Vehicle surface analysis system

Abstract

The present invention relates to a vehicle surface analysis system comprising a vehicle positioning unit, an optical image acquisition unit, and an evaluation unit. The vehicle positioning unit in particular comprises a rotatable platform for supporting a vehicle. The image acquisition unit comprises a plurality of individual image acquisition units operating at different wavelength work spectra and radiant energy levels to generate a number of recorded images. The evaluation unit comprises a difference value generation module, a difference value evaluation module, a comprehensive evaluation module, and a generation module, and is designed to provide a digital surface condition image of the vehicle.

Description

Technical Field

[0001] The present invention relates to a vehicle analysis system for digitally recording, evaluating, and providing the surface condition of a vehicle to be recorded, particularly the painted surface, as a digital image.

Background Art

[0002] Checking the condition of the vehicle surface, particularly the vehicle paint, is basically known from the prior art. For example, it is known to perform paint film thickness measurement using the magnetic induction method. The drawback of this is that it cannot be performed on non-magnetic vehicle areas. Furthermore, paint film measuring devices using the eddy current method have been known in the art. This device can also be used under non-magnetic surfaces such as aluminum. However, the drawback still exists that measurement under non-metallic surfaces such as plastic bumpers is impossible. Furthermore, such measuring devices known from the latest technology only provide information regarding the thickness of the paint and do not provide information regarding other parameters that may be relevant to the evaluation of the condition. Another drawback is that the determination is only performed selectively and manually and is not a non-contact type technology.

Summary of the Invention

[0003] The object of the present invention is to provide a tamper-resistant and user-friendly solution for recording and evaluating the condition of a vehicle surface that does not depend on subjective evaluation and can record various types of vehicle surfaces with as little time and personnel as possible.

[0004] This object is solved by a vehicle surface analysis system having the features shown in claim 1. Preferred embodiments further result from the dependent claims.

[0005] The vehicle surface analysis system according to the present invention comprises, as its main components, a vehicle positioning unit, an optical image acquisition unit, and an evaluation unit.

[0006] According to the present invention, the vehicle positioning unit is intended to support the vehicle under analysis and define its spatial position relative to further components of the system according to the present invention. For this purpose, it comprises a platform and a platform position detection unit.

[0007] The platform is designed in terms of size and load-bearing capacity so that a vehicle can be placed on it. The vehicle itself is not part of the system according to the present invention. In this sense, the vehicle is understood to be a land vehicle, in particular a passenger car. The platform is designed as a rotatable unit. The axis of rotation of the platform corresponds to the vertical axis of the vehicle placed on the platform so that the platform is positioned substantially horizontally. Therefore, the platform preferably corresponds to the design of a rotating plate.

[0008] The platform position detection unit is designed to be used to collect platform position data. This platform position data describes the angular position of a rotatable platform and, therefore, indirectly, the angular position of a vehicle placed on it. Rotating the platform during the detection process allows for mapping of vehicle object points with different spatial coordinates at different angular positions. The platform position data is then transmitted to an evaluation unit. The vehicle positioning unit and the evaluation unit are data-connected to each other for the transmission of platform position data.

[0009] The optical image acquisition unit is designed to provide several, preferably many, recorded images of the vehicle surface, firstly preferably capturing the entire vehicle surface, and secondly, capturing one identical surface portion simultaneously through several image acquisitions.

[0010] For this purpose, the optical image acquisition unit has several individual image acquisition units. According to the present invention, several individual image acquisition units mean that there are at least two individual image acquisition units. However, preferably there are at least three or more individual image acquisition units.

[0011] Each individual image acquisition unit comprises a light source and an image camera. The light source and the image camera have matching wavelength work spectra. This means that the emission spectrum of the light source and the acquisition spectrum of the image camera overlap at least partially. However, the wavelength work spectra of some individual image acquisition units differ from each other.

[0012] Preferably, the optical image acquisition unit includes an infrared wavelength range (hereinafter also abbreviated as IR), individual image acquisition units for the visible wavelength range, and an ultraviolet wavelength range (hereinafter also abbreviated as UV). However, further image acquisition units for other wavelength ranges may be provided. Visible light is understood to be the wavelength range of 380 nm to 780 nm. IR is the wavelength range above 780 nm, and UV is the wavelength range below 380 nm.

[0013] The light source is preferably an LED, which preferably has a precisely determinable narrowband emission spectrum. The spectrum reflected by the vehicle surface depends on both the characteristics of the vehicle surface and the spectrum applied by the light source. By using a precisely determinable emission spectrum, high analytical quality regarding the characteristics of the vehicle surface can be achieved from the resulting reflectance spectrum.

[0014] The reflection spectrum is recorded as an image by the associated image camera, and the working spectrum of the associated image camera is matched to the emission spectrum of the light source.

