Method and system for assessing and optionally monitoring or controlling surface texture

Abstract

The invention relates to a computer-implemented method for evaluating and optionally monitoring or controlling a surface texture, comprising the steps of providing image data of a surface to a processing device via an input channel, extracting a plurality of parallel lines from the processed image data by using a pattern recognition algorithm, stitching at least two extracted parallel lines, and calculating a wavelength spectrum of each formed stitched line by means of a fast Fourier transform, and deriving at least one texture parameter of the surface from the provided image data by providing at least one texture parameter via an output channel. Furthermore, the invention relates to a system comprising an input channel connected to a processing device, a processing device configured to derive and optionally monitor or control at least one texture parameter of a surface, an output device, and optionally at least one surface preparation device. Finally, the invention relates to a computer program product for evaluating and optionally monitoring or controlling a surface texture, comprising a data carrier storing a program code to be executed by a processor.

Description

Technical Field

[0001] This invention relates to a computer-implemented method for evaluating and optionally monitoring or controlling surface texture, comprising the steps of: providing image data of a surface to a processing device via an input channel; extracting multiple parallel lines from the processed image data using a pattern recognition algorithm to derive at least one texture parameter of the surface from the provided image data; stitching together at least two extracted parallel lines and calculating the wavelength spectrum of each formed stitched line by means of a fast Fourier transform; and providing at least one texture parameter via an output channel. Furthermore, this invention relates to a system comprising an input channel connected to a processing device, a processing device configured to derive and optionally monitor or control at least one texture parameter of a surface, an output device, and optionally at least one surface preparation device. Finally, this invention relates to a computer program product for evaluating and optionally monitoring or controlling surface texture, comprising a data carrier storing program code to be executed by a processor. Background Technology

[0002] Surfaces give an object its appearance. Surfaces reflect incident light into the observer's eye, thus creating the visual impression of the object.

[0003] The way a surface reflects incident light is defined by factors such as surface roughness. Roughness can actually be zero, meaning the surface is perfectly smooth, like a mirror. Alternatively, a surface can include a degree of roughness, i.e., texture or structured profile, resulting in a certain degree of waviness on the surface.

[0004] The texture can be regular, meaning it can include one or more repeating patterns. Alternatively, the texture can be irregular, meaning it may not include any repeating patterns. Of course, the texture can also include a combination of repeating and non-repeating patterns.

[0005] When an object is coated by applying at least one liquid or solid coating composition and subsequently curing the applied coating composition, the surface that determines the appearance of the object is provided by the resulting coating. Particularly in the automotive industry, body panels are coated for both protective and aesthetic purposes.

[0006] The coating is typically a composite coating system, requiring the application of a first coating, usually a colored topcoat, over an uncured or "wet" first coating, followed by the application of a second coating, usually a varnish. The applied first and second coatings are then cured together. Therefore, such systems are often described as "wet-on-wet" or "two coats / one bake." An incompletely cured drying process can be used between the application of the coatings.

[0007] This type of coating system is typically chosen when an exterior coating must offer optimal visual appearance as well as superior durability and weather resistance. Therefore, it is widely used in the automotive industry, particularly for automotive body panels. Minimum performance requirements for clear coat compositions intended for automotive body panels include high levels of adhesion, scratch and abrasion resistance, shatter resistance, moisture resistance, and weather resistance (measured, for example, by QUV). The clear coat composition must also provide a visual appearance characterized by high gloss, focus of image (DOI), and smoothness. Finally, the coating must be easy to apply in the manufacturing environment and resistant to application defects.

[0008] The varnish used in this coating system is typically applied with a film formation significantly higher than that of the colored topcoat. This higher varnish film formation is an aspect of the system that contributes to the desired appearance and / or durability of the entire system.

[0009] Unfortunately, the higher film-forming requirements of clear coats increase the tendency of clear coat compositions to sag. Sagging primarily occurs on vertically oriented surfaces (i.e., surfaces at an angle of 90° ± 45° to the Earth's surface) and can be described as the undesirable downward flow of the applied coating. It typically manifests as dripping or running, and sagging is sometimes attributed to the application of a coating that is "too heavy" or "too wet." Ideally, commercially successful clear coat compositions will have an inherent tendency to resist sagging, regardless of application and / or facility parameters. The stronger the resistance of the clear coat to sagging on vertically oriented surfaces, the easier it is to apply to automotive OEM facilities.

[0010] However, varnishes resisting vertical orientation and sagging traditionally exhibit increased flow resistance on horizontally oriented surfaces (i.e., surfaces at an angle of 180° ± 45° relative to the Earth's surface). Flow resistance of the coating composition on horizontally oriented surfaces typically results in "orange peel" and / or an overall unacceptable appearance in terms of the smoothness, gloss, and DOI of the cured coating film. Orange peel can be described as a recurring irregularity on the cured film surface caused by the application of a wet film that fails to "smooth out" after application. Although the cured film after peeling feels smooth to the touch, it appears as a series of continuous small bumps or pits. The less "smooth out" or flowable the applied wet film, the more pronounced or clearly defined these bumps or pits will be to the observer. The presence of this surface irregularity makes it particularly difficult to obtain a smooth, glossy varnish surface with a high DOI rating.

