VEHICLE SURFACE ANALYSIS SYSTEM

Description

[0001] The invention relates to a vehicle analysis system for digitally detecting and evaluating the surface quality of the vehicle to be detected, in particular a paint surface, and for providing the surface quality as a digital image. Document DE 20 2018 001659 U1 discloses a vehicle detection system for generating an n-dimensional digital image of the vehicle to be detected.

[0002] It is generally known from the prior art to check the condition of vehicle surfaces, particularly the vehicle paintwork. For example, it is known to measure paint layer thickness using magnetic induction methods. The disadvantage here is that these cannot be performed on non-magnetic vehicle areas. Furthermore, paint layer measuring devices using the eddy current method are known from the prior art. These can also be used on non-magnetic substrates such as aluminum. A disadvantage remains that measurements on non-metallic substrates such as plastic bumpers are not possible. Furthermore, such measuring devices known from the prior art only provide information about the paint thickness, but not about other parameters that may be relevant for assessing the condition.Another disadvantage is that the determination is only carried out selectively and manually and is not a contactless technology.

[0003] The object of the invention is to provide a tamper-proof, easy-to-use solution for recording and evaluating the condition of a vehicle surface that is independent of subjective assessments and with which different surface types of a vehicle can be recorded with the least possible time and personnel expenditure.

[0004] The problem is solved by a vehicle surface analysis system having the features listed in claim 1. Preferred developments are set out in the subclaims.

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

[0006] According to the invention, the vehicle positioning unit is designed to accommodate a vehicle to be analyzed and to define its spatial position relative to other components of the system according to the 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 capacity so that a vehicle can be positioned thereon. The vehicle itself is not part of the device according to the invention. Vehicles in this sense are understood to be land vehicles, in particular passenger cars. The platform is designed to rotate. The axis of rotation of the platform corresponds to the vertical axis of the positioned vehicle, so that the platform is arranged essentially horizontally. The platform thus preferably corresponds to the design of a turntable.

[0008] The platform position detection unit is designed to capture platform position data. The platform position data describes the angular position of the rotatable platform and thus indirectly the angular position of the positioned vehicle. If the platform is rotated during a detection process, object points of the vehicle that have different spatial coordinates at different angular positions can be assigned to one another. The platform position data is made available for transmission to the evaluation unit. For the transmission of the platform position data, the vehicle positioning unit and the evaluation unit are data-linked to one another.

[0009] The optical image capture unit is designed to provide a plurality, preferably a large number, of image recordings of the surface of the vehicle, wherein firstly, preferably, the entire surface of the vehicle is captured and secondly, one and the same surface sections are captured by a plurality of image recordings simultaneously.

[0010] For this purpose, the optical image capture unit comprises a plurality of individual image capture units. According to the invention, a plurality of individual image capture units means at least two individual image capture units. However, the number of individual image capture units is preferably at least three or more.

[0011] The individual image capture units each comprise a light source and an image camera. The light source and the image camera have a coordinated wavelength operating spectrum. This means that the emission spectrum of the light source and the recording spectrum of the image camera at least partially overlap. The wavelength operating spectrum of the multiple image capture units differs from one another.

[0012] The optical image capture unit preferably has an individual image capture unit in the infrared wavelength range (hereinafter also referred to as IR for short), an individual image capture unit in the visible wavelength range, and an image capture unit in the ultraviolet wavelength range (hereinafter also referred to as UV for short). However, additional image capture units in other wavelength ranges can also be present. Visible light is understood to be the wavelength range from 380 nm to 780 nm. IR is understood to be the wavelength range above 780 nm, and UV is understood to be the wavelength range below 380 nm.

[0013] The light radiation source can preferably be an LED, which advantageously has a precisely definable and narrow-band emission spectrum. The spectrum reflected by the vehicle surface depends both on the properties of the vehicle surface and on the spectrum exposed to the light radiation source. A precisely definable emission spectrum allows for high-quality analysis of the vehicle surface properties based on the resulting reflected spectrum.

[0014] The reflected spectrum is recorded as an image by the associated image camera, whereby the associated image camera is tuned in its working spectrum to the emission spectrum of the light radiation source.

[0015] According to the invention, the wavelength operating spectra of the multiple individual image capture units differ from one another. This means that the light radiation sources of the respective individual image capture units have different emission spectra, and the image cameras also have different operating spectra, with the operating spectrum of each image camera being matched to the respective associated light radiation source.

[0016] Due to the different wavelength working spectra, different reflected spectra are obtained from one and the same object point on the vehicle surface, which are available for analysis in the respective image recordings.

