicated, the histogram is a function representing the number of pixels Q k as a function of the gray level k. The histogram advantageously expresses in real time the proportion of the different gray levels k in the analysis zone, this analysis zone becoming an image I; once it has been captured by means of the image sensor 24. The histogram can be plotted to facilitate the identification of the gray level and the corresponding peak gray value g with which the maximum number of pixels Q is associated, but this is not obligatory. This step can be carried out by digital analysis using a suitable digital processing tool, for example the software associated with the image sensor 24 or the computer.

[0061] The operations carried out during the fourth sub-step 114 may involve a succession of observation and adjustment steps on the part of the operator. Indeed, the operator must first adjust the intensity of the light source 26 as a function of the difference observed between the actual gray value at which the peak g peak of the histogram is located and the first intermediate gray value g kI = gBc at which the peak g peak of the histogram should be located. If the actual gray value at which the peak g peak of the histogram is located is lower than the first intermediate gray value g kI at which the peak g peak of the histogram should be located, the operator increases the intensity of the light source 26.On the contrary, if the actual gray value at which the peak g peak of the histogram is located is greater than the first intermediate gray value gu at which the peak g peak of the histogram should be located, the operator decreases the intensity of the light source 26. As long as gpic is different from gkl, the operator repeats the observation and adjustment steps.

[0062] The operator is therefore constrained by the first intermediate gray value ga = gBc to be reached, so that this step does not depend on the subjective assessment of the operator but is, on the contrary, carried out according to a well-defined protocol. Once the histogram highlights a superposition of the real gray value at which the peak g peak is located and the first intermediate gray value gk;, the fourth sub-step 114 is completed. This means that the maximum number of pixels Q mœi detected by the acquisition device 20 corresponds to the first intermediate gray value g u. At the end of the fourth sub-step 114, the room 10 is therefore illuminated by the light source 26 with an illumination Ei defined by the first intermediate gray value gki. The illumination Ei obtained is therefore set to the gray values ​​actually measured by the image sensor 24.

[0063] According to a fifth aspect of the method 100 according to the invention, the image acquisition step 110 further comprises a fifth sub-step 115 during which the target white g BC is changed from the first intermediate gray value gu to the maximum g N. The fifth sub-step 115 thus performs the reverse of what was done during the third sub-step 113. Like the third sub-step 113, the fifth sub-step 115 can be implemented by the computer 40. The target white gBc, associated with the first intermediate gray value gk] during the third sub-step 113, is modified so as to be associated with the maximum g N. The fifth sub-step 115 is therefore a reassignment step in which the target white is reassigned the gray value gN corresponding to the maximum. As mentioned previously, according to a preferred embodiment, this maximum is equal to 255.By setting the full image dynamic range back to 8 bits, as the EL lighting was set to gu level, all the pixels in the room are correctly exposed (in the middle of the dynamic range). This allows for independence from ambient lighting.

[0064] Still during the fifth sub-step 115, once the reassignment has been carried out, a first image 11 of the part 10 is acquired. At this step of the method, the part 10 is illuminated by the light source 26 so that its illumination Ei corresponds to that defined by the first intermediate gray value gkl-

[0065] According to a sixth aspect of the method 100 according to the invention, the image acquisition step 110 comprises a sixth sub-step 116 during which the third 113, fourth 114 and fifth 115 sub-steps are repeated for second and third intermediate gray values ​​g k2, g k3 distinct from each other and distinct from the first intermediate gray value gk[ so as to obtain a second image 12 and a third image 13 respectively. The sixth sub-step 116 is therefore actually composed of six sub-steps since the entire process carried out during the third 113, fourth 114 and fifth 115 sub-steps is implemented for each of the second and third intermediate gray values ​​g k2, g k3. At this stage, it should be remembered that the first, second and third images Ib I2 and I3 do not necessarily illustrate the entire part 10 but at least the area SI to be observed.