[0011] Since the anti-sagging properties and the ability to "smooth out" after application of a coating composition depend on both the composition's components and the coating process, optimization of both the formulation and application process is necessary to achieve the desired visual appearance of the resulting coating. Therefore, an efficient method for evaluating and optionally monitoring or controlling the coating texture (i.e., the surface of the coated object) is of great interest. Summary of the Invention

[0012] Therefore, one object of the present invention is to provide an efficient computer-implemented method and system for evaluating surface texture, which allows empirical verification, particularly during surface preparation, of whether a surface has the desired visual appearance. Particularly preferably, the computer-implemented method and system should allow monitoring of the surface texture during its preparation process to gather information about the influence of production parameters on the resulting texture of the produced surface. Furthermore, particularly preferably, the computer-implemented method and system should allow control of the surface texture during its preparation process by evaluating at least one texture parameter and, if the determined texture parameter exceeds a predefined range or value, by modifying at least one production parameter. This allows for adjustment of the surface preparation process, preferably the production of the coating, to obtain the desired texture, thereby resulting in the very efficient production of coated objects with the desired texture.

[0013] The computer implementation method of the present invention:

[0014] One aspect of the present invention is a computer-implemented method for evaluating and optionally monitoring or controlling surface texture. The method includes the steps of: (i) providing image data of a surface to a processing device via an input channel; (ii) processing the provided image data by the processing device; (iii) deriving at least one texture parameter of the surface from the processed image data by extracting multiple parallel lines from the processed image data using a pattern recognition algorithm, forming at least one splice line by stitching together at least two extracted parallel lines, and calculating the wavelength spectrum of each splice line by means of a fast Fourier transform; and (iv) providing at least one texture parameter via an output channel. Since the at least one texture parameter is directly related to the appearance of the surface, it can be used to define and / or quantify the texture of the surface. Particularly preferably, the method further includes step (v) of monitoring or controlling the surface texture based on the derived texture parameter. This step (v) allows the correlation of production parameters with the obtained surface texture, or the acquisition of a desired surface texture by modifying at least one production parameter if the determined at least one texture parameter is outside a predefined value or range.

[0015] The surface to be evaluated, and optionally monitored or controlled, includes a line pattern (hereinafter referred to as a reflective line pattern). The reflective line pattern is preferably obtained by projecting a predefined line pattern onto the surface. Since any deformation of the reflective line pattern relative to the predefined line pattern is directly related to the surface roughness (i.e., the texture of the surface), the deformation of the reflective line pattern can be analyzed to obtain at least one texture parameter in step (iii). Thus, at least one texture parameter represents the deformation of the reflective line pattern relative to the predefined line pattern. Processing the provided image data, i.e., extracting reflective line pattern information from the provided image data via image processing prior to step (iii) of the method of the present invention, facilitates subsequent analysis of the surface line pattern in step (iii).

[0016] Step (i):

[0017] In step (i) of the method according to the invention, image data of a surface including a line pattern is provided to a processing device via an input channel. The line pattern is obtained by projecting a predefined line pattern onto the surface. Suitable input channels include, for example, image capture devices, databases, networks, clouds, physical storage media such as RAM, ROM, EEPROM, solid-state drives, flash memory, phase-change memory, optical disc storage, disk storage, etc. The surface including the line pattern can be a coating, particularly a varnish layer. This embodiment of the method readily allows for optimization of the appearance of a coating applied to an object (i.e., a coating applied to a car body part, etc.).

[0018] Advantageously, the image data provided in step (i) is obtained immediately after coating application and / or during or after flash application and / or during or after leveling application and / or during or after cooling curing. The applied coating composition can be a liquid aqueous or solvent-based coating composition or a solid coating composition. Furthermore, the coating composition can be a primer, topcoat, or varnish coating composition. The application of the coating composition can be performed, for example, via pneumatic and / or electrostatic spraying as known to those skilled in the art. “Flash” or “leveling” is understood as the passive or active evaporation of organic solvents and / or water from the applied coating material, preferably at 15 to 90°C for 0.5 to 60 minutes. After the flash stage, the formed coating film thus contains less water and / or solvent compared to the applied coating material, but is only partially dry and not yet cured. Conversely, the cured coating film is no longer soft or sticky, but is tuned to a solid coating film whose properties (such as hardness or adhesion to the object) no longer exhibit any substantial change even upon further exposure to curing conditions. Image capture can be performed at any time after the coating composition is applied to the object to obtain image data. Depending on the manufacturing process or the appearance problem to be solved, images can be captured repeatedly at predefined or randomly selected time points to monitor the temporal correlation of at least one texture parameter.

[0019] In many embodiments, the image is preferably captured by a camera having an optical axis extending onto the surface. In one example, a white board comprising a predefined line pattern is illuminated by a white light source, and the predefined line pattern of the white board is projected onto a surface parallel to the optical axis of the camera. If the surface includes a degree of roughness (i.e., texture), the predefined line pattern of the white board is distorted on the surface due to that roughness. In other words, both the position and orientation of the camera relative to the surface to be evaluated support capturing an image and obtaining image data of the surface comprising the line pattern by projecting the predefined line pattern onto the surface in a texture evaluation apparatus.