[0017] Furthermore, according to the invention, each of the individual image capture units is designed to have a plurality of different radiation energy levels of the light radiation source. A plurality of different radiation energy levels is preferably understood to mean at least two different radiation energy levels. In this case, the invention equally encompasses the light radiation source being subjected to different power and thus illuminating with a different luminous flux, as well as, for example, a light radiation source having a plurality of LEDs, wherein a different number of LEDs are switched on depending on the radiation energy level to be set. Also included are light-directing devices, for example lenses or diaphragms. The decisive factor is the different radiation energy level applied to the respective detection area of ​​the vehicle surface.

[0018] Particularly preferably, the respective radiation energy level is determined by the evaluation unit. According to this aspect of the invention, the light radiation source receives a control signal from the evaluation unit, which can be transmitted via a separate connection or optionally via the existing data connection between the respective individual image capture unit and the evaluation unit.

[0019] All individual image acquisition units directly provide surface coordinates and indirectly, through the inclusion of platform position data, spatial coordinate data of object points on the vehicle surface. The spatial coordinate data of all individual image acquisition units of the optical image acquisition unit are referenced to one and the same spatial coordinate system. For this purpose, the individual image acquisition units are calibrated to the same spatial coordinate system. This is also referred to below as the unified spatial coordinate system.

[0020] Each individual image capture unit has an image capture area. The image capture area encompasses at least a portion of the vehicle's surface. The image capture areas of the individual image capture units overlap and form a common image capture area. The platform is positioned so that a deployed vehicle is at least partially located within the common image capture area.

[0021] The vehicle is rotated using the vehicle positioning unit. This involves sequentially performing detection processes, allowing detections to be made at a variety of different angular positions of the platform and thus of the vehicle, hereinafter also referred to as detection angles.

[0022] Each image capture represents an individual acquisition. The different individual acquisitions are thus carried out with respect to a specific object point, firstly by different individual image acquisition units and thus in different wavelength working spectra, secondly by one and the same individual image acquisition unit with different radiation energy levels and thirdly with different acquisition angles.

[0023] This creates a three-dimensional space of wavelength working spectrum, radiation energy level and detection angle, into which the individual detections are classified.

[0024] The image capture unit further comprises a positioning unit. The positioning unit establishes a fixed positional relationship between the individual image capture units and between the individual image capture units and the vehicle positioning unit. It is preferably a rack or frame. The positioning unit can also be embodied as a housing.

[0025] Preferably, markers are also arranged in the common image acquisition area to enable calibration of the individual image acquisition units into the same uniform spatial coordinate system. The markers are preferably attached to the inside of a housing.

[0026] According to the invention, each of the individual image acquisition units is further characterized in that pixel data of object points of the vehicle can be captured in an image recording and transmitted to the evaluation unit. The image acquisition units are designed such that the pixel data obtained by means of the image recording comprise, firstly, coordinate data of the object points and, secondly, wavelength-related and radiation energy level-related light intensity value data. The pixel data of an object point are preferably summarized as a data tuples (x, y, g) and further processed.

[0027] The coordinate data is available as area coordinate data (x, y). The evaluation unit can then assign them to the spatial coordinates of the common spatial coordinate system.

[0028] Wavelength-related light intensity value data within the meaning of the present invention means that the light intensity value data of the images captured by the cameras of different individual image capture units are determined by the respective wavelength operating spectra. Thus, the light intensity value data from the different individual image capture units can differ for one and the same object point.

[0029] For the purposes of the present invention, light intensity value data related to radiation energy levels is understood to mean that the light intensity value data of the images captured by the cameras of the same individual image capture units are determined by the applied radiation energy level. The light intensity value data from the different images captured by the same individual image capture units for one and the same object point differ, as expected, at different radiation energy levels.

[0030] Surprisingly, however, it was found that the radiation energy level-related differences correlate differently depending on the differences in the radiation energy levels and the differences in the wavelength working spectra, and that these different correlations allow for a more accurate analysis of the vehicle's surface.

[0031] According to the invention, the evaluation unit comprises a difference value generation module, a difference value evaluation module, an overall evaluation module, and a generation module. Physically, the evaluation unit is preferably embodied as a computer with computer programs.

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

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

[0034] For this purpose, the difference value module is configured to assign the light intensity value data from the image acquisition for an object point to the light intensity value data of at least one further image acquisition for the same object point using the associated coordinate data. Thus, for example, the data tuple (x, y, g1) of a first image acquisition and the data tuple (x, y, g2) of a second image acquisition are combined into a data tuple (x, y, g1, g2).

