Method for determining at least one piece of object information of a real object using image processing, as well as an electronic identification system

Abstract

The invention relates to a method for determining at least one object information of a real object (3), comprising: - Marking areas (5) to be recorded with a detection device (4) on a surface (6) of the object (3) by attaching at least one marking element (7) within a respective area (5), - Capturing the real object (3) with the capture device (4) by capturing image information of the marked areas (5), - Generating a virtual reconstruction (8) of the real object (3) based on the captured image information of the marked areas (5) by an electronic evaluation unit (4), - Determining at least one object information of the real object (3) on the basis of the generated virtual reconstruction (8) of the object (3) by the electronic evaluation unit (4). Furthermore, the invention relates to an electronic determination system (1).

Description

[0001] The invention relates to a method for determining at least one object information of a real object.

[0002] Furthermore, the invention relates to an electronic determination system with an electronic detection unit and an electronic evaluation unit.

[0003] Today's technology offers various approaches to filtering image information and reducing it to the relevant pixels. Algorithms can be used to locate particularly prominent features or pixels, such as corners. After the image has been captured, the corresponding pixels are searched for and filtered in the captured image.

[0004] For example, WO 2010 / 027391 A2 discloses a method for high-resolution three-dimensional image capture using an unfocused camera. A lens concealed by a mask with two sets of apertures can be assigned to a corresponding device. A first set of apertures generates a plurality of defocused images of an object, which are used to determine the camera position. The second set of optical filters generates a plurality of defocused images of a projected marking pattern on the object. These marking patterns are projected using a projector.

[0005] For example, DE 10 2006 013 318 A1 discloses a 3D reconstruction of static scenes through a unified combination of geometric and photometric methods. In particular, industrial image processing increasingly requires the reconstruction of the three-dimensional structure of workpieces or their surfaces from two-dimensional image data. To enable a 3D reconstruction of static scenes from 2D image data, which generates dense and location-independent precise distance data under a wide variety of boundary conditions, it is proposed to solve the reconstruction problem at the algorithmic level by combining or merging known methods.For this purpose, the intensity distribution, which is transformed into a point-like light source by the lens and the image sensor, is estimated from a single or several different focused pixel-synchronous images of the scene based on the Depth from Defocus (DFD) method.

[0006] WO 2013 / 137733 A1 discloses a method for extracting information about one or more spatial objects by a person, which method is designed to analyze the sequence of images in real time, use image analysis techniques, and extract information about said one or more objects and communicate at least part of this information to the person in real time via the output when the information is extracted using image analysis techniques, wherein the information about another object includes more than one person. The spatial distance between two objects, the spatial relative angle between two substantially linear objects, and / or an indication of the perceived accuracy of the extracted information.

[0007] Furthermore, DE 10 2016 002 186 A1 discloses a method for determining a geometric measurement value of an object, wherein at least one visual image of the object is recorded in a recording step.

[0008] With such conventional methods, numerous pieces of image information, or even the entire image, must be processed. Algorithms for filtering this information and detecting these prominent pixels are complex and error-prone. Furthermore, there is usually only limited influence on which pixels are to be identified. However, since the geometry is reconstructed based on these pixels, this is of central importance. Furthermore, these methods cannot be applied in poor lighting conditions, low contrast, or darkness.

[0009] However, such methods have the disadvantage that inaccuracies occur when extracting the points relevant for the measurement and problems arise when achieving the desired accuracy and reliability.

[0010] An object of the present invention is to be able to generate a virtual reconstruction of a real object in a simpler, in particular computationally minimized, manner in order to be able to use this for an analysis of the real object.

[0011] This problem is solved by a method and an electronic determination system according to the independent patent claims. Useful further developments arise from the dependent patent claims.

[0012] One aspect of the invention relates to a method for determining at least one object information of a real object, comprising: - Marking areas to be recorded with a detection device on a surface of the object by applying at least one marking element within a respective area, - Capturing the real object with the capturing device by capturing image information of the marked areas, - Generating a virtual reconstruction of the real object based on the captured image information of the marked areas by an electronic evaluation unit, - Determining at least one piece of object information of the real object on the basis of the generated virtual reconstruction of the object by the electronic evaluation unit.