[0020] The surface portion between at least two lines of the line pattern preferably has an area ranging from 10mm × 10mm to 50mm × 50mm, particularly a 15mm × 15mm area. In the case where the line pattern on the surface is a grid comprising vertical and horizontal intersecting lines, the surface portion corresponds to the area formed by the intersecting lines of the grid. This size of surface portion is easily achievable when using line patterns and is large enough to evaluate the regularity and irregularity of the surface texture.

[0021] The line pattern can be periodic or non-periodic, with periodic line patterns being preferred. Examples of periodic line patterns are simple periodic strips or line patterns, particularly simple line grids, multiple interlaced or interconnected strip gratings, or strip grids with an internal (periodic) structure whose intensity profile deviates from a stepped or box profile, and, for example, profiles with Gauss, Doppelgauss, or Lorentz profiles.

[0022] In a preferred embodiment, the line pattern comprises multiple lines, particularly a line grid, and most preferably an orthogonal line grid. The line pattern may include multiple horizontal or vertical lines. Alternatively, the line pattern may include a grid, i.e., multiple intersecting lines, particularly an orthogonal grid having multiple lines extending perpendicular to the other multiple lines. Therefore, the preferred predefined line pattern projected onto the surface is selected from multiple straight lines, particularly a straight line grid, and most preferably an orthogonal grid of parallel straight lines.

[0023] Step (ii):

[0024] In step (ii) of the method of the present invention, the provided image data is processed by a processing device. The processing preferably includes extracting line pattern information from the image data provided in step (i). In this regard, preprocessing the image data provided in step (i) is particularly preferred. Preprocessing may include applying standard image processing algorithms to the provided image data, such as increasing contrast, sharpness, or brightness. Furthermore, it is particularly preferred to convert the image data provided in step (i) or the preprocessed image data into binary image data. A binary image is an image composed of pixels, which may have exactly one of two colors, namely black and white. The use of binary image data significantly improves the detectability of reflective line patterns because binary image data supports the application of the pattern recognition algorithm preferably used in step (iii). The preprocessing of the provided image data can support the following conversion to binary image data.

[0025] Step (iii):

[0026] In step (iii) of the method of the present invention, at least one texture parameter of the surface is derived from the deviation of the line pattern information of the processed image data, because the deviation of the reflected line pattern relative to the predefined line pattern (i.e., the line pattern projected onto the surface) is directly caused by the texture of the surface. Therefore, the at least one texture parameter derived in step (iii) of the method of the present invention reflects the deviation of the line pattern of the surface from the predefined line pattern projected onto the surface. Thus, deriving at least one texture parameter in step (iii) includes determining the deviation of the line pattern of the surface from the predefined line pattern projected onto the surface.

[0027] Step (iii) involves extracting multiple lines from the processed image data, preferably from binary image data, using a pattern recognition algorithm, and forming at least one splicing line by stitching together at least two of the extracted lines. The splicing line is longer than each extracted line and correspondingly includes more texture information, thus allowing the surface texture to be reliably determined using image data obtained from a small measurement area. This is particularly useful if only image data for a fairly small area is available, for example, during the preparation of a coating by curing the corresponding coating composition in an oven, as this setup only allows for acquiring images of the coating in a very small area to avoid unnecessary heat loss due to the opening in the oven needing to capture surface image data during coating curing. The wavelength spectrum of each splicing line is then calculated using a Fast Fourier Transform (FFT). The FFT extracts the periodic content of the lateral deviation of the splicing line from the original lines of the corresponding splice. The periodic content can be readily transformed into the wavelength spectrum of the splicing line. The calculated wavelength spectrum is then closely related to the repeating pattern of the surface texture.

[0028] At least one texture parameter can be derived as a spectral peak of the calculated wavelength spectrum. The wavelength of the spectral peak corresponds to the dominant repeating pattern of the surface texture. The wavelength of the spectral peak (i.e., the dominant spatial repetition rate) can be considered as the first texture parameter.

[0029] Alternatively, at least one texture parameter is derived from the wavelength range of the calculated wavelength spectrum, which includes the wavelengths of the spectral peaks of the calculated wavelength spectrum. Using the wavelength range instead of the wavelength supports classifying surfaces based on their appearance, that is, assigning surfaces to a class of surfaces with similar appearances. The wavelength range containing the spectral peaks of the calculated wavelength spectrum can be considered as a second texture parameter.

[0030] In this respect, the wavelength range is preferably a predetermined short-wavelength range from 0.3 mm to 1 mm or a predetermined long-wavelength range from greater than 1 mm to 10 mm. The short-wavelength range covers a texture with a finely repeating pattern. The long-wavelength range is adjacent to the short-wavelength range and covers a texture with a coarsely repeating pattern.

[0031] Alternatively, the method of the present invention can be used to derive the short-wavelength range by comparing the surface to a standardized reference surface. A standardized reference surface is provided to cover the short-wavelength range. The surface is associated with the short-wavelength range when it reflects incident light approximately like a standard reference surface.

[0032] Step (iv):

[0033] At least one texture parameter derived in step (iii) is provided via an output channel. Suitable output channels are, for example, physical output channels such as displays, networks, or logical output channels, such as APIs, function calls, databases, etc. Most preferably, a display device is used as the output channel. Suitable display devices are those well known to those skilled in the art and include display devices that provide visual information, which is typically logically and / or physically organized as an array of pixels.