[0015] According to the present invention, the wavelength work spectra of several individual image acquisition units are different from each other. This means that each light source of an individual image acquisition unit has a different emission spectrum, and each image camera also has a different work spectrum, and the work spectrum of each image camera is adapted to the correspondingly mapped light source.

[0016] Due to different wavelength work spectra, different reflection spectra can be obtained from the same object point on the vehicle surface, which can be used for analysis in corresponding image acquisition.

[0017] According to the present invention, each individual image acquisition unit is further designed to have several different radiant energy levels of the light source. Several different radiant energy levels are understood to preferably mean at least two different radiant energy levels. In this context, the present invention also deals with the fact that the light source is supplied with different power and therefore illuminates with different luminous fluxes, and that, for example, the light source has multiple LEDs and different numbers of LEDs are switched on depending on the set radiant energy level. A light guide device is also included, which is implemented, for example, by a lens or an aperture. The difference in the radiant energy levels applied to each vehicle surface area to be recorded is critical.

[0018] Particularly preferably, each radiant energy level is determined by the evaluation unit. In consideration of this aspect of the present invention, the light source receives a control signal from the evaluation unit for this purpose, and the control signal can be transmitted via a separate connection or optionally via an existing data connection between each individual image acquisition unit and the evaluation unit.

[0019] All individual image acquisition units indirectly provide surface and spatial coordinate data for object points on the vehicle surface by including platform position data. The spatial coordinate data of all individual image acquisition units of the optical image acquisition unit are related to one same spatial coordinate system. For this purpose, individual image acquisition units are calibrated within the same spatial coordinate system. Hereafter, this will also be referred to as a uniform spatial coordinate system.

[0020] Each individual image acquisition unit has an image acquisition range. The image acquisition range includes at least a portion of the vehicle's surface. The image acquisition ranges of the individual image acquisition units overlap, forming a common image acquisition range. The platform is positioned such that the vehicle placed on the platform is at least partially within the common image acquisition range.

[0021] The vehicle is rotated by a vehicle positioning unit. During this rotation, the acquisition process is performed sequentially, and multiple different angular positions of the platform, and consequently the vehicle, are recorded. These angular positions will hereafter be referred to as acquired angles.

[0022] Each image acquisition represents an individual acquisition. Thus, different individual acquisitions are performed in relation to a specific object point, firstly by different individual image acquisition units and therefore in different wavelength work spectra, secondly by the same individual image acquisition unit using different radiant energy levels, and thirdly using different acquisition angles.

[0023] This spans a three-dimensional space of the wavelength work spectrum, radiant energy levels, and acquisition angles at which individual acquisitions are positioned.

[0024] Furthermore, the image acquisition unit includes a positioning unit. The positioning unit establishes fixed positional relationships between individual image acquisition units and between individual image acquisition units and the vehicle positioning unit. This is preferably a frame or stand. The positioning unit may also be designed as a housing.

[0025] Preferably, the markings are also arranged within the common image acquisition range so that the individual image acquisition units can be calibrated to the same uniform spatial coordinate system. Preferably, the markings should be inside the housing.

[0026] According to the invention, each of the individual image acquisition units can further be provided such that it can acquire image point data of an object point of the vehicle by image acquisition and transmit it to an evaluation unit. The image acquisition unit is designed such that the image point data obtained by image acquisition has, on the one hand, coordinate data of the object point and, on the other hand, light intensity data related to the wavelength and the radiation energy level. The image point data of the object point is preferably combined as a data tuple (x, y, g) and further processed.

[0027] The coordinate data is available as two-dimensional coordinate data (x, y). Then, they can be mapped to the spatial coordinates of the common spatial coordinate system by an evaluation unit.

[0028] The wavelength-related light intensity data in the sense of the present invention should be understood such that the light intensity data of the recorded images of the image cameras of different individual image acquisition units is determined by the respective wavelength work spectrum. Thus, the light intensity data from different individual image acquisition units can be different for one and the same object point.

[0029] For the purposes of the present invention, the light intensity data related to the radiation energy level is understood to mean that the light intensity data of the recorded images of the image camera of the same individual image acquisition unit is determined by the applied radiation energy level. However, the light intensity data from different images recorded by the same individual image acquisition unit for one and the same object point will, as expected, be different if the radiation energy levels are different.

[0030] However, unexpectedly, the differences due to the radiation energy levels show different correlations depending on the differences in the radiation energy levels and the wavelength work spectra, and it has been found that these different correlations enable a more accurate analysis of the vehicle surface.

[0031] According to the present invention, the evaluation unit includes a difference value generation module, a difference value evaluation module, an overall evaluation module, and a generation module. Physically, the evaluation unit is preferably designed as a computer having a computer program.