[0013] The proposed method allows a real object to be analyzed in the simplest way by determining at least one piece of object information or several pieces of object information based on the virtual reconstruction. In contrast to conventional methods, which were already explained at the beginning, the real object is not fully captured, but rather specifically marked areas are captured. This allows time savings and, in particular, a reduction in workload to be achieved during the capture stage. Subsequently, the virtual reconstruction, i.e., a computer-based reconstruction, of the real object can be generated, particularly on the system side. Based on the captured image information, only those areas of the real object that have been specifically marked are taken into account.This makes reconstruction easier and requires less computing power and therefore less processing time.

[0014] The capture device can be an image capture unit or an image capture system, such as a camera. With the help of the capture device, two-dimensional (2D) images or image information of the real object can be captured, recorded, or captured. In particular, the specially marked areas are taken into account. Thus, a three-dimensional (3D) reconstruction of the real object can be performed using 2D images of the marked areas. Thus, virtual reconstruction, for example, is a computer-based 3D reconstruction of the real object.

[0015] For example, the real object may be an object or item to be analyzed, checked or measured.

[0016] The areas from which 2D images are to be obtained or recorded are marked by manually or automatically attaching or applying at least one marking element. For example, the marking element is a specially provided marker, which in turn is an item or object. The markings are, of course, many times smaller than the object to be examined. The marking elements can, for example, be detachably attached, arranged or positioned on the areas to be examined or recorded at any time. As a possible example, the marking elements can be glued to the surface of the areas to be recorded.

[0017] For example, the proposed method can be used for measurement purposes, object examinations, testing procedures, material investigations, product analyses, and object measurements. Any real object can be reconstructed three-dimensionally in a very simple way without complex computational effort in order to obtain desired information about the real object. One application, for example, could be an object being examined within a wind tunnel. Using the object information, information about the object's aerodynamics can be determined. In particular, deformations that occur on the object during testing in the wind tunnel can be determined through the virtual reconstruction.

[0018] By applying the special marking elements and capturing the object based on the marked areas, software-supported feature detection or pixel detection, which is complex and computationally intensive, can be dispensed with. Using the marking elements, the captured images or the captured image information can be provided as filtered images, since the image information and thus the captured images have already been reduced to essential points, i.e., the marked areas, using the marking elements. This reduces computing power and, in particular, the workload during the subsequent processing of the captured images or the captured image information.

[0019] A further advantage of applying marking elements and capturing the object based on these marking elements is, for example, that post-processing of the images or the captured image information and filtering the captured images for prominent points or pixels can be simplified, since these prominent points are already present due to the application of the marking elements. The risk of errors is very low, since the relevant points are clearly defined by imprinting them on the geometry, i.e., by applying the marking elements, before the image is captured or before the real object is captured, and these points can be clearly and easily identified during subsequent image processing. In addition, the user, for example, has control over which areas or points of the real object are to be examined.This not only significantly reduces the amount of information to be processed, but also ensures that all desired information is included. Depending on the application, the marking elements can be applied individually, depending on the type of object and the type of object involved.

[0020] In particular, multiple marking elements can be provided for each area to be recorded. In particular, any number of marking elements can be applied to the surface of the object.

[0021] In particular, the proposed method is a computer-implemented method. In particular, the proposed method can be used in industrial image processing.

[0022] In one embodiment, it is provided that the virtual reconstruction of the real object is generated based on a photogrammetry method, in particular using a structure-from-motion method, wherein object recognition, a measurement of the geometric structure of the object and / or movement detection of the object are carried out with the generated virtual reconstruction of the real object and are taken into account when determining the at least one piece of object information. Thus, depending on the object in question and which object-specific information is to be determined or ascertained, the virtually reconstructed object, such as a three-dimensional virtual computer-based object, can be analyzed or evaluated accordingly. Thus, for example, the object in question can be provided as object information using object recognition.This is important, for example, in manufacturing, such as a production assembly line. Furthermore, by measuring the geometric structure of the object, the size, dimensions, and / or measurements of the object can be determined. This can be advantageously used, for example, in the surveying of properties or agricultural areas. Motion detection, in turn, can be used to detect external movements and / or the object's own movements. This information can be used to determine whether areas of the object have moved, for example, have become deformed. This can be advantageously used, for example, in the development and testing phases in the automotive industry.