[0035] In this case, the assignment can be based, in particular, on images taken by different individual image acquisition units with the same radiation energy level. In this case, the images are based on different wavelength operating spectra.

[0036] Furthermore, the assignment of images taken with different radiation energy levels from one and the same image acquisition unit can be carried out.

[0037] However, it is also possible to assign images that have different wavelength working spectra as well as different radiation energy levels.

[0038] Furthermore, it is possible to assign images that have the same wavelength working spectra, the same radiation energy levels but different detection angles.

[0039] Ultimately, assignments are possible in all combinations of wavelength working spectra, radiant energy levels and detection angles.

[0040] In addition, it is possible for a multiple assignment to occur in the sense that, for example, a first image recording is assigned in a first assignment to another image recording taken by the same individual image capture unit but with a different radiation energy level, and that the same first image recording is then assigned in a second assignment to another image recording of a different individual image capture unit.

[0041] Furthermore, the difference value generation module is configured to compare the light intensity value data after the assignment has been completed in a light intensity value data comparison and to generate difference value data therefrom, as well as to provide the difference value data to the difference value evaluation module. Difference value data can thus be provided from each assignment.

[0042] Especially in the case of multiple assignments, a large number of difference value data can be provided.

[0043] The differential value evaluation module is designed to evaluate the data quality of the differential value data. Based on the evaluation, this differential value data is categorized using a configurable quality value. If the differential value data reaches the configurable quality value for data quality, it is categorized as usable differential value data. If the differential value data falls below the quality value, it is categorized as unusable differential value data. The configurable quality value can be determined, for example, by permissible deviations from differential values ​​of neighboring object points.

[0044] The difference value generation and difference value evaluation are carried out with reference to each object point used and for each image acquisition of the different individual image acquisition units.

[0045] The difference value generation module and the difference value evaluation module perform a multitude of difference value evaluations. It is possible for the difference value generation module and the difference value evaluation module to each be implemented in multiple ways. It is possible for the difference value generation module elements and the difference value evaluation module elements to process the pixel data from the recorded images in parallel, or for sequential processing to be performed by one and the same module or module element, followed by intermediate storage.

[0046] In particular, when assigning image recordings with different radiation energy levels from one and the same individual image acquisition unit, it is advantageously possible to assign such a difference value generation module element or a difference value evaluation module element to each individual image acquisition unit.

[0047] The usable difference value data from the previously described acquisition for this specific object point, the difference value generation and the subsequent difference value evaluation are transferred to the overall evaluation module and form the basis for an overall evaluation from all usable difference value data for this object point

[0048] The overall evaluation module uses the coordinate data for the object points to assign the usable difference value data from the difference value evaluation module and thus from the individual image acquisition units to one another.

[0049] The overall evaluation module is designed to compare the quality value of the usable difference value data from one difference value generation with the quality value of the usable difference value data from another difference value generation. On this basis, an object-point-related weighting, for example as a rank categorization, of the usable difference value data from the difference value generations can be carried out depending on the quality value. For example, it is possible to assign a weighting factor to the difference value data according to the rank categorization. The difference value data for a specific object point with the highest quality value, for example, receives the highest weighting factor. Difference value data for this specific object point with a lower quality value only receives a low weighting factor.The weighting factor can be used for subsequent processing and, in particular, determine how the different weighted difference value data are related to one and the same object point. The weighted difference value data is made available to the generation module in a transferable format.

[0050] The weighting is therefore based on an assessment of the quality of the difference value data based on the quality value. The quality assessment can be absolute or relative to the recorded data quality of the difference value data. In addition to discrete algorithms, algorithms that incorporate an "n-to-n" relationship into the quality assessment can also be used.This makes it possible, for example, to increase the resulting quality of the analysis if the quality of the difference value data from a difference value generation from individual acquisitions from one acquisition angle is low by using the difference value data from difference value generation from individual acquisitions from several acquisition angles or if the quality of the difference value data from a difference value generation from individual acquisitions in one radiation energy level is low by using the difference value data from difference value generation from several different radiation energy levels, each at the same object point.

[0051] Furthermore, the overall evaluation module can perform a plausibility check. If at least three weighted difference value data sets are available for one and the same object point, the overall evaluation module can perform a comparison of the weighted difference value data available for a specific object point and can be configured such that, if the first weighted difference value data deviates from the second and third weighted difference value data to a set degree, the first weighted difference value data is discarded and no longer made available for transfer to the generation module.