[0034] Optional step (v):

[0035] The method of the present invention may further include monitoring or controlling the texture of the surface based on the texture parameters derived in step (iii).

[0036] Since image data can be repeatedly provided and processed during surface preparation, the method of the present invention allows monitoring of the surface texture during its preparation via at least one texture parameter derived from the image data. Therefore, a preferred first alternative step (v) of the method of the present invention includes monitoring the texture of the surface (5) by repeatedly determining at least one surface texture parameter derived from a line pattern in the processed image data, preferably repeatedly during the preparation of at least one surface, and optionally storing the determined at least one texture parameter on at least one storage device. The stored texture parameter can then be correlated with application, drying, curing, and cooling parameters used when the image data was acquired to evaluate the effect of the parameters on the determined texture parameter. Image data repeatedly provided during the surface preparation process can be collected at predefined or randomly selected time points. To correlate the determined at least one texture parameter with the preparation conditions used to prepare the surface, the preparation conditions are preferably stored at the time the image data is collected and stored on at least one storage device. Suitable storage devices may be selected from disks, hard disk drives, servers, clouds, networks, etc.

[0037] Determining at least one texture parameter during surface preparation also allows modification of the conditions used for surface preparation to adjust at least one texture parameter to a predefined value or range. This allows the surface texture to be adjusted by modifying the preparation conditions during preparation, and thereby reduces the occurrence of undesirable textures on the prepared surface. Therefore, the method of the present invention provides an efficient method for preparing a surface with a predefined texture. Therefore, an alternative optional step (v) includes comparing, preferably repeatedly during surface preparation, at least one texture parameter of the surface derived from a line pattern in processed image data with at least one predefined texture parameter, and modifying at least one parameter used during surface preparation if the derived at least one texture parameter deviates from the predefined texture parameter by a predefined value. Preferably, the at least one parameter changed during surface preparation is selected from application conditions, drying conditions, curing conditions, cooling conditions, or any combination thereof.

[0038] In many embodiments, the method of the present invention is executed by a processor that implements program code that implements the method. In this way, the evaluation of the flow of the sprayed coating can be at least partially automated, which improves the efficiency and accuracy of the evaluation process.

[0039] A fundamental advantage of the method according to the invention is that it can very effectively evaluate the texture of a surface, and further, it allows monitoring or control of the surface texture, thereby allowing the derived texture parameters to be correlated with the conditions used to prepare the surface to derive the effect of said conditions on the obtained texture, or to control the surface texture during its preparation to obtain the desired texture of the prepared surface. The method is based on a very simple apparatus and uses image processing and Fast Fourier Transform. Image processing and Fast Fourier Transform can be performed automatically by a computer. Furthermore, the method can be readily incorporated into currently used surface preparation processes, preferably during the preparation of coatings on an object.

[0040] The system of the present invention:

[0041] Another aspect of the invention is a system for evaluating and optionally monitoring or controlling surface texture, comprising:

[0042] (a) An input channel connected to a processing device, the input channel being configured to provide image data to the processing device.

[0043] (b) A processing device configured as follows:

[0044] - Process image data of a surface including line patterns, wherein the line patterns are obtained by projecting a predefined line pattern onto the surface, and

[0045] - By using a pattern recognition algorithm to extract multiple parallel lines from the processed image data, forming at least one splicing line by stitching together at least two extracted parallel lines, and calculating the wavelength spectrum of each splicing line using a fast Fourier transform, at least one texture parameter of the surface is derived from the line pattern of the processed image data; and

[0046] - Optionally, at least one derived texture parameter can be monitored and / or controlled by providing monitoring or control signals to the surface preparation equipment.

[0047] (c) An output channel configured to display at least one exported texture parameter.

[0048] (d) Optionally, at least one surface preparation device is connected to the processing device and configured to prepare a surface.

[0049] Suitable processing devices include at least one processor, an operating system configured to execute executable instructions, memory, and a computer program including instructions executable by a digital processing device to perform the methods of the present invention. Furthermore, the processing and / or output device may further include a display having a screen for displaying a graphical user interface (GUI).

[0050] Surface treatment equipment may include at least one application device configured to apply a liquid or solid coating composition to a surface, and / or at least one device configured to level the applied coating and / or cure the applied coating and / or cool and cure the coating.

[0051] The system may further include at least one line pattern projection device configured to project a predefined line pattern onto a surface. Suitable line pattern projection devices may include a whiteboard with a predefined line pattern and a light source, preferably a white light source.

[0052] This system is particularly well-suited for use with the methods of the present invention as described above, because it allows for the efficient evaluation, monitoring, or control of the texture of a surface, preferably the texture of a coating applied to an object.

[0053] With necessary modifications, further preferred embodiments of the system of the present invention apply to the description of the method of the present invention.

[0054] The computer program product of this invention:

[0055] Another aspect of the invention is a computer program product for evaluating and optionally monitoring or controlling surface texture, comprising a data carrier storing program code to be executed by a processor. The data carrier can be used to install the stored program code and / or to upgrade installed program code using the stored program code.