[0032] The evaluation unit receives pixel data from the optical image acquisition unit and platform position data from the vehicle positioning unit.

[0033] The difference value generation module generates difference value data from different light intensity data.

[0034] For this purpose, the difference value module is designed to map the light intensity data of a recorded image for an object point to the light intensity data of at least one other recorded image for the same object point according to the relevant coordinate data. Thus, for example, the data tuple (x, y, g1) of the first recorded image and the data tuple (x, y, g2) of the second recorded image are combined into the data tuple (x, y, g1, g2).

[0035] The mapping may relate to such images from different individual image acquisition units captured at the same radiation energy level. In this case, the recorded images are based on different wavelength work spectra.

[0036] Furthermore, it is possible to map images from one and the same individual image acquisition unit captured at different radiation energy levels.

[0037] However, it is also possible to map image acquisitions based on both different wavelength work spectra and different radiant energy levels.

[0038] Furthermore, it is possible to map images acquired at different acquisition angles, even though they are based on the same wavelength work spectrum and the same radiant energy level.

[0039] Ultimately, mapping is possible for all combinations of wavelength work spectrum, radiant energy level, and acquisition angle.

[0040] Furthermore, for example, in the first mapping, the first image acquisition is mapped to further image acquisitions from the same individual image acquisition unit, but at different radiant energy levels, and then in the second mapping, the same first image acquisition is mapped to further image acquisitions from different individual image acquisition units, meaning that multiple mapping is possible.

[0041] Furthermore, after the mapping is complete, the difference value generation module is designed to compare the light intensity data in the light intensity data comparison, generate difference value data from this comparison, and provide the difference value data to the difference value evaluation module. Thus, difference value data can be provided from each mapping.

[0042] In particular, in the case of multiple mappings, it is possible to provide a large amount of difference value data.

[0043] The difference value evaluation module is designed to perform an evaluation of the data quality of difference value data. Based on the evaluation, this difference value data is classified using an adjustable quality value. If the difference value data reaches the adjustable quality value of the data quality, it is classified as usable difference value data. If the difference value data falls below the quality value, it is classified as unusable difference value data. The adjustable quality value can be defined, for example, based on the allowable deviation of the difference value from adjacent object points.

[0044] The generation and evaluation of difference values ​​are performed for each object point used and for each image acquisition of different individual image acquisition units.

[0045] The difference value generation module and the difference value evaluation module perform multiple difference value evaluations. Each of the difference value generation module and the difference value evaluation module can have multiple designs. The difference value generation module elements and the difference value evaluation module elements can process image point data from image acquisition in parallel, and a single module or module element can perform sequential processing with subsequent temporary storage.

[0046] In particular, when image acquisitions with different radiant energy levels from the same individual image acquisition unit are mapped, it is preferable to map one such difference value generation module element or one difference value evaluation module element to one individual image acquisition unit.

[0047] The usable difference value data obtained through the aforementioned acquisition, difference value generation, and subsequent difference value evaluation for a specific object point is sent to the comprehensive evaluation module, which forms the basis for the comprehensive evaluation from all usable difference value data for that object point.

[0048] The overall evaluation module uses the coordinate data of object points to map the available difference value data from the difference value evaluation module, and therefore from the individual image acquisition units, to each other.

[0049] The comprehensive evaluation module is designed to perform a comparison between the quality values ​​of the available differential data for one differential value generation and the quality values ​​of the available differential data for further differential value generation. Based on this, the available differential data for differential value generation can be weighted as a function of the quality values, for example, in the form of a ranking classification, relating to object points. For example, weight coefficients can be mapped to differential data according to the ranking classification. For example, the differential data for a given object point with the highest quality value is given the highest weight coefficient. The differential data for this particular object point with a low quality value is given only a low weight coefficient. The weight coefficients can be used for subsequent processing, in particular, to determine how different weighted differential data relate to one same object point. The weighted differential data is provided to the generation module in a convertible format.

[0050] Therefore, the weighting is based on a quality assessment of the difference data using quality values. The quality assessment can be an absolute or relative assessment of the recorded data quality of the difference data. In addition to discrete algorithms, it is also possible to use algorithms that include an "n-to-n" relationship for quality assessment. Thus, for example, if the quality of the difference data generated from difference data based on individual acquisitions from one acquisition angle is low, it is possible to improve the quality of the resulting analysis by using difference data generated from difference data based on individual acquisitions from multiple acquisition angles, or if the quality of the difference data generated from difference data based on individual acquisitions at one radiant energy level is low, it is possible to use difference data generated from difference data at multiple different radiant energy levels always related to the same object point.