[0023] For example, the capture device can be used to capture a 3D geometry relating to the object. For this purpose, computer vision methods are used to convert the captured images into a virtual computer-based representation. The structure-from-motion method is primarily used here. This method allows the 3D geometry of the object to be captured to be generated in the computer or in a processing unit from 2D images taken from different perspectives, for example. For this purpose, individual pixels such as edges, corners or image details are tracked across the various images. For this purpose, the image information can be reduced to the relevant points in order to ensure the assignment of the pixels from one captured image of the object to the corresponding pixels in the other captured images.Thus, with the help of the captured image information concerning the marked areas, such images can be provided as information in order to be able to carry out the reconstruction on this basis.

[0024] Photogrammetry, also known as image measurement, is a group of non-contact measurement and evaluation methods used to indirectly determine the position and shape of an object from photographs by image measurement, as well as to describe its content by image interpretation.

[0025] In one embodiment, it is provided that the generated virtual reconstruction of the real object is compared with a virtual reference object of the real object, wherein a comparison result is taken into account when determining the at least one piece of object information. This allows, in particular, changes in the object compared to a basic state or initial state to be detected or determined. This is particularly advantageous during product testing or quality assurance. A virtual reference object, i.e., a three-dimensional reference body, can be provided to the electronic evaluation unit with respect to the real object. Thus, a comparison can be carried out after the virtual reconstruction has been generated.In particular, the specially marked areas, i.e. by means of the marking elements, can be compared in order to be able to identify corresponding deviations, changes or other modifications.

[0026] For example, the comparison result can be used to determine a deformation and / or deformation of at least a partial area of ​​the real object and provide this information as at least one item of object information. The marked areas or respective partial areas, which extend, for example, between two marking elements, can be examined to determine whether deformations or deformations are present. Thus, it can be determined whether the real object exhibits a change in state compared to a baseline state, and in particular a change in its shape or geometry. This can be advantageously used for quality assurance and defect detection of products, objects, or other manufactured parts.

[0027] In one embodiment, it is provided that, along with the image information of a respective region, images are provided of at least one marking element applied in the respective region. As already mentioned at the beginning, the application of the special marking elements means that a complete capture of the object is not necessary, since the capture of the object and the subsequent virtual reconstruction takes place on the basis of these special markings or marking elements and thus on predefined prominent pixels. It is particularly advantageous if, optionally, a respective marked region and a respective marking element present therein are captured from or from different perspectives and / or from different views. This, in turn, is advantageous for the reconstruction of the object.

[0028] In one embodiment, the attached marking elements provide predefined image features for generating the virtual reconstruction. Thus, depending on the circumstances or situation regarding the object and the object information to be determined, a specific arrangement or specific attachment of the marking elements can be carried out. Thus, the areas or points to be examined or analyzed using the virtual reconstruction can be defined in advance. This has the primary advantage that image features can be specified in advance and do not have to be extracted or filtered from the recorded images using complex, computationally intensive, and cost-intensive processes.

[0029] In other words, the applied marker elements can be used to specify artificial, particularly relevant image features or pixels. This facilitates subsequent virtual reconstruction.

[0030] In one embodiment, the marking elements are attached to the surface of the object by means of adhesive bonding. This allows a respective marking element to be attached to a specific area on the surface of the object that is to be measured in the simplest way possible using an adhesive bond. By using the adhesive method or adhesive bonds, the marking elements can then be removed again non-destructively. This means that any object can be examined individually, since the marking elements, which can be removed or detached at any time, can first be attached to obtain object information and then the marking elements can be removed again. A further advantage here is that the marking elements can be realigned or adjusted during the measurement or during a measuring process.This means that at least some of the marking elements already applied can be removed and re-applied to a different position on the object.

[0031] A further advantage of gluing the marking elements to the surface is that they remain firmly glued even if the object is deformed or distorted. Unlike with the prior art, for example, if a projection unit or projector were used, the marking point would be repositioned accordingly in the event of deformation or distortion. This could lead to distortion, inaccuracy, or incorrect reconstruction.