[0066] At the end of the fourth sub-step 114 implemented for the acquisition of the second image I2, the room 10 is illuminated by the light source 26 with an illumination E2 defined by the second intermediate gray value gk2. Preferably, the second intermediate gray value gk2 is between 110 and 140 while being distinct from the first intermediate gray value gkb. Similarly, at the end of the fourth sub-step 114 implemented for the acquisition of the third image I3, the room 10 is illuminated by the light source 26 with an illumination E3 defined by the third intermediate gray value gk3. Preferably, the third intermediate gray value gk3 is between 110 and 140 while being distinct from the first intermediate gray value gkl and the second intermediate gray value gk2. The first, second and third images L, I2 and I3 are therefore obtained by a well-defined protocol which depends neither on the experience of the operator nor on the environment in which the part 10 is located, which objectifies the method 100 of quantifying the burns generated during the grinding of the part 10.

[0067] Incidentally, step 120 of processing the first, second and third images Ii, I2 and I3 is no longer impacted by subjective input data but, on the contrary, by objective input data. The burns present on the part can therefore be distinguished from the other anomalies present on the surface S of the part 10, and therefore identified, which allows their quantification. The subsequent step 130 of calculating the surface burn rate p on the zone SI of the part can therefore also be implemented from reliable and objective input data.

[0068] According to a seventh aspect of the method 100 according to the invention, the image processing step 120 comprises a sub-step 123 during which, for each of the first, second and third images 1, 12 and 13, a thresholding of the first series of pixels is carried out so as to identify a third series of pixels associated with the burns. The thresholding makes it possible to discriminate the pixels associated with the burns, i.e. the third series of pixels, from the other pixels of the first series of pixels, which makes it possible to better distinguish the burns of the surface S of the sample and other potential anomalies located on the surface of the sample.

[0069] According to a preferred implementation, this sub-step 123 is implemented by Otsu thresholding. The first, second and third images F, I2 and I3 previously mentioned are then transformed into binary images. The images are called binary because for a given gray level kL, all the pixels of the image having a gray value gCi lower than the gray value of this gray level kL are brought back to a first gray value, while, in parallel, all the pixels of the image having a gray value gC2 higher than the gray value of this gray level kL are brought back to a second given gray value. Thus, the images are binarized. The selected gray level kL makes it possible to highlight the burns by thresholding effect. In this respect and preferably, the first gray value is the reference black g0 while the second gray value is the maximum gN, which makes it possible to distinguish the burns very clearly ([Fig.3], right column, fourth image from the top of the figure).

[0070] Otsu's method makes it possible to automatically obtain a threshold for separating the pixels into two classes. In this regard, we define a first class C j of levels of gray k, with k between 0 and k L, k L being an arbitrarily chosen reference gray level satisfying the condition 0 < k L < N, and a second class C 2 of gray levels k with k between k L and N. From there, it is appropriate to assign very different gray values ​​to the pixels associated with the gray levels of the first class C; and to the pixels associated with the gray levels of the second class C 2 , a gray value being assigned to each class. Otsu's method does not require parameter adjustment (automatic thresholding) and contributes to obtaining objective results.

[0071] As an alternative to the Otsu method, it is also possible to implement the watershed method to perform the thresholding 123 of the first series of pixels of the first, second and third images 1, 12 and 13 and thus identify a third series of pixels associated with the burns. According to another alternative, the thresholding sub-step 123 can be implemented by the region growth method. That being said, the Otsu method has the advantage of not requiring parameter adjustment and is simpler to implement than the two aforementioned methods.

[0072] According to an eighth aspect of the method 100 according to the invention, the surface burn rate p on the zone SI to be observed corresponds to the ratio R of an average of the areas of the third series of pixels associated with the burns in the first series of pixels of the first, second and third images 1 j, 12 and 13 on an average of the areas of the pixels of the first series of pixels in the first, second and third images 1 j, 12 and 13.

[0073] The calculation of the surface burn rate p therefore results from the data of the three images 1 j, 12 and 13 acquired during the method 100 according to the invention. The surface burn rate p is therefore calculated on the basis of objectively established data originating from the analysis of three images of the part 10 under well-defined lighting conditions. It is therefore possible to calculate and compare with each other the surface burn rates p of different zones SI to be observed because the image acquisition step 110 of the method 100 according to the invention is repeatable.