[0051] Furthermore, validation can be performed by the comprehensive evaluation module. If at least three weighted difference data sets are available for the same object point, the comprehensive evaluation module can compare the available weighted difference data sets for a given object point and, based on the degree of adjustability of the deviation of the first weighted difference data set from the second and third weighted difference data sets, it can be designed to discard the first weighted difference data set and not forward it further to the generation module.

[0052] The generation module is designed to map coordinate data from weighted difference data of individual image acquisition units to a uniform spatial coordinate system, taking into account the platform's position data. Different coordinate data from the weighted difference data of the same object point on the vehicle are provided for different angular positions of the platform. Nevertheless, since the platform coordinate data is also known to the evaluation unit, all weighted difference data associated with the same object point can be uniquely mapped to this object point.

[0053] Based on this, firstly, a digital surface contour image of the vehicle is generated in a uniform spatial coordinate system.

[0054] Initially, the digital surface contour images generated in this way are based solely on coordinate data.

[0055] Next, the generation module complements the vehicle's digital surface contour image by adding further data from the weighted difference data based on the coordinate data, thereby creating a digital surface state image of the vehicle. The additional weighted difference data includes data other than coordinate data from the data tuple, namely, data relating to the difference in light intensity values, weighting data, and data relating to wavelength and radiant energy levels.

[0056] The digital surface condition image is provided in a displayable format.

[0057] A particularly useful feature is that digital surface condition images provide comprehensive information about the overall condition of the vehicle's surface, any damage, and any previous touch-ups or repairs.

[0058] In particular, this provides information on the following characteristics of the vehicle surface: - Determining the relative age of the paint on the painted surface. - Determining the thickness of the clear coat finish - Visualization of defects and irregularities on the painted surface - Detection of scratches or damage to the painted surface and underlying layers. - Determination of UV transmittance on glass surfaces - Evaluation of the deterioration of plastic surfaces over time - Detection of cracks and fissures on plastic surfaces - Detection of color differences on painted surfaces - Determination of gloss, smoothness, and surface properties of painted surfaces.

[0059] A further benefit is that the characteristics can be determined non-contact, under conditions where all potential interference or tampering can be eliminated.

[0060] A particularly beneficial aspect is that the vehicle surface analysis system enables the generation of a uniform digital surface condition image of the vehicle based on several different individual image acquisition units.

[0061] For a single object point, image point data is provided from separate acquisitions performed by different, separate image acquisition units.

[0062] Experts tend to increase the informational value of analysis results by aggregating large amounts of databases, but surprisingly, it has been found that the quality of analysis results can be improved by determining difference values ​​from the aggregated databases, and therefore by reducing the number of databases initially.

[0063] Furthermore, the following facts are particularly useful.

[0064] Firstly, individual image acquisition units can effectively support each other. For example, image acquisition in one wavelength range may provide high information quality for certain parts of the vehicle surface but not for others, while conversely, image acquisition in a different wavelength range may provide particularly high information quality only for those other parts.

[0065] Secondly, it is beneficial for a vehicle surface analysis system to automatically identify the quality of pixel data from different image acquisitions, and therefore its suitability for use, and to always use pixel data that provides higher quality digital surface condition images.

[0066] Thirdly, the pixel data is initially assigned, preferably by subtractive mapping, through the generation of difference values. Subsequently, cumulative mapping of the difference values ​​is performed to further improve the quality of the analysis results.

[0067] A further advantage is that digital surface condition images allow the vehicle to be displayed in various views, for example, with the doors closed or open, and from various perspectives, such as a 360° view.

[0068] In particular, there is the advantage of being able to obtain digital images of vehicles with a sufficient database for the following two important applications:

[0069] Firstly, digital surface condition images are suitable for recording vehicle damage, automatically determining the necessary repairs, identifying required spare parts and work processes, and determining the resulting repair costs, all of which can be achieved in digital format. In particular, the ability to detect and display damage caused by overpainting is highly beneficial.

[0070] Secondly, by further processing digital images, vehicle evaluations can be performed automatically, for example, to support the remote sale of used cars. In vehicle evaluations, additional data such as vehicle age, mileage, number of previous owners, and other value-determining factors can be included in the automatic calculation of vehicle value.

[0071] Security against tampering and reliable documentation of vehicle damage registration and vehicle assessment are particularly beneficial.

[0072] Another advantage is the modular nature of the vehicle surface recording system. Depending on the requirements, i.e., according to the quality specifications, or according to the type of vehicle surface to be analyzed, such as painted surfaces, glass surfaces, or plastic parts surfaces, the vehicle surface analysis system can be equipped with different individual image acquisition units, or only specific image acquisition units can be used for image acquisition.