[0032] In addition, the marking elements can be circular, dot-shaped, strip-shaped, square, or curved. In particular, the marking elements can be designed accordingly depending on the application or situation. Thus, any desired shape of the marking elements is conceivable.

[0033] In one embodiment, it is provided that the marking elements are at least partially fluorescent elements, wherein a brightness and / or a body color of the fluorescent elements is adapted such that the fluorescent elements optically differ from the real object when detecting the real object. This conceivable possibility with regard to the design of at least one of the marking elements can result in efficient and improved detection of the respective marked areas. As already mentioned, the marking elements are intended to specify striking image features or pixels in order to be able to recognize them quickly and easily without complex evaluation or extraction from the recorded images. For this purpose, it is important that the marking elements differ from or stand out from the remaining areas of the object that are not marked.This can be achieved with the help of fluorescence, as this causes the marking elements to glow compared to the rest of the object and thus to stand out optically from the rest of the object or to optically stand out from the object.

[0034] For example, the marking elements can be plate-shaped, such as a sheet of paper or an adhesive strip. In particular, the marking elements have a much smaller dimension than the object. In particular, the marking elements can have a material thickness of just a few millimeters.

[0035] The marking elements, which are at least partially designed as fluorescent elements, can be adapted in such a way that the brightness and the body colour are adjusted depending on the circumstances of the object and the surroundings of the object, so that the marking elements stand out optically or visually from the rest of the object.

[0036] It is provided that the marking elements are at least partially self-luminous elements, wherein a brightness and / or a light color of the self-luminous elements are adjusted such that the self-luminous elements visually differ from the real object when the real object is detected. Thus, in this exemplary embodiment, the marking elements can in turn be designed such that they visually stand out from the remaining areas of the object or stand out from the object in order to be able to detect the object efficiently. Due to the highlighted marking elements, these can be identified immediately and in the simplest way in the recorded images, so that prominent pixels or image features can be recognized immediately in the recorded images without complex computing effort.The marking elements can, for example, be designed entirely as self-illuminating elements or at least partially as self-illuminating elements. For example, the marking elements can be light points or luminous dots. Thus, they illuminate accordingly to stand out from the rest of the object. The light color and / or brightness of each marking element can be adjusted.

[0037] Depending on the application and how the object is to be measured and what the object is, some marking elements can be fluorescent elements and others can be self-luminous elements.

[0038] In one embodiment, the marking elements are fixedly attached to the surface of the real object. This can be achieved, in particular, by gluing the marking elements, thus ensuring a firm yet detachable attachment. The fixed positioning or attachment of the marking elements makes it easier to detect deformations, changes in state, and / or deformations of the object.

[0039] In a further aspect, the invention relates to an electronic determination system with an electronic detection device and an electronic evaluation unit, wherein the electronic determination system is designed to carry out a method according to the previous aspect or an advantageous development thereof.

[0040] For example, the aforementioned method can be carried out or implemented with the aid of the electronic system just mentioned, which has means.

[0041] In particular, the electronic determination system can be an image processing system or device. The electronic determination system can be used, in particular, in test benches, measuring stations, or quality assurance devices to analyze a wide variety of objects by performing a three-dimensional reconstruction based on specially recorded images.

[0042] For example, the electronic identification system may be a fully automated system or an at least partially automated system.

[0043] In particular, advantageous embodiments of one aspect of the invention can be regarded as advantageous embodiments of the other aspect and vice versa.

[0044] For use cases or application situations that may arise during the method and which are not explicitly described here, it may be provided that, in accordance with the method, an error message and / or a request to enter user feedback is issued and / or a default setting and / or a predetermined initial state is set.

[0045] The invention also includes further developments of the electronic determination system according to the invention that have features already described in connection with the further developments of the method according to the invention. For this reason, the corresponding further developments of the electronic determination system according to the invention are not described again here.

[0046] The invention also includes combinations of the features of the described embodiments.