[0074] Particularly advantageously, the first intermediate gray value gkl is equal to 110, the second intermediate gray value gk2 is equal to 130 and the third intermediate gray value gk3 is equal to 140, the number of gray levels N being equal to 256. These intermediate gray values ​​are both weakly dispersed around a central value between the reference black g0 and the maximum gN while being sufficiently different from each other so that the first, second and third images 1 j, 12 and 13 are sufficiently contrasted with respect to each other. The gray values ​​between 110 and 140 correspond to halftones to which it is easier to match gpic during the adjustment carried out during the fourth sub-step 114 of the image acquisition step 110.

[0075] Furthermore, illumination of the part in gray values ​​gk too close to the reference black g0 or too close to the maximum gN would not make it possible to distinguish the burns on the part during the fifth sub-step 115. Indeed, under these lighting conditions, the part 10 would be, depending on the case, either too dark or too bright for the contrast between the burns and the rest of the part 10 to be sufficient for the image processing step 120 to be able to be implemented easily.

[0076] With reference to [Fig.2], according to a particular implementation, the second processing step 120 comprises a first masking sub-step 121 in which a mask 14 is generated 1210 ([Fig.3], image in the left column) corresponding to a binary image in which the pixels of the areas of interest of the first series of pixels have a first binary value equal to one and the rest of the pixels have a second binary value equal to zero, then the mask 14 is applied 1211 to the first, second and third images 1 j, 12 and 13 so as to obtain a second series of images IiM, I2M and I3M comprising only the first series of pixels.

[0077] The first masking sub-step 121 makes it possible to target the area SI to be observed in the image ([Fig.3], right column, first image from the top of the figure) and to extract it from the background 12 or, similarly, to target the background 12 of the image and to extract the area SI to be observed. In either case, the first masking sub-step 121 makes it possible to separate the first series of pixels associated with the part 10 from the second series of pixels associated with the background 12. Once this separation is carried out, the image processing can continue on the first series of pixels, then the identification and quantification of the burns can be carried out as mentioned in relation to the seventh aspect of the invention. The first masking sub-step 121 therefore makes it possible to retain only the areas of interest for the quantification of burns ([Fig.3], right column, second image from the top of the figure).

[0078] As indicated previously, the mask 14 is a binary image in which the pixels of the areas of interest of the first series of pixels have a first binary value equal to 1 and the rest of the pixels have a second binary value equal to 0. In other words, the mask is composed of 0 and 1.

[0079] The mask 14 is generated by determining a threshold gray value gM close to the gray value g0, and therefore to the reference black, in order to isolate the second series of pixels, corresponding to the pixels representing the background 12, to keep only the first series of pixels, corresponding to the pixels representing the area to be observed. Preferably, the threshold gray value gM used for mask 14 is between 1 and 10 for a gray level dynamic of 8 bits.

[0080] Then, during step 1211, this gray threshold is applied to the first, second and third images 11, 12 and Z 3, which makes it possible to generate, respectively, fourth, fifth and sixth images 1 ]M, 1 2M and 13M of the same size where all the pixels having gray values ​​gk lower than the threshold are assigned the binary value 1 while the gray values ​​gk of the rest of the pixels are positioned at 0 (example of mask 14, the reverse would be possible). Then, the mask 14 (binary image) is inverted so that the pixels at 1 go to 0 and represent the background, while the pixels at 0 go to 1 and represent the room.

[0081] The images 1 ]M, 12M and 13M are gray-level images obtained from the first, second and third gray-level images 1 j, 12 and 13 and the binary mask 14. As the first gray-level image 11 and the mask 14 have the same size, the pixels of the first image L superimposed / added to pixels of the mask at 1 are retained in the new image I4 and the pixels of the acquisition image superimposed / added to pixels of the mask at 0 are not retained and are set to 0 by the binary logic operators. The same applies to the second and third images 12 and 13. The image 1211 contains only pixels other than black composing the part to be viewed. These operations make it possible to separate the first series of pixels from the second series of pixels.

[0082] In this regard, although the threshold gray value gu is close to the gray value g0, it is possible during step 1211 that certain pixels set to the value 0 should in reality be set to the value 1 and vice versa. This can occur in particular when the sharpness of the image is not sufficient to properly identify the contours of the different zones. In particular, this concerns the pixels located in the immediate vicinity of the first series of pixels. It is therefore advantageous to define the threshold gray value g14 by analyzing the pixels located in the vicinity of the first series of pixels, preferably at a distance not exceeding more than 5%, preferably not more than 3% of an outline of the first series of pixels. This is a tolerance.