[0052] The generation module is designed to assign the coordinate data from the weighted differential value data of the individual image acquisition units, including the platform position data, to a uniform spatial coordinate system. Different angular positions of the platform result in different coordinate data for the weighted differential value data of one and the same object point on the vehicle. Nevertheless, all weighted differential value data relating to one and the same object point can be clearly assigned to this object point, since the evaluation unit also knows the platform coordinate data.

[0053] On this basis, a digital surface contour image of the vehicle is first generated in the uniform spatial coordinate system.

[0054] The digital surface contour image thus generated is initially based only on the coordinate data.

[0055] The generation module then supplements the vehicle's digital surface contour image by adding additional data from the weighted difference value data based on the coordinate data to create a digital surface texture image of the vehicle. The additional weighted difference value data is the data from the data tuples that is not coordinate data, specifically data on the differences in light intensity values, weighting data, wavelengths and radiant energy levels, and so on.

[0056] The digital surface texture image is provided in an output format.

[0057] The digital surface texture image provides a particular advantage in that it provides comprehensive information on the overall condition, damage, and previous touch-ups and repairs related to the vehicle surface.

[0058] In particular, it provides information on the following properties of the vehicle’s surface: Determination of the relative age of the paint on a painted surface Determination of the thickness of a clear coat layer Visual representation of defects and irregularities on a painted surface Detection of scratches or damage on a paint surface and in underlying layers Determination of the UV transmittance of glass surfaces Assessment of the aging state of plastic surfaces Detection of breakages and cracks on plastic surfaces Detection of color differences on painted surfaces Determination of the degree of gloss and smoothness and surface quality on painted surfaces

[0059] A further advantage is the non-contact determination of properties under conditions in which all potentially disturbing or distorting influences can be excluded.

[0060] The vehicle surface analysis system has the particular advantage of enabling the creation of a uniform digital surface texture image of a vehicle based on several different individual image acquisition units.

[0061] For one and the same object point, pixel data from individual acquisitions by different image acquisition units are available.

[0062] Although the expert is inclined to increase the significance of an analysis result by accumulating a large database, it was surprisingly found that, on the contrary, an improvement in the quality of the analysis result can be achieved by determining difference values ​​from the collected database and thus initially reducing the database.

[0063] Furthermore, the following is particularly advantageous: First, the individual image acquisition units can advantageously support each other. For example, images recorded in a specific wavelength range can provide high information quality for certain sections of the vehicle surface, but not for other sections, while conversely, images recorded in a different wavelength range can provide particularly high information quality for these other sections.

[0064] Secondly, it is advantageous that the vehicle surface analysis system independently recognizes the quality and thus the suitability for use of the pixel data from different image recordings and uses the pixel data that provide a higher quality of the digital surface texture image.

[0065] Third, it is advantageous to first subtractively map the pixel data by generating difference values. Subsequently, the difference values ​​are then cumulatively mapped to further improve the quality of the analysis result.

[0066] Furthermore, the digital surface texture image offers the further advantage of being able to display the vehicle in different views, for example with closed or open doors, as well as in different perspectives, for example as a 360° view.

[0067] A particular advantage is that the result is a digital image of the vehicle that provides a sufficient database, particularly for the following two important applications.

[0068] First, the digital surface texture image is suitable for recording vehicle damage and automatically determining the necessary repair measures, specifying the required spare parts and work steps, and deriving the repair costs from this. All of this can be done digitally. A particular advantage here is that damage concealed by overpainting can be detected and displayed.

[0069] Second, by further processing the digital image, a vehicle valuation can be carried out automatically, for example, to support the remote sale of used vehicles. Additional data such as vehicle age, mileage, number of previous owners, and other value-determining factors can be included in the automated calculation of the vehicle value.

[0070] Of particular advantage are the security against manipulation and the reliable documentation of a vehicle damage report or a vehicle assessment.

[0071] A further advantage lies in the modularity of the vehicle surface detection system. Depending on requirements—i.e., depending on the quality requirements or the vehicle surface types to be analyzed, such as paint surfaces, glass surfaces, or plastic part surfaces—the vehicle surface analysis system can be equipped with various individual image acquisition units, or only specific image acquisition units can be involved in image acquisition.

[0072] The vehicle surface analysis system according to the invention is based, in particular, on the fact that all individual image acquisition units, and thus all image recordings, are calibrated to one and the same coordinate system. The pixel data is acquired multiple times both due to the different configuration of the image acquisition units and because acquisitions can be made at different angular positions due to the rotational movement of the vehicle on the platform. The quality of the acquired pixel data is increased because even uncertain statements from a single acquisition can be used by incorporating other uncertain statements from one or more additional individual acquisitions.