[0047] Exemplary embodiments of the invention are described below. Shown are: Fig. 1 a schematic representation of an electronic determination system for determining object information of a real object; Fig. 2 an exemplary representation of a real object from Fig. 1, where special markings are applied to the surface of the object; Fig. 3 starting from the Fig. 2 a detection situation of the object, where the background is dark and the markings are illuminated accordingly in order to be able to detect them better; and Fig. 4 a schematic flow of a conceivable application case regarding the determination of object information.

[0048] The exemplary embodiments explained below are preferred exemplary embodiments of the invention. In the exemplary embodiments, the described components each represent individual, independently considered features of the invention, which also further develop the invention independently of one another and are thus also to be considered as components of the invention, either individually or in a combination other than that shown. Furthermore, the described exemplary embodiments can also be supplemented by further features of the invention already described.

[0049] In the figures, functionally identical elements are provided with the same reference numerals.

[0050] In the Fig. Figure 1 shows an example of an electronic, in particular automated, identification system 1. With the help of this electronic identification system 1, objects can be analyzed in order to obtain corresponding object information. For this purpose, the identification system 1 uses image processing, in particular photogrammetry.

[0051] The determination system 1 can have at least one electronic evaluation unit 2. The electronic evaluation unit 2 can be a computing unit or a computer. With the aid of the evaluation unit 2, the following information can be obtained regarding an object 3 to be analyzed or assessed (cf. Fig. 2) Image processing is performed. In this example, object 3 is an aluminum profile. However, object 3 can be any object, such as a production object or a manufacturing object. For example, object 3 can be captured or recorded using a capture device 4. Capture device 4 can be a camera system or a plurality of cameras.

[0052] One advantage of the present invention is that, in particular, image recordings can be reduced to clearly defined points. In other words, for the assessment or analysis of object 3, there is no complete, detailed recording of object 3, but rather specific points or areas are recorded. This eliminates the need for software-supported feature recognition, which above all saves computing power. Such features or image points are necessary in photogrammetry and in particular in image processing in order to be able to reconstruct a three-dimensional virtual object from a large number of 2D image recordings, for example. In order to remedy this situation and, above all, to save or reduce computing power and complexity, the areas or points required for the analysis of object 3 are specially marked.Thus, prominent points or areas to be examined can be marked accordingly in advance. For this purpose, areas 5 of which images should be taken can be marked. These areas 5 are distributed on the surface 6 of the object 3. At least one marking element 7 (cf. ) can be used to mark these areas 5. Fig. 2). These marking elements 7 can be, for example, colored and / or luminous dots, i.e. luminous dots, or colored or luminous stripes. As shown in the Fig. As can be seen in Figure 2, these marking elements 7 can be arranged as points distributed on the surface 6.

[0053] In particular, the marking elements 7 can be designed in such a way that they stand out from the object 3. As in the Fig. 2, these are colored dots on the surface 6 of object 3.

[0054] The marking elements 7 can, as already mentioned, be luminous or self-luminous or fluorescent dots or stripes or other geometric shapes. For better recognition or detection of the marking elements 7 and in particular of the areas 5 marked thereby, the ambient lighting in the test environment can be switched off or dimmed with respect to the analysis of the object 3. As a result, the dots or marking elements 7 are essentially the only thing that can be recognized in the recorded images, as is the case, for example, in the Fig. 3 can be seen. The rest of the recorded image may be completely black due to the darkness. The pixels of the marking elements 7 in the recorded images can therefore exhibit a significantly higher brightness than the surrounding pixels in the image. The detection and localization of these prominent luminous points or marking elements 7 is thus very easily possible, for example, by distinguishing between brightness values. This means that the images are already filtered during recording and reduced to the essential points. The positions of the marking elements 7 can be freely selected depending on the application.

[0055] The application of luminous objects, as the marker elements 7, of any shape and size, enables the easy identification and localization of relevant pixels in recorded images with respect to the object 3. This offers the advantage that the object 3 to be captured can be reduced to the most necessary information in order to subsequently reconstruct it. The process of detecting image features or pixels in images is thus eliminated, since only the most important points, which can be specified by the marker elements 7, are recorded during image capture. This significantly simplifies the subsequent processing of the images.Accordingly, computing power can be saved or reduced, since images or image information relating to the marked areas 5 or the marking elements 7 recorded by the recording device 4 require a significantly smaller amount of data to be processed. This is subsequently further advantageous for performing a virtual reconstruction of the real object 3 based on the recorded image information, i.e., recorded two-dimensional images. In other words, a virtual, in particular three-dimensional, reconstruction 8 can be generated or created here. This can be performed by the evaluation unit 2.