[0083] According to a particular implementation illustrated in [Fig. 2], the second processing step 120 comprises, following the first masking sub-step 121, a second contrast adjustment sub-step 122 aimed at processing the second series of images IiM, I2M and I3M so as to better distinguish the burns from other anomalies, possible, of the surface S of the part 10 and of the surface S itself. In other words, the second contrast adjustment sub-step 122 aims to highlight the contours of the burns in the images, and more precisely the contours of the burns in the first series of pixels ([Fig.3], right column, third image from the top of the figure).

[0084] In this regard, a number of threshold pixels Q seuU is defined 1221, with Q seuU < Q max. then the histogram obtained during the fourth sub-step 114 of the image acquisition step is clipped 1222 from the number of threshold pixels Q threshold for each gray level k having a number of pixels Q k greater than the number of threshold pixels Q seuU. Following this operation, a number of clipped pixels Q s is obtained which is then redistributed 1223 homogeneously over all the gray levels k so as to obtain a clipped histogram. This method, known as contrast limited adaptive histogram equalization (CLAHE), makes it possible to improve the contrast of an image without amplifying the noise in the homogeneous regions of the image. Other contrast enhancement methods could be used.

[0085] The CLAHE method differs from ordinary histogram equalization in that the adaptive method calculates multiple histograms, each corresponding to a distinct section of the image, and uses them to redistribute the brightness values ​​of the image. It can thus improve local contrast and enhance edge definition in each region of an image.

[0086] Preferably, prior to step 1221, each image 1 ]M, 1 2M and 13M can be subdivided into several thumbnails, and depending on the number of thumbnails, an appropriate maximum slope can be defined limiting the amplification of the contrast. The maximum slope is a parameter making it possible to prevent overamplification of noise in relatively homogeneous regions of an image. It limits the stretching of the contrast in the intensity transfer function. Very high maximum slope values ​​allow the histogram equalization to obtain maximum local contrast. The value 1 gives the original image. For example, if the number of gray levels of the histogram established in the fourth sub-step 114 of the image acquisition step is equal to 256, as in an example mentioned previously, the thumbnails can advantageously have a dimension of 40x40 pixels.In this case, a maximum slope of two may preferably be selected. As previously mentioned, other contrast enhancement methods can be implemented to adjust the contrast.

[0087] At the end of this contrast adjustment step 122, each of the fourth, fifth and sixth images 11M, 12M and 13M therefore has an improved contrast, which makes it possible to better define the outline of the burns on the surface S of the part 10, to identify and distinguish these burns from other anomalies which may possibly be present on the surface ([Fig.3], right column, third image from the top of the figure).

[0088] As illustrated in [Fig.3], the thresholding sub-step 123 can advantageously be implemented following the second contrast adjustment sub-step 122, which makes it possible to have more precise thresholding 123. This being the case, when neither the first masking sub-step 121 nor the second contrast adjustment sub-step 122 are implemented, the thresholding sub-step 123 is implemented after the sixth sub-step 116 of the image acquisition step.

[0089] As follows from the previous sections, the image acquisition step 110 is computer-assisted, that is to say that some of its sub-steps are implemented by the computer 40. The steps 120 of image processing and 130 of calculating the surface burn rate p on the part 10 are steps that can be fully implemented by the computer. Preferably, the computer 40 is the same as that used for the image acquisition step 110. Preferably, also, the computer 40 is equipped with a processor configured to implement the different steps and sub-steps of the method 100 implemented by computer.

[0090] In this regard, data processing software may be installed on the processor to automate the processing of the data in real time. What is important in the context of the present invention is that the processor is able to process the image data received from the image sensor 24.

[0091] The implementations shown in the cited figures are only possible examples, in no way limiting, of the invention which on the contrary encompasses design variants within the reach of those skilled in the art.