[0073] The digital surface texture image can advantageously be represented as multiple layers, which is why this can also be referred to as multi-layer information. Each layer contains different types of information, for example, surface damage in one layer and hidden repairs of previous damage in another layer. This provides the viewer or, for example, a vehicle appraiser with more information than with a purely visual representation of the vehicle's surface.

[0074] The result of the vehicle surface detection is provided as a digital surface texture image with several types of information, so that the digital surface texture image is designed to represent a digital twin of the surface of the detected vehicle.

[0075] The digital surface texture image as a digital twin also enables the information aggregated in it to be further processed automatically, for example for a repair calculation.

[0076] According to an advantageous development, the vehicle surface analysis system comprises a housing. The vehicle positioning unit is arranged within the housing. The housing has the particular advantage that defined lighting conditions can be achieved during the acquisition processes in both the visible and non-visible spectrum and, in particular, that stray light sources are shielded. This can advantageously increase the accuracy of the acquired object data. At the same time, the environment and, in particular, the personnel are protected from light sources of the individual image acquisition units, which is particularly relevant for UV light radiation sources with higher radiation 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, the optical image capture unit is preferably also arranged within the housing.

[0077] According to another development, the vehicle registration system includes a comparison module. The comparison module contains a database with data relating to a normative digital image. The database can be available as an internal or external database. An external database offers the additional advantage of centralized data maintenance. The normative digital image describes a vehicle of the same type, as it corresponds to its original manufacturing condition.

[0078] The comparison module is designed to compare the digital surface condition image with the normative surface condition image and generate a digital difference image. The digital difference image describes the extent to which the condition of the vehicle being recorded deviates from the original manufacturing condition of the vehicle surface. The digital difference image thus indicates, in particular, the degree of aging, damage, and repairs to the surface, particularly paint touch-ups and repainting of subsurface damage. This can thus be output, for example, as a condition report. This vehicle condition information can also form the basis for statements regarding required repairs, particularly paint repairs, or the value of the vehicle in question.

[0079] A further development provides for the vehicle registration system to include a repair calculation module. The repair calculation module has a database containing repair data, which includes data on repair work times and repair costs, as well as, if applicable, spare parts such as plastic parts of the vehicle surface. This database can also be available as an internal database or as an external database.

[0080] Data on spare parts indicates which spare parts are required for a repair, depending on the type of damage. Data on repair labor times indicates the repair times, usually referred to as labor values, required to complete a repair. Data on repair costs indicate the prices at which spare parts and repair labor are available. Therefore, repair costs are preferably stored in the database as unit prices.

[0081] The repair calculation module is designed to create a repair assessment based on the digital difference image and the repair data, wherein the repair assessment includes spare parts required for a repair, repair labor times to be spent, and repair costs.

[0082] This advanced training makes it possible to obtain automated, tamper-proof information about required repairs and their costs. This allows for automated cost estimates to be generated, resulting in significant savings in personnel costs.

[0083] In an advantageous further development, it is also possible to automatically trigger spare parts orders based on the repair assessment.

[0084] Following further development, the vehicle registration system includes a valuation module. The valuation module contains a database with vehicle price data. This database can also be an internal or external database.

[0085] Vehicle price data includes, for example, list prices depending on the vehicle configuration, price tables depending on the vehicle age, mileage, number of previous owners and any additional price data.

[0086] The valuation module is designed to create a valuation based on the vehicle price data from the digital surface condition image, the digital difference image, and the repair data. This can preferably be a value reduction or increase based on the surface condition, which expresses the extent to which the surface condition of the vehicle, relative to its age, is above or below the average of comparable vehicles. According to this development, a solution is advantageously available to support the determination of a vehicle's commercial value. This solution is automated and thus requires minimal effort, is tamper-proof, and can be reliably documented.

[0087] The invention is illustrated by way of example with reference to Fig. 1Schematic representation in plan view Fig. 2Schematic diagram of image recordings from acquisition processes Fig. 3Block diagram with repair calculation module and value determination module explained in more detail.

[0088] Fig. 1 shows a schematic representation of a first embodiment of the vehicle surface analysis system.

[0089] The position of the vehicle 4 relative to the optical image capture unit 2 can be determined by means of a vehicle positioning unit. For this purpose, the vehicle positioning unit 1 has a rotatable platform 11. The vehicle 4 can be driven onto this platform as intended. The arrow illustrates the rotatability of the platform 11. Another element of the vehicle positioning unit 1 is the platform position detection unit 12. It detects the rotational position and thus the angular position of the platform 11 and transmits this to the evaluation unit 3 via a wired data connection.