[0056] According to the present invention, program code implements the method of the invention. The stored program code is capable of efficiently evaluating and optionally monitoring or controlling the texture of a surface. Since the monitoring or control of the surface texture can be repeated during the preparation of the surface, the obtained surface can be optimized, preferably the quality of the coating, thereby allowing for the efficient preparation of surfaces with desired texture properties.

[0057] Further preferred embodiments of the computer program product of the present invention, with necessary modifications, apply to the methods and systems described herein.

[0058] Applications of the invention:

[0059] Another object of the present invention is the use of at least one texture parameter determined by the method according to the invention for monitoring or controlling the texture of a surface.

[0060] Furthermore, the method of the present invention can be used to detect surface defects, such as pits.

[0061] Particularly preferably, the method of the present invention is used during the preparation of coatings or paints, preferably the outermost coating, and particularly preferably coatings on automobile bodies or automobile body parts. Therefore, another object of the present invention is the use of at least one texture parameter determined according to the method of the present invention for the manufacture of coated objects, preferably automobile bodies and / or automobile body parts. In this respect, it is particularly preferred that at least one texture parameter determined according to the method of the present invention is used in conjunction with automobile paint lines.

[0062] The purpose of this invention is to allow the surface texture to be monitored or controlled by repeatedly determining the texture parameters of the surface during the preparation of the surface, thereby leading to an efficient production process for coated objects.

[0063] Further preferred embodiments relating to the use of the invention, with necessary modifications, are applicable to the methods described herein.

[0064] The present invention is specifically described through the following embodiments:

[0065] Example 1: A method for evaluating and optionally monitoring or controlling the texture of surface 5, comprising the following steps:

[0066] (i) Image data 10 of a surface (5) including line patterns 11, 12; 21, 22; 31, 32 is provided to a processing device via an input channel, wherein the line patterns 11, 12; 21, 22; 31, 32 are obtained by projecting predefined line patterns onto the surface;

[0067] (ii) Image data 10 provided by the processing device;

[0068] (iii) By using a pattern recognition algorithm to extract multiple parallel lines 40, 41, 42, 43, 44 from the processed image data, by splicing at least two of the extracted parallel lines 41, 42, 43, 44 to form at least one splicing line 50, 60, and by using a fast Fourier transform to calculate the wavelength spectrum 73 of each splicing line 50, 60, at least one texture parameter 75 of surface 5 is derived from the line patterns 11, 12; 21, 22; 31, 32 in the processed image data 30; and

[0069] (iv) Provide at least one texture parameter 75 via the output channel.

[0070] Example 2: The method according to Example 1 further includes monitoring or controlling the texture of the surface 5 based on at least one derived texture parameter 75.

[0071] Example 3: The method according to Example 1 or 2, wherein surface 5 is a coating, particularly a varnish layer.

[0072] Example 4: According to the method of Example 3, the image data 10 provided to the processing device via the input channel is obtained immediately after the coating is applied and / or during or after the leveling coating and / or during or after the curing coating and / or during or after the cooling curing coating.

[0073] Example 5: According to any one of the preceding embodiments, wherein the portion 13, 23, 33 of the surface 5 between at least two lines of the line patterns 11, 12; 21, 22; 31, 32 has a region ranging from 10 mm × 10 mm to 50 mm × 50 mm, particularly a region of 15 mm × 15 mm.

[0074] Example 6: The method according to any one of the foregoing examples, wherein the line patterns 11, 12; 21, 22; 31, 32 are periodic or non-periodic line patterns, preferably periodic line patterns 11, 12; 21, 22; 31, 32.

[0075] Example 7: According to any one of the preceding examples, the line patterns 11, 12; 21, 22; 31, 32 include multiple lines 11, 12; 21, 22; 31, 32, particularly grid lines 11, 12; 21, 22; 31, 32, most preferably orthogonal grid lines 11, 12; 21, 22; 31, 32.

[0076] Example 8: The method according to any one of the foregoing embodiments, wherein processing the provided image data 10 in step (ii) includes extracting line pattern information from the image data 10 provided in step (i).

[0077] Example 9: According to the method described in Example 8, the processing of the provided image data 10 includes preprocessing the provided image data 10.

[0078] Example 10: According to the method of Example 8 or 9, the processing of the obtained image data 10 includes converting the obtained image data 10 or the preprocessed image data 20 into binary image data 30.

[0079] Example 11: The method according to any one of the preceding embodiments, wherein deriving at least one texture parameter 75 includes determining the deviation of the line patterns 11, 12; 21, 22; 31, 32 of the surface 5 from a predefined line pattern projected onto the surface 5.

[0080] Example 12: The method according to any one of the preceding examples, wherein at least one texture parameter 75 is derived as the spectral peak 74 of the calculated wavelength spectrum 73.

[0081] Example 13: The method according to any one of Examples 1 to 11, wherein at least one texture parameter 75 is derived as a wavelength range of a calculated wavelength spectrum 73 including spectral peak 74.

[0082] Example 14: According to the method described in Example 13, the wavelength range is a predetermined short-wavelength range from 0.3 mm to 1 mm or a predetermined long-wavelength range from greater than 1 mm to 10 mm.