[0056] For this reconstruction, for example, a structure-from-motion method can be used.

[0057] In one embodiment, an adhesive tape can be used as a base for applying the marking elements 7. This adhesive tape can be designed such that it glows in the dark if it has previously been activated by light, such as LEDs, daylight, or UV light. Thus, a coating or a top side of the adhesive tape is a fluorescent element. For example, dots can be punched out of this adhesive tape using a hole punch, or other shapes, such as stripes, can be cut out. In other words, the marking elements 7 can be extracted or obtained from the adhesive tape. Thus, the marking elements 7 here are fluorescent adhesive pieces of the adhesive tape. For easy application, they can now be adhered to the prominent locations, positions, or areas 5 to be examined.Before detecting object 3, these fluorescent elements or points can be illuminated to activate them accordingly. If the illumination is then switched off, as shown in . Fig. 3 there is a black background, the glued-on shapes, i.e. the marking elements 7, shine and the rest of the surface 6 of the object 3 and in particular the surroundings appear black or dark. In this state or in this phase, the areas 5 can be detected and images can thus be taken. In these images or in this image information, in particular only the luminous areas, i.e. the areas 5, can be recognized or seen. These can then be localized via a brightness threshold value in the image processing, in particular by means of the evaluation unit 2. For example, the center point, i.e. the center point of the marking elements 7, can be determined from connected “bright pixels” in these recorded images.

[0058] In a further conceivable embodiment, the marking elements 7 can be designed to be self-luminous, so that they again stand out or stand out from the rest.

[0059] Further examples of this could be any object of any shape, type, and / or material for the use of the marking elements 7. As already explained, the detection of bright points can occur in comparison to a dark or black background. The reverse case is also conceivable, so that the marking elements 7 are black or glow black, and the background is bright. In particular, there should be sufficient contrast between the marking elements 7 and the object 3 and / or the background.

[0060] Another possibility or design of the marking elements 7 is the use of reflector markers, which are applied to the surface 6 and illuminated accordingly to achieve a very high local brightness value and filter it out. Instead of the brightness value, different colors can also be used for the marking elements 7. Thus, the marking elements 7 are always designed in such a way that they can be easily recognized in the recorded images and thus filtered out without complicated algorithms.

[0061] With the aid of the detection device 4, in addition to image recordings of the areas 5 of the object 3, video recordings can also be made. Furthermore, it is conceivable that the marking elements 7 function as markers that interact with any type of radiation, such as UV radiation or infrared radiation.

[0062] The aforementioned embodiment regarding the bonding of the marking elements 7 offers the primary advantage that, after the examination or after the detection of the object 3, the marking elements 7 can be detached or removed again. Furthermore, the marking elements 7 are designed, particularly in terms of their weight and material thickness, such that they do not influence the shape and material behavior of the object 3. Thus, the object 3 is detected by means of the detection device 4 and the marking elements 7, so that the complexity of a structure can be reduced. By bonding the marking elements 7 and, in particular, by attaching an additional physical element as a striking image characteristic or image feature, a stationary marking can be achieved.In other words, the position of the marking elements 7 can remain unaffected during a movement or deformation of the object 3. Thus, the markings remain at the same location on the object 3. In contrast, as is done in the prior art, for example, the markings can be positioned differently in projections after a deformation of the object 3. For the evaluation, a respective marking element 7 can be specifically selected and tracked independently of any deformation of the object 3. This allows, for example, movements and deformations of the object 3 to be recorded and provided as object information, for example, during the evaluation of the reconstruction 8.

[0063] Furthermore, the present invention offers the advantage that, unlike in conventional methods, the entire object does not have to be reproduced in high resolution, but only the selected, marked areas 5. The special marking elements 7 also enable the object 3 to be detected and subsequently reconstructed, even if poor lighting conditions exist for the detection.