[0073] The vehicle surface analysis system according to the present invention is based, in particular, on the fact that all individual image acquisition units, and therefore all image acquisitions, are calibrated to one same coordinate system. Image point data is acquired multiple times due to the different designs of the image acquisition units and the fact that acquisitions can be performed at different angular positions as a result of the rotation of the vehicle on the platform. The quality of the acquired pixel data is improved because even uncertain information obtained in a single acquisition can be used in addition to other uncertain information obtained in one or more individual acquisitions.

[0074] Digital surface condition images can be usefully represented as multiple layers, which is why they are also called multilayer information. Each layer contains different types of information; for example, one layer might contain information about surface damage, while another layer might contain information about hidden repairs to previous damage. In this way, viewers, or for example, vehicle evaluators, can obtain more information than simply representing the vehicle's surface with a picture.

[0075] The digital surface condition image is designed to represent a digital twin of the recorded vehicle surface, and the recording results of the vehicle surface are provided as a digital surface condition image containing multiple types of information.

[0076] Digital surface as a digital twin situation By using images to automatically process the information gathered within them, it becomes possible to perform calculations such as repair estimates.

[0077] In a beneficial further development, the vehicle surface analysis system is provided with a housing, and the vehicle positioning unit is located inside the housing. The housing can achieve defined optical conditions in both the visible and invisible spectra during the recording process, and has a particularly beneficial effect in that interference light sources are shielded. Therefore, it is preferable to improve the accuracy of the recorded object data. At the same time, the environment and especially personnel are protected from the light sources of the individual image acquisition units, which is particularly relevant to UV light sources with high radiant energy levels. Preferably, the housing can simultaneously fully or partially form the positioning unit of the optical image acquisition unit and determine the positional relationship of the individual image acquisition units. For this purpose, it is preferable that the optical image acquisition unit is also located inside the housing.

[0078] According to another further development, the vehicle recording system includes a comparison module. The comparison module contains a database with data on a reference digital image. The database can be an internal or external database. As an additional benefit, the external database also allows for centralized data management. The reference digital image describes the same type of vehicle in its as-manufactured state.

[0079] The comparison module is designed to perform a comparison between a digital surface condition image and a reference surface condition image to generate a digital difference image. The digital difference image explains how much the recorded vehicle condition deviates from the condition of the vehicle surface at the time of manufacture. Therefore, the digital difference image shows, in particular, the degree of surface deterioration, damage, and repair, i.e., the degree of paint touch-ups and overpainting of subsurface damage. Thus, it can be output, for example, in the form of a condition report. This vehicle condition report can serve as the basis for necessary repairs, particularly paint repairs and descriptions regarding the value of the vehicle.

[0080] Further developments include a vehicle recording system equipped with a repair calculation module. This module includes a database containing repair data, which may include repair time and costs, as well as, in some cases, data on spare parts such as plastic components on the vehicle surface. This database may exist as an internal or external database.

[0081] Spare parts data indicates which spare parts are needed for repair in which cases of damage. Repair time data includes the repair time required to perform the repair, usually called the labor value. Repair cost data shows the price at which spare parts are available and the cost at which the repair work can be performed. Therefore, it is preferable that repair costs be stored in the database as standard prices.

[0082] The repair calculation module is designed to create a repair assessment based on digital difference images and repair data, which includes spare parts required for the repair, the repair time to be used, and the repair cost.

[0083] This further development preferably makes it possible to obtain an automated and tamper-proof detailed statement regarding necessary repairs and their costs. Therefore, cost estimates can be generated automatically. One advantage is that labor costs can be significantly reduced.

[0084] In a further development, it would also be possible to automatically order spare parts based on repair evaluations.

[0085] Further developments suggest that the vehicle recording system includes an appraisal module. The appraisal module includes a database containing vehicle price data. Again, this database could be an internal or external database.

[0086] Vehicle price data is understood to include, for example, a list price based on the vehicle configuration, a price list based on vehicle age, mileage, number of previous owners, and any additional price data.

[0087] The appraisal module is designed to generate an appraisal value based on vehicle price data including digital surface condition images, digital difference images, and repair data. This appraisal value may preferably be a surface condition-based depreciation or value, where the vehicle's surface condition is above or below the average of comparable vehicles considering the vehicle's age. Further developments of this approach favorably provide solutions that assist in determining the commercial value of a vehicle, are automated and therefore require little work, are tamper-proof, and can be reliably documented.

[0088] By using exemplary embodiments, the present invention will be described in more detail with reference to the accompanying drawings. [Brief explanation of the drawing]

[0089] [Figure 1] This is a schematic diagram of the top view. [Figure 2] This is a schematic diagram of the image acquisition process. [Figure 3] This is a block diagram of the repair calculation module and the assessment module.

[0090] Figure 1 is a schematic diagram of a first embodiment of a vehicle surface analysis system.