[0083] Example 15: The method according to Example 13, wherein the wavelength range is a short-wavelength range derived by comparing surface 5 with a standardized reference surface.

[0084] Example 16: The method according to any one of the foregoing embodiments, wherein the output channel is a display device.

[0085] Example 17: The method according to any one of Examples 2 to 16, wherein monitoring the texture of the surface 5 includes preferably repeatedly determining at least a texture parameter 75 of the surface 5 derived from the line patterns 11, 12; 21, 22; 31, 32 in the processed image data 30 during the preparation of at least one surface 5, and optionally storing the determined at least one texture parameter 75 on at least one storage device.

[0086] Example 18: The method according to any Example 17, wherein monitoring the texture of the surface 5 further includes correlating at least one texture parameter 75 that is repeatedly determined with surface preparation parameters used at the time point when image data 10 for deriving at least one texture parameter 75 is obtained.

[0087] Example 19: The method according to any one of Examples 2 to 16, wherein controlling the texture of surface 5 includes comparing, preferably repeatedly during the preparation of surface 5, at least one texture parameter 75 of surface 5 derived from line patterns 11, 12; 21, 22; 31, 32 in processed image data 30 with at least one predefined texture parameter, and modifying at least one parameter used during the preparation of surface 5 if the derived at least one texture parameter 75 deviates from the predefined texture parameter by a predefined value.

[0088] Example 20: The method according to any one of the foregoing embodiments is executed by a processor that executes program code implementing the method.

[0089] Example 21: A system for evaluating and optionally monitoring or controlling the texture of surface 5, comprising:

[0090] (a) An input channel connected to a processing device, the input channel being configured to provide image data 10 to the processing device.

[0091] (b) A processing device configured as follows:

[0092] -Processing image data 10 of surface 5 including line patterns 11, 12; 21, 22; 31, 32, wherein the line patterns 11, 12; 21, 22; 31, 32 are obtained by projecting predefined line patterns onto the surface, and

[0093] - By using a pattern recognition algorithm to extract multiple parallel lines 40, 41, 42, 43, 44 from the processed image data, at least two of the extracted parallel lines 41, 42, 43, 44 are spliced ​​together to form at least one splicing line 50, 60, and at least one texture parameter 75 of surface 5 is derived from the line patterns 11, 12; 21, 22; 31, 32 in the processed image data 30 by means of fast Fourier transform to calculate the wavelength spectrum 73 of each splicing line 50, 60; and

[0094] - Optionally, the at least one derived texture parameter 75 can be monitored and / or controlled by providing monitoring or control signals to the surface preparation equipment.

[0095] (c) An output channel configured to display at least one exported texture parameter 75.

[0096] (d) Optionally, at least one surface preparation device is connected to the processing device and configured to prepare surface 5.

[0097] Example 22: The system according to Example 21 further includes at least one line pattern projection device configured to project a predefined line pattern onto a surface.

[0098] Example 23: A computer program product for evaluating and optionally monitoring or controlling the texture of surface 5, comprising a data carrier storing program code to be executed by a processor, the program code implementing the method according to any one of Examples 1 to 21.

[0099] Example 24: Use of at least one texture parameter 75 determined according to any one of Examples 1 to 20 for monitoring or controlling the texture of a surface.

[0100] Example 25: At least one texture parameter 75 determined according to any one of Examples 1 to 20 for use in manufacturing a coated object, preferably for use in automobile bodies and / or automobile body parts.

[0101] Further advantages and constructions of the invention will become apparent from the following description and accompanying drawings.

[0102] It should be understood that, without departing from the scope of the invention, the features previously described and subsequently described can be used not only in the indicated combinations, but also in different combinations or individually. Attached Figure Description

[0103] Figure 1 A perspective view schematically illustrating an apparatus for performing a method according to an embodiment of the present invention;

[0104] Figure 2 This shows image data obtained by projecting predefined orthogonal grid lines onto a surface;

[0105] Figure 3 This shows the preprocessing process. Figure 2 The image data shown is the preprocessed image data obtained from the image data shown;

[0106] Figure 4 Showing the transformation Figure 3 The binary image data obtained from the preprocessed image data shown;

[0107] Figure 5 schematically showing from Figure 4 Multiple lines extracted from the binary image data shown;

[0108] Figure 6 The four extracted lines are shown schematically.

[0109] Figure 7 Schematic illustration including Figure 6 The splicing line of the four lines shown;

[0110] Figure 8 The binary representation of the splicing line is shown;

[0111] Figure 9 Showing includes from Figure 8 The curve of the wavelength spectrum calculated from the splicing line shown is shown. Detailed Implementation

[0112] Figure 1 A perspective view schematically illustrating an apparatus 1 for performing a method according to an embodiment of the invention is shown. The apparatus 1 includes a surface 5 and a camera 4 having an optical axis extending onto the surface 5, i.e., the camera 4 is pointed toward the surface 5.