[0090] Fig. 1 further shows the optical image capture unit 2. In the present embodiment, this has three individual image capture units 21. Each of the individual image capture units has a light radiation source 211 and an image camera 212.

[0091] In the exemplary embodiment, a first of the three individual image capture units 21 is designed with an infrared light radiation source and an infrared image camera, a second of the three individual image capture units 21 is designed with a light radiation source and an image camera, each in the visible light wavelength range, and a third of the three individual image capture units 21 is designed with an ultraviolet light radiation source and an ultraviolet camera.

[0092] The image capture area 22 of each individual image capture unit 21 is aligned so that the vehicle 4 located on the platform 11 is captured. In the exemplary embodiment, the image capture areas 22 overlap.

[0093] In the exemplary embodiment, the positioning unit 23 is designed as a frame. The individual image acquisition units 21 are rigidly mounted on this frame, thus fixing their positional relationship to each other and to the platform 11. This design allows, after calibration, all image point data acquired by the individual image acquisition units 21 for object points of the vehicle to be assigned to a uniform spatial coordinate system.

[0094] In the embodiment according to Fig. 1 The vehicle surface analysis system comprises a housing 2 which is impermeable to the wavelength ranges of all three individual image acquisition units. In particular, the vehicle positioning unit 1 as well as the optical image acquisition unit 2 are arranged in the interior of the housing 5. This has a closable opening (in Fig. 1 not shown) through which the vehicle 4 can be driven into the interior onto the platform 11 and can be driven out again after detection has taken place.

[0095] Fig. 1 further shows the evaluation unit 3, which in the exemplary embodiment is a computer system consisting of a computer with software.

[0096] The evaluation unit 3 is connected to the three individual image acquisition units 21 via data connections and receives the pixel data of the object points on the vehicle surface of the vehicle 4 from image recordings, also called individual acquisitions. (The data connections to the evaluation unit 3 from the individual image acquisition units 21 and from the platform position acquisition unit 12 are shown without reference symbols.)

[0097] The evaluation unit 3 has according to Fig. 1 a difference value generation module 31, a difference value evaluation module 32, an overall evaluation module 33 and a generation module 34.

[0098] The individual image recordings are assigned using the difference value generation module 31. In the present exemplary embodiment, several image recordings are available from each individual image acquisition unit 21, each of which was recorded with different radiation energy levels. According to the first exemplary embodiment, the difference value generation module 31 is designed such that the image recordings of the different individual image acquisition units 21, i.e., with different wavelength working spectra but the same radiation energy level, are assigned, and that the difference in the light intensity values ​​is determined from each assignment and provided as a difference value.

[0099] The difference value evaluation module 32 receives the difference values ​​from the difference value generation module 31 and is configured to evaluate the data quality of the difference values. Each of the obtained difference values ​​is evaluated based on a comparison with difference values ​​for neighboring object points to determine whether it is a plausible difference value. In the present embodiment, a difference value that meets this criterion is categorized as usable and forwarded to the overall evaluation module 33 as a usable difference value. Otherwise, the difference value is categorized as unusable and thus discarded and not forwarded. In this way, all received difference values ​​are processed sequentially by the difference value evaluation module 32.

[0100] The difference value evaluation module 32 thus provides the feature that only sufficiently reliable data are included in the surface quality image of the vehicle to be created later, so that the surface quality image also has a high degree of reliability.

[0101] In the overall evaluation module 33, the usable difference value data obtained from the difference value evaluation module 32 are assigned to one another on the basis of the coordinate data for the object points and evaluated in relation to one another.

[0102] The assignment of the usable difference value data as belonging to the same object point is based on the fact that the evaluation unit 3 is able to assign all individual image acquisition units 21 to a uniform spatial coordinate system by means of the defined position of the individual image acquisition units 21 based on their position determination by the positioning unit 23 and by means of the angular position of the platform 11 and thus of the installed vehicle 4 known by the platform position acquisition unit 12.

[0103] After the assignment has been completed, the overall evaluation module 33 in the present embodiment compares the quality value of the usable difference value data. As a result of the comparison, the compared usable difference value data are sorted, for example, according to the rank of the quality value, and assigned a weighting factor. The usable difference value data with the highest quality value receive the highest weighting factor, and vice versa. The weighting factor corresponds to the quality value. The usable difference value data for each detected object point are provided to the generation module 34 together with the weighting factor.

[0104] The generation module 34 assigns the coordinate data from the usable difference value data to the uniform spatial coordinate system, including the platform position data.