[0091] Vehicle 4 can have its position relative to the optical image acquisition unit 2 fixed by the vehicle positioning unit. For this purpose, the vehicle positioning unit 1 includes a rotatable platform 11. As intended, vehicle 4 can be driven onto this platform. The arrows indicate the rotatability of the platform 11. A further element of the vehicle positioning unit 1 is the platform position detection unit 12. It records the rotational position, and therefore the angular position, of the platform 11 and transmits it to the evaluation unit 3 via a wired data connection.

[0092] Figure 1 also shows an optical image acquisition unit 2. In an exemplary embodiment, this unit comprises three separate image acquisition units 21. Each of the separate image acquisition units has a light source 211 and an image camera 212.

[0093] In this embodiment, the first of the three individual image acquisition units 21 has an infrared light source and an infrared image camera, the second of the three individual image acquisition units 21 has a light source in the visible light wavelength range and an image camera, and the third of the three individual image acquisition units 21 has a light source in the ultraviolet wavelength range and a camera.

[0094] The image acquisition range 22 of each individual image acquisition unit 21 is directed to cover the vehicle 4 placed on the platform 11. In this embodiment, the image acquisition ranges 22 overlap.

[0095] In an exemplary embodiment, the positioning unit 23 is designed as a frame. Individual image acquisition units 21 are rigidly mounted on it and thus fixed in their positional relationships with respect to each other and to the platform 11. This design allows all image point data captured by the individual image acquisition units 21 at the vehicle's object points to be mapped to a uniform spatial coordinate system after calibration.

[0096] In the exemplary embodiment shown in Figure 1, the vehicle surface analysis system has a housing 2 that is opaque to the wavelength range of all three individual image acquisition units. In particular, the vehicle positioning unit 1 and the optical image acquisition unit 2 are located inside the housing 5. The housing 5 is provided with a closable opening (not shown in Figure 1) through which the vehicle 4 can be moved inside on the platform 11 and then moved back outside after recording is complete.

[0097] Figure 1 also shows evaluation unit 3, which in this example is a computer system consisting of a computer with software.

[0098] The evaluation unit 3 is connected to three individual image acquisition units 21 via data connections, from which it receives image point data of object points on the vehicle surface of vehicle 4 from image acquisition, also known as individual acquisition. (Data connections from the individual image acquisition units 21 and the platform position detection unit 12 to the evaluation unit 3 are shown without reference numerals.)

[0099] According to Figure 1, the evaluation unit 3 includes a difference value generation module 31, a difference value evaluation module 32, an overall evaluation module 33, and a generation module 34.

[0100] The difference value generation module 31 is used to map individual image acquisitions. In this exemplary embodiment, several image acquisitions are available from individual image acquisition units 21, and each image acquisition is recorded at a different radiant energy level. According to the first exemplary embodiment, the difference value generation module 31 is designed to map the image acquisitions from different individual image acquisition units 21, i.e., mappings where the wavelength work spectra are different but in all cases the same radiant energy level is used, and to determine the difference in light intensity values ​​from each mapping and provide it as a difference value.

[0101] The difference value evaluation module 32 is configured to receive difference values ​​from the difference value generation module 31 and perform an evaluation of the data quality of the difference values. Each received difference value is evaluated to determine whether it is a valid difference value based on a comparison with the difference value for adjacent object points. Difference values ​​that meet this criterion are classified as usable in this embodiment and are transferred to the overall evaluation module 33 as usable difference values. Otherwise, the difference value is classified as unusable and is therefore discarded and not transferred. All received difference values ​​are thus processed sequentially by the difference value evaluation module 32.

[0102] Therefore, the difference value evaluation module 32 includes only data that is sufficiently reliable for the vehicle surface condition image created later, and thus the surface condition image also has the characteristic of being highly reliable.

[0103] In the overall evaluation module 33, the available difference value data obtained from the difference value evaluation module 32 are mapped to each other based on the coordinate data of the object points and evaluated in relation to each other.

[0104] Mapping the available differential value data as belonging to the same object point is based on the fact that the evaluation unit 3 can perform a uniform spatial coordinate system mapping for all individual image acquisition units 21 due to the defined positions of the individual image acquisition units 21 based on the position fixing by the positioning unit 23, and the angular position of the platform 11 known via the platform position detection unit 12, and therefore the angular position of the support vehicle 4.

[0105] Once the mapping is complete, the overall evaluation module 33 compares the quality values ​​of the available differential value data in this exemplary embodiment. As a result of the comparison, the compared available differential value data are ordered, for example, according to the quality value rank, and weight coefficients are mapped to them. The available differential value data with the highest quality value receives the highest weight coefficient, and vice versa. The weight coefficients correspond to the quality values. The available differential value data for each recorded object point, along with the weight coefficients, is provided to the generation module 34.