[0064] The marking elements 7 are to be understood as being part of the recorded images, so that standard "structure-from-motion methods" can be applied, since artificial image marks, i.e. the marking elements 7, are inserted or attached, which are clearly identifiable and also firmly connected to the object 3.

[0065] In other words, the marker elements 7 form the relevant pixels in the captured images and provide the only color information in the images, allowing the images to be directly reduced to the essential information. This facilitates post-processing of the images and filtering of the images for prominent points, as these prominent points can be directly extracted from the image based on the brightness values ​​of the individual pixels. The susceptibility to errors is very low, as the relevant points are clearly defined by imprinting them on the geometry of the object 3 before the image is captured and can be clearly identified, for example, against a dark background. Furthermore, the user has control over exactly which points are to be detected. This not only greatly reduces the amount of information to be processed, but also ensures that all desired information is retained.

[0066] In the Fig. For better illustration, Figure 4 explains a possible application of the method according to the invention. In this case, object 3 can be a component of a vehicle. Any component or vehicle component of a vehicle is conceivable. For example, based on the virtual reconstruction of object 3, insights into the aerodynamics of object 3 can be obtained. For this purpose, an example of a measurement process or examination process for object 3 is described below.

[0067] In a step S1, object 3, which in this case may be a cooling air path of a vehicle or an underbody panel of a vehicle, can be positioned in a wind tunnel as a possible test setup. It is important that the air flow does not cause any deformations and / or deformations in or on object 3. In order to obtain such deformations, for example, as object information, the virtual reconstruction 8 of object 3 can be used. The photogrammetry method can be used particularly advantageously here.

[0068] Here, too, the marking elements 7 are glued in advance to potential weak points of the object 3. Likewise, marking elements 7 can be glued or attached to any location on the surface 6.

[0069] In order to be able to detect such deformations or other changes to the surface 6 of the object 3, a reference acquisition of the object 3 can be carried out in a step S2 before activating the wind tunnel. In other words, a acquisition of the object 3 in its basic state or initial position can be carried out in order to be able to create a virtual reference object of the real object 3. This can later be used to determine deformations. Now that the reference object is available, the actual measuring processes or the aerodynamic investigations in the wind tunnel can begin. After these measurements, the respective areas 5 marked with the marking elements 7 can be acquired in a step S3, for example from different perspectives, in order to be able to generate image information or two-dimensional images from them.

[0070] In a step S4, the acquired two-dimensional images relating to the specific markings can subsequently be evaluated by means of the evaluation unit 4 and by means of image processing programs, so that the virtual reconstruction 8 can be generated or created. Subsequently, in a step S5, the generated virtual reconstruction 8 can be compared with the reference object in order to be able to determine corresponding deformations or other changes to the object 3. In this case, the marking elements 7 identified in the images can be compared with the corresponding marking elements before and after the measurement. Thus, a geometric acquisition of component information, an assessment of leaks in the cooling air path as a possible object 3 or a cw influence of deformed underbody paneling parts as object 3 can be carried out.This insight from the simplest way to generate a virtual reconstruction 8 can increase the efficiency and range of a vehicle. This is because all components, i.e., a multitude of vehicle objects, can be assessed to determine whether one or more of them exhibit impairments or faulty areas. Thus, through targeted identification and reduction of, for example, a leak in the cooling air path, continuous improvements can be made to vehicle development. This can, for example, improve simulation processes in the development process of a product, such as a vehicle.

[0071] Furthermore, further applications or fields of application of the present invention are conceivable. Such use of luminous dots or marking elements 7 can be used for image processing in the field of robotics, particularly in production. Another application could be in agriculture, for example, in the surveying of land areas.

[0072] The marking elements 7 can also be used to determine the position of objects by robots, for example, in production. This allows the robots to precisely determine the position they are approaching. Another application could be in logistics. Marking goods, such as pallets in factory halls, is conceivable. This makes it possible to determine their presence and position, even in poor lighting conditions. These luminous dots can also be used in agriculture. Corners, edges, or other relevant positions in fields can be marked. This enables area determination using drones or high masts.