[0105] Based on the coordinate data, a digital surface contour image of the vehicle 4 is first generated in the unified spatial coordinate system. The digital surface contour image is formed by a point cloud that corresponds to the geometry of the vehicle surface.

[0106] Subsequently, the additional data from the weighted difference value data are added to the digital surface contour image of the vehicle 4 using the coordinate data, thus generating a digital surface texture image of the vehicle 4.

[0107] This digital surface texture image is then made available for output. In the exemplary embodiment, the digital image is transmitted as a file. The digital surface texture image can also be visualized on a monitor as a data output unit. However, the digital surface texture image goes beyond mere visualization. In particular, in the exemplary embodiment, it is possible to adjust the visualization according to specific analysis criteria, such as paint thickness, paint age, or covered corrosion spots. Depending on the analysis criterion, the visualization can be adjusted so that it deviates from the visual impression and highlights the gradual development of the analysis criteria in color.

[0108] Fig. 2 shows an exemplary embodiment of a possible system for image recordings from acquisition processes. The abscissa represents the wavelength λ and the ordinate the radiation energy level.E. In the exemplary embodiment, the images are captured by three individual image capture units 21, with the first individual image capture unit 21 operating in the wavelength operating spectrum λ1 in the UV range, the second individual image capture unit 21 operating in the wavelength operating spectrum λ2 in the visible light range, and the third individual image capture unit 21 operating in the wavelength operating spectrum λ3 in the IR range. Each of the image capture units generates three images with different radiation energy levels E1, E2, and E3.

[0109] The image recordings λ1E1 to λ3E3 are transmitted to the evaluation unit. In the exemplary embodiment, an assignment is first performed within a wavelength working spectrum, and thus, for example, the difference value generation module generates a difference value from the image recordings λ1E1 and λ1E2, as well as a further difference value from the image recordings λ1E2 and λ1E3. In the same way, difference values ​​are generated from the image recordings λ2E1 and λ2E2, as well as from λ2E2 and λ2E3, and so on. Furthermore, additional difference values ​​are generated between the image recordings of different wavelength working spectra but the same radiation energy levels, such as from the image recordings λ1E1 and λ2E1, and so on. However, difference values ​​from any "n-to-n" assignments, such as λ1E2 and λ3E3, are also possible.

[0110] Fig. 3 shows a further embodiment in a block diagram representation, whereby both a repair assessment and a value determination can be carried out here.

[0111] For the individual image acquisition units 21 of the optical image acquisition unit 2, the difference value generation module 31, the difference value evaluation module 33, the overall evaluation module 33 and the generation module 34, the explanations for the embodiment according to Fig.1 and Fig. 2 .

[0112] After the digital surface texture image has been generated by the generation module 33, it is processed in the embodiment according to Fig. 3transferred to a comparison module 35. The comparison module 35 contains a database 351 as a database with data on normative digital surface texture images of many vehicle models with different equipment, which also includes the normative surface texture image of the detected vehicle 4. This database is regularly supplemented with new vehicle models appearing on the market. The comparison module 35 recognizes the vehicle model of the detected vehicle 4 based on the digital surface texture image and compares the digital surface texture image of the detected vehicle 4, which it received from the generation module 34, with the normative surface texture image of the corresponding model, which it took from the database 351, and generates a digital difference image.The digital difference image contains information about deviations of the recorded vehicle 4 from an originally manufactured vehicle, so that hidden damage in particular can be identified.

[0113] The digital difference image is made available to both the repair evaluation module 36 and, in parallel, to the value determination module 37.

[0114] The repair calculation module 36 has a database 361 with repair data. The repair data consists of model-specific data on spare parts, repair labor times, and repair costs, with the repair costs stored as unit prices. Based on the digital difference image and the repair data, the repair evaluation module determines which spare parts are required for a repair, which repair labor times are required, and which repair costs will be incurred according to the stored unit prices, and outputs this as a repair evaluation.

[0115] Cumulatively or alternatively, the commercial value of the recorded vehicle 4 can be determined using the value determination module 37.