[0106] By including platform position data, the generation module 34 maps coordinate data from available differential value data to a uniform spatial coordinate system.

[0107] Based on the coordinate data, first, a digital surface contour image of vehicle 4 is generated in a uniform spatial coordinate system. The digital surface contour image is formed by a point cloud corresponding to the geometric shape of the vehicle surface.

[0108] Next, based on the coordinate data, further data is added to the digital surface contour image of vehicle 4 from weighted difference data, and a digital surface state image of vehicle 4 is generated.

[0109] Next, this digital surface condition image is provided in a displayable format. In an exemplary embodiment, the digital image is transmitted as a file. The digital surface condition image can also be visualized on a monitor that functions as a data output device. However, the digital surface condition image is not merely a visualization. In particular, in the exemplary embodiment, the visualization can be adjusted according to specific analytical criteria such as coating thickness, coating age, or coating corrosion spots. Depending on the analytical criteria, the visualization can be set to deviate from a visual impression and to highlight the gradual formation of the analytical criteria with color.

[0110] Figure 2 shows a possible classification of image acquisition from the acquisition process in an exemplary embodiment. The x-coordinate represents the wavelength λ, and the y-coordinate represents the radiant energy level E. In this embodiment, image acquisition is performed by three separate image acquisition units 21, the first separate image acquisition unit 21 operating in the UV wavelength work spectrum λ1, the second separate image acquisition unit 21 operating in the visible light wavelength work spectrum λ2, and the third separate image acquisition unit 21 operating in the IR wavelength work spectrum λ3. Each image acquisition unit generates three images with different radiant energy levels E1, E2, and E3.

[0111] The acquired images λ1E1 to λ3E3 are transmitted to the evaluation unit. In an exemplary embodiment, mapping is first performed within one wavelength work spectrum, and for example, the difference value generation module generates difference values ​​from acquired images λ1E1 and λ1E2, and further difference values ​​are generated from acquired images λ1E2 and λ1E3. Similarly, difference values ​​are similarly generated from acquired images λ2E1 and λ2E2, and λ2E2 and λ2E3, etc. Furthermore, for example, from acquired images λ1E1 and λ2E1, further difference values ​​are generated between acquired images that have different wavelength work spectra but the same radiant energy level. However, difference values ​​from arbitrary "n-to-n" mappings such as λ1E2 and λ3E3 are also possible.

[0112] Figure 3 shows a further exemplary embodiment represented as a block diagram, where both repair evaluation and assessment can be additionally performed.

[0113] The description of the exemplary embodiment shown in Figures 1 and 2 applies to the individual image acquisition units 21, difference value generation module 31, difference value evaluation module 32, overall evaluation module 33, and generation module 34 of the optical image acquisition unit 2.

[0114] After the digital surface condition image is generated by the generation module 34, it is transferred to the comparison module 35 in the exemplary embodiment shown in Figure 3. The comparison module 35 contains a database 351 as a data bank containing data on reference digital surface condition images of numerous vehicle models with different designs, including the reference surface condition image of the recording vehicle 4. This data bank is regularly updated with newly released vehicle models. The comparison module 35 identifies the vehicle model of the recording vehicle 4 based on the digital surface condition image, compares the digital surface condition image of the recording vehicle 4 received from the generation module 34 with the reference surface condition image of the corresponding vehicle model obtained from the database 351, and generates a digital difference image. The digital difference image contains information about the deviation of the recording vehicle 4 from the vehicle in which it was originally manufactured, and can therefore detect hidden damage in particular.

[0115] The digital difference image is made available in parallel to both the repair calculation module 36 and the assessment module 37.

[0116] The repair calculation module 36 includes a database 361 containing repair data. The repair data is vehicle model-related data concerning spare parts, repair time, and repair costs, with repair costs stored as standard prices. Based on the digital reference image and repair data, the repair calculation module determines the spare parts required for the repair, the repair time to be used, and the repair costs incurred according to the stored standard prices, and outputs this as a repair evaluation.

[0117] The commercial value of the recording vehicle 4 can be determined cumulatively or alternatively by the evaluation determination module 37.