[0113] The device 1 further includes a whiteboard 3 with a predefined line pattern and a white light source 2 arranged to illuminate the whiteboard 3. The camera 4, surface 5, and whiteboard 3 are preferably arranged relative to each other such that the predefined line pattern of the whiteboard 3 is projected onto the surface, and the resulting line pattern projected onto surface 5 is parallel to the optical axis of the camera 4. The predefined line pattern of the whiteboard 3 may include an orthogonal grid of multiple parallel lines or preferably parallel straight lines. Additionally, the corresponding parallel straight lines may be equally spaced. However, the line pattern of the whiteboard may also be a non-periodic line pattern. The line pattern reflected by surface 5 deviates from the predefined line pattern of the whiteboard 3 (see...). Figure 2 , 3 4). The degree of deviation is directly related to the surface roughness (i.e., texture) of the surface.

[0114] Whiteboard 3 is illuminated by light source 2. Whiteboard 3 (i.e., a predefined line pattern of whiteboard 3) is projected onto surface 5, and surface 5 including the projected line pattern is captured by camera 4. Surface 5 including the line pattern can be a coating, particularly a clear coat. The coating can be applied to an object, preferably an automotive body part, in a spraying process, preferably a hood spraying process. Furthermore, the applied coating can subsequently be leveled and / or cured and / or cooled. However, the invention is not limited to evaluating and optionally monitoring or controlling the texture of the paint or coating.

[0115] Figure 2 Image data 10 of surface 5 captured by camera 4 is shown. Image data 10 may be captured after the coating is applied and / or during or after the coating is applied during leveling and / or during or after the coating is applied during curing and / or during or after the coating is cooled and cured.

[0116] The captured image data 10 includes portions 13, 23, and 33 of surface 5 and portions of surface 5 including line patterns 11, 12; 21, 22; 31, and 32. Line patterns 11, 12; 21, 22; 31, and 32 include horizontal lines 11, 21, and 31 and vertical lines 12, 22, and 32. Portions 13, 23, and 33 have an exemplary area of ​​15 mm × 15 mm and can typically have areas ranging from 10 mm × 10 mm to 50 mm × 50 mm.

[0117] Figure 3 This shows the preprocessing process. Figure 2 The captured image data 10 shown is obtained as preprocessed image data 20. Processing the captured image data 10 may include preprocessing the captured image data 10 by increasing its contrast, sharpness, brightness, etc.

[0118] Figure 4 Showing the transformation Figure 3 The binary image data 30 obtained from the preprocessed image data 20 shown is shown.

[0119] In a further step, at least one texture parameter 75 of the surface portions 13, 23, 33 is derived from line pattern information extracted from the processed image data 30 (i.e., binary image data 30). Deriving at least one texture parameter 75 includes extracting multiple lines 40, 41, 42, 43, 44 from the binary image data 30 using a pattern recognition algorithm. Figure 5 Showing from Figure 4 Multiple lines 40 extracted from the binary image data 30 shown. Figure 6 Four extracted lines, 41, 42, 43, and 44, are shown as an example.

[0120] Exporting at least one texture parameter 75 further includes forming at least one splicing line 50, 60 by splicing at least two extracted lines 41, 42, 43, 44. Figure 7 Schematic illustration including with Figure 6 The four lines 41, 42, 43, and 44 shown correspond to the four line segments 51, 52, 53, and 54. Figure 8 The binary representation of the splicing line 60, which has been spliced ​​together by more extracted lines 40, is shown.

[0121] Derivation of at least one texture parameter 75 includes calculating the wavelength spectrum 73 of each splice line 60 using fast Fourier transform. Figure 9 The graph 70 is shown, which includes an abscissa 71 indicating wavelength, a ordinate 72 indicating spectral content of wavelength, and a curve from... Figure 8 The splicing line 60 shown is used to calculate the wavelength spectrum 73. The calculated wavelength spectrum 73 includes a spectral peak 74 at wavelength 75. The wavelength 75 of the spectral peak 74 can be derived as a first texture parameter of surface 5.

[0122] Figure Labels

[0123] 1 device

[0124] 2. Light source

[0125] 3 Whiteboard

[0126] 4 cameras

[0127] 5 Surface

[0128] 10 captured images

[0129] 11 Horizontal lines

[0130] 12 Vertical lines

[0131] 13 Surface portion

[0132] 20 Preprocessed images

[0133] 21 Horizontal Line

[0134] 22 Vertical lines

[0135] 23 Surface portion

[0136] 30 processed images, binary images

[0137] 31 Horizontal line

[0138] 32 Vertical lines

[0139] 33 Surface portion

[0140] 40 extraction line

[0141] 41 Extraction line

[0142] 42 Extraction line

[0143] 43 Extraction line

[0144] 44 Extraction line

[0145] 50 splicing line

[0146] 51 line segments

[0147] 52 line segments

[0148] 53 line segments

[0149] 54 line segments

[0150] 60 splicing line

[0151] 70-line graph

[0152] 71 x-axis

[0153] 72. Vertical axis

[0154] 73 Wavelength spectrum

[0155] 74 spectral peaks

[0156] 75. Wavelength of the spectral peak

Claims

1. A method for evaluating and monitoring or controlling the texture of a surface (5), comprising the following steps: (i) Image data (10) of a surface (5) including line patterns (11, 12; 21, 22; 31, 32) is provided to a processing device via an input channel, wherein the line patterns (11, 12; 21, 22; 31, 32) are obtained by projecting a predefined line pattern onto the surface (5); (ii) The image data provided is processed by the processing device (10); (iii) Extracting multiple parallel lines (40, 41, 42, 43, 44) from the processed image data using a pattern recognition algorithm, forming at least one splicing line (50, 60) by splicing at least two extracted parallel lines (41, 42, 43, 44), and deriving at least one texture parameter (75) of the surface (5) from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30) by calculating the wavelength spectrum (73) of each splicing line (50, 60) using fast Fourier transform; and (iv) Provide the at least one texture parameter (75) via the output channel.