[0116] For this purpose, the valuation module 37 has a database 371 with vehicle price data. The vehicle price data contains, in particular, data on list prices and age- and mileage-dependent market prices for many vehicle models, including data on the model of the recorded vehicle 4. Based on the vehicle price data, the digital difference image, and the repair data, the valuation module 37 creates a vehicle valuation. Optionally, additional vehicle data, such as the number of previous owners, can also be manually entered via the digital image and the digital difference image and taken into account by the valuation module 37 when creating the vehicle valuation. Reference symbols used

[0117] 1Vehicle positioning unit 11Platform 12Platform position detection unit 2Optical image acquisition unit 21Single image acquisition unit 211Light radiation source 212Image camera 22Image acquisition area 23Positioning unit 3Evaluation unit 31Difference value generation module 32Difference value evaluation module 33Total value evaluation module 34Generation module 35Comparison module 351Data base of the comparison module 36Repair calculation module 361Data base of the repair calculation module 37Value determination module 371Data base of the value determination module 4Vehicle 5Enclosure

Claims

1. A vehicle surface analysis system, comprising a vehicle positioning unit (1), an optical image acquisition unit (2) and an evaluation unit (3), wherein 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, wherein the platform (11) is rotatable about a vertical axis of the placed vehicle (4), and wherein the platform position detection unit (12) is designed to record platform position data and to provide them in a transmittable form to the evaluation unit (3), wherein the optical image acquisition unit (2) comprises several individual image acquisition units (21) and a positioning unit (23), wherein each of the individual image acquisition units (21) comprises a light radiation source (211) and an image camera (212), wherein each of the individual image acquisition units (21) has an image acquisition range (22), wherein the image acquisition range (22) covers a surface of the vehicle (4) at least in sections, wherein each of the individual image acquisition units (21) has a wavelength work spectrum different from a wavelength work spectrum of another one of the individual image acquisition units (21), wherein the light radiation source (221) of each of the individual image acquisition units (21) is designed to provide a plurality of different radiation energy levels, wherein the positioning unit (23) determines a positional relationship of the individual optical image acquisition units (21) with respect to each other and with respect to the vehicle positioning unit (1), wherein the individual image acquisition units (21) are designed to acquire pixel data of an image acquisition of object points of the vehicle (4) and to provide them in a transmittable form to the evaluation unit (3), wherein the pixel data contain wavelength-related and radiation energy level-related light intensity value data and coordinate data of the object points, wherein the evaluation unit (3) comprises a difference value generation module (31), a difference value assessment module (32), an overall assessment module (33) and a generation module (34), wherein the difference value generation module (31) is designed to map the light intensity value data of the image acquisition for an object point by means of the associated coordinate data to the light intensity value data of at least one further image acquisition for the same object point, to compare the light intensity value data in a light intensity value data comparison and to generate difference value data therefrom, as well as to provide the difference value data to the difference value assessment module (32), wherein the difference value assessment module (32) is designed to carry out an evaluation of a quality of the difference value data and, on the basis of the evaluation, to carry out a categorization in usable difference value data when an adjustable quality value of the difference value quality is reached and in non-usable difference value data when the quality value is not reached, and to provide usable difference value data in a transmittable form to the overall assessment module (33), wherein the overall assessment module (32) is designed to use the coordinate data for the object points to map the usable difference value data from the light intensity value data comparison to further usable difference value data from a further light intensity value data comparison, to perform a comparison of the quality value of the usable difference value data from the light intensity value data comparison with the quality value of the further usable difference value data from the further light intensity value data comparison, and to perform a weighting of the usable difference value data, depending on the quality value, as weighted difference value data, wherein the generation module (33) is designed to map the coordinate data from the pixel data to a uniform spatial coordinate system by including the platform position data, to generate a digital surface contour image of the vehicle (4) in the uniform spatial coordinate system, to supplement the digital surface contour image of the vehicle (4) by adding the weighted difference value data on the basis of the coordinate data to create a digital surface quality image of the vehicle, and to provide the digital surface quality image in a displayable manner.

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

3. The vehicle surface analysis system according to any one of the preceding claims, characterized in that the vehicle recording system comprises a comparison module (35), wherein the comparison module (35) includes a database with data on a normative digital surface condition image, wherein the comparison module (35) is designed to carry out a comparison between the digital surface condition image and the normative surface condition image and to generate a digital difference image.

4. The vehicle surface analysis system according to claim 3, characterized in that the vehicle recording system comprises a repair calculation module (36), wherein the repair calculation module (36) comprises a database with repair data, wherein the repair data include data on spare parts, on repair work times and on repair costs, wherein the repair calculation module (36) is designed to generate a repair assessment on the basis of the digital difference image and the repair data, wherein the repair assessment comprises spare parts required for a repair, repair work times to be spent and repair costs.

5. The vehicle surface analysis system according to any one of the preceding claims 3 and 4, characterized in that the vehicle surface system comprises a valuation module (37), wherein the valuation module (37) comprises a database with vehicle price data and wherein the valuation module (37) is designed to generate a vehicle valuation based on the vehicle price data, the digital difference image and the repair data.