[0118] For this purpose, the appraisal module 37 includes a database 371 containing vehicle price data. The vehicle price data includes, in particular, list prices for many vehicle models as well as market prices that depend on age and mileage, and also includes data on the model of the recorded vehicle 4. Based on the vehicle price data, digital difference images, and repair data, the appraisal module 37 generates a vehicle appraisal value. Optionally, supplementary vehicle data, such as the number of previous owners, can also be manually entered via digital images and digital difference images and taken into consideration by the appraisal module 37 when generating the vehicle appraisal value. [Explanation of Symbols]

[0119] 1. Vehicle positioning unit 11 Platforms 12 Platform position detection unit 2 Optical image acquisition unit 21 Individual image acquisition units 211 Light source 212 Image Camera 22 Image acquisition range 23 Positioning Unit 3. Evaluation Unit 31. Difference Value Generation Module 32 Difference Value Evaluation Module 33. Overall Evaluation Module 34 Generation Modules 35 Comparison Modules 351 Comparison Module Database 36 Repair Calculation Module 361 Repair calculation module database 37 Assessment Module 371 Assessment Module Database 4 vehicles 5 Housing

Claims

1. A vehicle surface analysis system, The system comprises a vehicle positioning unit (1), an optical image acquisition unit (2), and an evaluation unit (3). The vehicle positioning unit comprises a platform (11) and a platform position detection unit (12), wherein the platform (11) is designed to support a vehicle (4) thereon, the platform (11) is rotatable around the vertical axis of the vehicle (4) on which it is positioned, and the platform position detection unit (12) is designed to record platform position data and provide it to the evaluation unit (3) in a transmittable form. The optical image acquisition unit (2) comprises a plurality of individual image acquisition units (21) and a positioning unit (23), Each of the individual image acquisition units (21) is equipped with a light source (211) and an image camera (212), Each of the individual image acquisition units (21) has an image acquisition range (22), and the image acquisition range (22) covers at least partially the surface of the vehicle (4). Each of the individual image acquisition units (21) has a different wavelength work spectrum from another individual image acquisition unit (21), Each of the individual image acquisition units (21) is designed to provide multiple different radiant energy levels. The positioning unit (23) determines the positional relationship of the individual optical image acquisition units (21) relative to each other and to the vehicle positioning unit (1), The individual image acquisition unit (21) is designed to acquire pixel data by acquiring images of object points of the vehicle (4) and to provide it to the evaluation unit (3) in a form that can be transmitted. The pixel data includes wavelength-related and radiant energy level-related light intensity value data, and the coordinate data of the object point. The evaluation unit (3) comprises a difference value generation module (31), a difference value evaluation module (32), an overall evaluation module (33), and a generation module (34). The difference value generation module (31) is designed to map the light intensity value data obtained from the image acquisition of an object point to the light intensity value data obtained from at least one further image acquisition of the same object point using the coordinate data associated with the light intensity value data, compare the light intensity value data in a light intensity value data comparison, generate difference value data therefrom, and provide the difference value data to the difference value evaluation module (32). The difference value evaluation module (32) is designed to perform an evaluation of the quality of the difference value data to determine the difference value quality, classify the difference value data into usable data when it reaches an adjustable quality value and unusable data when it does not reach the quality value, and provide the usable difference value data to the overall evaluation module (33) in a form that can be transmitted. The comprehensive evaluation module (32) is designed to use the coordinate data of the object point to map the available difference data from the light intensity data comparison to further available difference data from further light intensity data comparisons, compare the difference quality of the available difference data from the light intensity data comparison with the difference quality of the further available difference data from further light intensity data comparisons, and weight the available difference data as weighted difference data according to the quality value of each difference quality. A vehicle surface analysis system is designed to map the coordinate data from the pixel data to a uniform spatial coordinate system by including the platform position data in the generation module (33), generate a digital surface contour image of the vehicle (4) in the uniform spatial coordinate system, complement the digital surface contour image of the vehicle (4) by adding the weighted difference value data based on the coordinate data to create a digital surface state image of the vehicle, and provide the digital surface state image in a displayable format.

2. The vehicle surface analysis system comprises a housing (5), and the vehicle positioning unit (1) is positioned within the housing (5). The vehicle surface analysis system according to claim 1, characterized in that...

3. The vehicle surface analysis system includes a comparison module (35), the comparison module (35) includes a database having data relating to a reference digital surface condition image, and the comparison module (35) is designed to perform a comparison between the digital surface condition image and the reference digital surface condition image and generate a digital difference image. A vehicle surface analysis system according to any one of claims 1 or 2, characterized in that

4. The vehicle surface analysis system includes a repair calculation module (36), the repair calculation module (36) includes a database containing repair data, the repair data includes data relating to spare parts, repair time, and repair costs, and the repair calculation module (36) is designed to generate a repair evaluation based on the digital difference image and the repair data, the repair evaluation including spare parts required for the repair, the repair time used, and the repair costs. The vehicle surface analysis system according to claim 3, characterized in that...

5. The vehicle surface analysis system comprises an appraisal module (37), the appraisal module (37) comprises a database having vehicle price data, and the appraisal module (37) is designed to generate a vehicle appraisal based on the vehicle price data, the digital difference image, and the repair data. The vehicle surface analysis system according to claim 4, characterized in that

Images