Claims

1. Claims Method (100) for quantifying burns generated by grinding a part (10) comprising an area (SI) to be observed, the method comprising at least: - a step (110) of acquiring images 11, i integer, of the area (SI) to be observed on a background (12) by means of an apparatus (20) comprising an observation device (22) provided with an image sensor (24) and a light source (26) capable of illuminating the part (10), said acquisition apparatus (20) being configured to acquire images in N gray levels k,k = [0.. .AQ, N integer, each gray level being associated with a gray value gk, each image 11 comprising a first series of pixels associated with the part (10) and a second series of pixels associated with the background (12), - a step (120) of processing the images acquired during the image acquisition step (110), - a step (130) of calculating the surface burn rate p on the area (SI) to be observed, said processing steps (120) and (130) of calculation being implemented by computer, the method (100) being characterized in that the image acquisition step (110) comprises: - a first sub-step (111) of positioning the part (10) between the image sensor (24) and a screen (30) so that the image sensor (24), the part (10), and the screen (30) are aligned in this order, said screen (30) having a matte surface (31) having a gray value corresponding to a reference black g0 and located opposite the part (10), - a second sub-step (112) of adjusting the exposure time T exp and the intensity 1 exp of the light source (26) to predetermined values, as well as the magnification level G of the image, - a third sub-step (113) in which a gray value g BC is changed from a gray level, called target white, from a maximum g N to a first intermediate gray value gk] between the reference black g 0 and the maximum g N without including these values, - a fourth sub-step (114) in which a histogram is produced representing the number of pixels Q k, Q integer, as a function of the gray level k and the intensity I exp of the source is adjusted (24) of light so that the gray value g peak with which the maximum number of pixels Q max detected by the acquisition device is associated corresponds to the first intermediate gray value gkl defined during the third sub-step (113), - a fifth sub-step (115) in which the target white g BC is changed from the first intermediate gray value gk] to the maximum g N and a first image I h is acquired - a sixth sub-step (116) in which the third (113), fourth (114) and fifth (115) sub-steps are repeated for second and third intermediate gray values ​​g k2, g k3 distinct from each other and distinct from the first intermediate gray value gkl so as to obtain a second image 12 and a third image Z 3 respectively, in that the image processing step (120) comprises a sub-step (123) during which, for each of the first, second and third images 1 day, 12 and 13,a thresholding of the pixels of the first series of pixels is carried out so as to identify a third series of pixels associated with the burns, and in that the surface burn rate p on the zone (SI) to be observed corresponds to the ratio R of an average of the areas of the third series of pixels associated with the burns in the first series of pixels of the first, second and third images 1 j, 12 and 13 on an average of the areas of the pixels of the first series of pixels in the first, second and third images 1 j, 12 and 13.,

2. The method (100) of claim 1, wherein the number of gray levels N is equal to 256, the maximum g N being equal to 255, the first g k1, second g k2 and third g k3 intermediate gray values ​​being between 110 and 140.

3. The method (100) of claim 2, wherein the first intermediate gray value gkl is equal to 110, the second intermediate gray value gk2 is equal to 130, and the third intermediate gray value gk3 is equal to 140.

4. Method (100) according to any one of the preceding claims, in which the second processing step (120) comprises a first masking sub-step (121) in which: - a mask (14) corresponding to a binary image is generated (1210) in which the pixels of the areas of interest of the first series of pixels have a first binary value equal to 1 and the rest of the pixels have a second binary value equal to 0, then - the mask (14) is applied (1211) to the first, second and third images 1;, 12 and 13 so as to obtain a second series of images IiM, I2M and I3M comprising only the first series of pixels.

5. Method (100) according to the preceding claim, in which the second processing step (120) comprises, following the first masking sub-step (121), a second contrast adjustment sub-step (122) by applying the CLAHE method to the second series of images I1M, I2M and I3M.

6. Method (100) according to the preceding claim, in which the thresholding sub-step (123) is carried out by applying the Otsu method.

7. Method (100) according to any one of the preceding claims, wherein during the second sub-step (112) of adjusting the step (110) of acquiring images, the sharpness of the image 11, the dimensions of the image and / or the resolution of the image sensor (24) are further adjusted.

8. A method (100) according to any preceding claim, wherein the observation device (22) is a binocular magnifier, the image sensor (24) is a CCD camera and the light source (26) is a ring of LEDs.

9. A method (100) according to any preceding claim, wherein the part (10) is a titanium or titanium alloy part treated by grinding.

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