2. The method of claim 1, further comprising monitoring or controlling the texture of the surface (5) based on at least one derived texture parameter (75).

3. The method according to claim 1 or 2, wherein, The surface (5) is a coating.

4. The method according to claim 3, wherein, The surface (5) is a varnish layer.

5. The method according to claim 1 or 2, wherein, The line pattern (11, 12; 21, 22; 31, 32) consists of multiple lines (11, 12; 21, 22; 31, 32).

6. The method according to claim 5, wherein, The line pattern (11, 12; 21, 22; 31, 32) is a grid line (11, 12; 21, 22; 31, 32).

7. The method according to claim 5, wherein, The line pattern (11, 12; 21, 22; 31, 32) is an orthogonal grid line (11, 12; 21, 22; 31, 32).

8. The method according to claim 1 or 2, wherein, Processing the provided image data (10) in step (ii) includes extracting the line pattern information from the image data (10) provided in step (i).

9. The method according to claim 8, wherein, Processing the obtained image data (10) includes converting the obtained image data (10) into binary image data (30).

10. The method according to claim 1 or 2, wherein, Derivation of the at least one texture parameter (75) includes determining the deviation of the line pattern (11, 12; 21, 22; 31, 32) of the surface (5) from a predefined line pattern projected onto the surface (5).

11. The method according to claim 1 or 2, wherein, The at least one texture parameter (75) is derived as the spectral peak (74) of the calculated wavelength spectrum (73).

12. The method according to claim 1 or 2, wherein, The at least one texture parameter (75) is derived as a wavelength range of the calculated wavelength spectrum (73) containing the spectral peak (74).

13. The method according to claim 1 or 2, wherein, Monitoring the texture of the surface (5) includes repeatedly determining at least one texture parameter (75) of the surface (5) derived from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30).

14. The method according to claim 13, wherein, Monitoring the texture of the surface (5) includes repeatedly determining the at least one texture parameter (75) of the surface (5) derived from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30) during the preparation of the at least one surface (5).

15. The method according to claim 13, wherein, Monitoring the texture of the surface (5) further includes storing at least one determined texture parameter (75) on at least one storage device.

16. The method according to claim 13, wherein, Monitoring the texture of the surface (5) further includes correlating the repeatedly determined at least one texture parameter (75) with the surface preparation parameters used at the time point when the image data (10) for deriving the at least one texture parameter (75) is obtained.

17. The method according to claim 14, wherein, Controlling the texture of the surface (5) includes comparing at least one texture parameter (75) of the surface (5) derived from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30) with at least one predefined texture parameter during the preparation of the surface (5), and modifying at least one parameter used during the preparation of the surface (5) if the derived at least one texture parameter (75) deviates from the predefined texture parameter by a predefined value.

18. The method according to claim 17, wherein, Controlling the texture of the surface (5) includes repeatedly comparing at least one texture parameter (75) of the surface (5) derived from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30) with at least one predefined texture parameter during the preparation of the surface (5).

19. A system for evaluating and monitoring or controlling the texture of a surface (5), comprising: (a) An input channel connected to a processing device, the input channel being configured to provide image data (10) to the processing device. (b) A processing device configured as - Processing image data (10) of a surface (5) including line patterns (11, 12; 21, 22; 31, 32), wherein the line patterns (11, 12; 21, 22; 31, 32) are obtained by projecting a predefined line pattern onto the surface, and - By using a pattern recognition algorithm to extract multiple parallel lines (40, 41, 42, 43, 44) from the processed image data, at least one splicing line (50, 60) is formed by splicing at least two of the extracted parallel lines (41, 42, 43, 44), and at least one texture parameter (75) of the surface (5) is derived from the line patterns (11, 12; 21, 22; 31, 32) in the processed image data (30) by calculating the wavelength spectrum (73) of each splicing line (50, 60) using fast Fourier transform; and (c) An output channel configured to display at least one of the exported texture parameters (75).

20. The system according to claim 19, wherein, The processing device is further configured to monitor and / or control the at least one derived texture parameter (75) by providing monitoring or control signals to the surface preparation device.

21. The system according to claim 19, wherein, The system also includes: (d) At least one surface preparation device connected to the processing device and configured to prepare the surface (5).

22. A computer program product for evaluating and monitoring or controlling the texture of a surface (5), comprising a data carrier storing program code to be executed by a processor, the program code implementing the method according to any one of claims 1 to 18.

23. The use of at least one texture parameter (75) determined by the method of any one of claims 1 to 18 for manufacturing a coated object, wherein the surface is provided by a coating obtained by applying a coating composition to the object.

24. The use according to claim 23, wherein, The objects to be coated include automobile bodies and / or automobile body parts.

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