[0073] The application of the marking elements 7, such as luminous dots, as explained in the previous embodiments, offers the following advantages: • The luminous dots enable measurements to be taken in poor lighting conditions (extreme case: darkness), while other methods require good exposure of all adhesive dots (and other markers) in order to detect them. • The images of the luminous dots do not have to be sharp. This makes it possible to measure in very confined spaces (e.g. in the engine compartment of a vehicle), where the distance between the camera and the luminous dots can be very small. The method using the luminous dots also works below the close-up limit of the camera (lens) combination. This also makes the process very flexible in terms of camera selection. This is because only the luminous dots are visible in the respective images; the rest of the image is black. The center of these luminous dots is always in the same place, regardless of whether the dots are sharp or blurred. This means that the luminous dots can be located at different distances from the camera (within one image), meaning some (or all) of the points can be outside the plane of focus, without the quality of the process being affected. • Furthermore, the luminous dots are similar to other adhesive dots and are fixed to the object, meaning they move with the object, unlike projected patterns. • Due to the fluorescent properties of the luminous dots, it is not necessary to equip each individual dot / marker with a battery and / or cable, etc. They can therefore simply be glued to the object without impairing the movement of the components (contactless measurement) and without the need for additional measuring technology (apart from cameras and, for example, an LED that can activate all the luminous dots simultaneously).

[0074] The combination of these advantages makes the inventive method very flexible in its application, while simultaneously simplifying the code and reducing computational effort and error susceptibility compared to conventional (algorithmic) feature detection methods. Furthermore, the implementation of this method is very cost-effective and straightforward. List of reference symbols 1 electronic identification system 2 electronic evaluation unit 3 real object 4 Recording device 5 areas 6 Surface 7 marking elements 8 virtual reconstruction S1 - S5 steps

Claims

[1] Method for determining at least one item of object information of a real object (3), comprising: - Marking areas (5) to be recorded with a detection device (4) on a surface (6) of the object (3) by applying at least one marking element (7) within a respective area (5), wherein the marking elements (7) are at least partially self-luminous elements, wherein a brightness and / or a light color of the self-luminous elements is adapted such that the self-luminous elements are optically different from the real object (3) when detecting the real object (3). - detecting the real object (3) with the detection device (4) by detecting image information of the marked areas (5), - generating a virtual reconstruction (8) of the real object (3) on the basis of the captured image information of the marked areas (5) by an electronic evaluation unit (4), - Determining the at least one item of object information of the real object (3) on the basis of the generated virtual reconstruction (8) of the object (3) by the electronic evaluation unit (4). [2] Method according to claim 1, wherein the virtual reconstruction (8) of the real object (3) is generated on the basis of a photogrammetry method, in particular by means of a structure-from-motion method, wherein with the generated virtual reconstruction (8) of the real object (3) an object recognition, a measurement of the geometric structure of the object (3), and / or a movement recognition of the object (3) is carried out and taken into account in the determination of the at least one item of object information. [3] Method according to claim 1 or 2, wherein the generated virtual reconstruction (8) of the real object (3) is compared with a virtual reference object of the real object (3), wherein a comparison result is taken into account when determining the at least one item of object information, in particular a deformation of at least one partial area of ​​the real object (3) is determined with the comparison result and is provided as at least one item of object information. [4] Method according to one of the preceding claims, wherein the image information of a respective area (5) is used to provide images, in particular from different perspectives, of at least one marking element (7) applied in the respective area (5). [5] Method according to one of the preceding claims, wherein the attached marking elements (7) provide predetermined image features for generating the virtual reconstruction (8). [6] Method according to one of the preceding claims, wherein the marking elements (7) are applied to the surface (6) of the object (3) by means of gluing, in particular the marking elements (7) have a circular, a dot-shaped, a strip-shaped, a square or an arc-shaped shape. [7] Method according to one of the preceding claims, wherein the marking elements (7) are at least partially fluorescent elements, wherein a brightness and / or a body color of the fluorescent elements is adapted such that the fluorescent elements are optically different from the real object (3) when the real object (3) is detected. [8] Method according to one of the preceding claims, wherein the marking elements (7) are fixedly attached to the surface (6) of the real object (3). [9] Electronic determination system (1) with an electronic detection unit (4) and an electronic evaluation unit (2), wherein the electronic determination system (1) is designed to carry out a method according to one of the preceding claims.

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