Method, device, storage medium and program product for measuring quality of distortion parameters

Abstract

The method comprises the following steps: obtaining a first image of a test chart in a first spatial pose, the first image being obtained by shooting a display screen through a lens, the display screen being configured to display the test chart in the first spatial pose based on a distortion parameter to be tested, the first spatial pose being obtained by projecting and transforming a reference spatial pose based on a first conversion matrix, performing inverse projection and transformation on the first image based on the first conversion matrix to obtain a first target image, matching the first target image with a preset target image to obtain a matching result, and determining a quality measurement result of the distortion parameter to be tested according to the matching result, the spatial pose corresponding to the preset target image being related to the reference spatial pose. The quality measurement method for the distortion parameter provided in the embodiments of the present disclosure improves the accuracy of the measurement result.

Description

Technical Field

[0001] This disclosure relates to the field of virtual reality technology equipment, and in particular to a method, device, storage medium, and program product for measuring the quality of distortion parameters. Background Technology

[0002] Virtual reality (VR) technology devices (such as standalone VR headsets) have lenses positioned in front of the display screen. When a user wears a VR headset, their eyes view the image displayed on the screen through these lenses. VR headsets have extremely stringent requirements for the quality of lens distortion correction.

[0003] In related technologies, a camera is typically used to capture images of a checkerboard pattern displayed on a screen based on the distortion parameters to be tested, through a lens, to obtain an image to be processed. Then, key point detection is performed on the image to be processed, and the quality of the distortion parameters is measured based on the detection results.

[0004] However, in the process of realizing this application, the inventors discovered that the prior art has at least the following problems: the above-mentioned method is easily affected by the graininess of the screen and the sharpness of the lens edge when detecting key points, which makes the accuracy of key point detection low, and thus affects the accuracy of the final distortion parameter quality measurement results. Summary of the Invention

[0005] This disclosure provides a method, apparatus, storage medium, and program product for measuring the quality of distortion parameters, thereby improving the accuracy of distortion parameter quality measurement.

[0006] In a first aspect, embodiments of this disclosure provide a method for measuring the quality of distortion parameters, including:

[0007] A first image of the test chart in a first spatial pose is acquired; the first image is captured by a lens onto a display screen; the display screen is used to display the test chart in the first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting the reference spatial pose using a first transformation matrix.

[0008] Based on the first transformation matrix, the first image is back-projected to obtain the first target image;

[0009] The first target image is matched with a preset target image to obtain a matching result, and the quality measurement result of the distortion parameter to be tested is determined based on the matching result; the spatial pose corresponding to the preset target image is related to the reference spatial pose, and is obtained by taking a picture of the test chart displayed on the display screen based on the distortion parameter to be tested through a lens.

[0010] Secondly, embodiments of this disclosure provide a quality measurement device for distortion parameters, comprising:

[0011] The acquisition module is used to acquire a first image of the test pattern card in a first spatial pose; the first image is obtained by capturing the image on the display screen through a lens; the display screen is used to display the test pattern card in the first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting the reference spatial pose based on a first transformation matrix.

[0012] The processing module is used to perform back-projection transformation on the first image based on the first transformation matrix to obtain the first target image;

[0013] The matching module is used to match the first target image with a preset target image to obtain a matching result, and determine the quality measurement result of the distortion parameter to be tested based on the matching result; the spatial pose corresponding to the preset target image is related to the reference spatial pose.

[0014] Thirdly, embodiments of this disclosure provide an electronic device, including: a display screen, a lens, an imaging device, a processor, and a memory;

[0015] Both the display screen and the camera device are connected to the processor.

[0016] The display screen is used to display a test chart in the first spatial pose based on the distortion parameters to be tested.

[0017] The imaging device is used to capture the first image on the display screen through a lens and send the first image to the processor.

[0018] The memory stores computer-executed instructions;

[0019] The processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the distortion parameter quality measurement method as described in the first aspect and various possible designs of the first aspect.

[0020] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the distortion parameter quality measurement method described in the first aspect and various possible designs of the first aspect.

[0021] Fifthly, embodiments of this disclosure provide a computer program product, including a computer program that, when executed by a processor, implements the method for measuring the quality of distortion parameters as described in the first aspect and various possible designs of the first aspect.

[0022] The method, device, storage medium, and program product for measuring the quality of distortion parameters provided in this embodiment include: acquiring a first image of a test pattern card in a first spatial pose, wherein the first image is obtained by capturing a picture of the test pattern card in the first spatial pose through a lens, the display screen is used to display the test pattern card in the first spatial pose based on the distortion parameters to be tested, the first spatial pose is obtained by projecting a reference spatial pose based on a first transformation matrix, performing a back-projection transformation on the first image based on the first transformation matrix to obtain a first target image, matching the first target image with a preset target image to obtain a matching result, and determining the quality measurement result of the distortion parameters to be tested based on the matching result, wherein the spatial pose corresponding to the preset target image is related to the reference spatial pose and is obtained by capturing a picture of the test pattern card displayed on the display screen based on the distortion parameters to be tested through a lens. The distortion parameter quality measurement method provided in this disclosure uses projection transformation to design different poses for the test chart. Images of the test chart in different poses on the display screen are captured through a lens. The captured images are then subjected to back projection transformation. Based on the matching degree of the test chart in the back projection transformation image, the quality measurement result of the distortion parameter to be tested is determined. This method does not require key point detection and is not affected by screen graininess or lens edge sharpness. It simulates dynamic scenes, improves the accuracy of measurement results, and can meet the high requirements for distortion correction accuracy in dynamic scenes. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A schematic diagram illustrating an application scenario of the distortion parameter quality measurement method provided in this embodiment of the disclosure;

[0025] Figure 2 Flowchart of the distortion parameter quality measurement method provided in the embodiments of this disclosure Figure 1 ;

[0026] Figure 3a A schematic diagram of a reference pose provided for an embodiment of this disclosure;

[0027] Figure 3b A schematic diagram of a first spatial pose provided in an embodiment of this disclosure;

[0028] Figure 4 Flowchart of the distortion parameter quality measurement method provided in the embodiments of this disclosure Figure 2 ;

[0029] Figure 5 Schematic diagram three of the distortion parameter quality measurement method provided in the embodiments of this disclosure;

[0030] Figure 6 A structural block diagram of the quality measurement device for distortion parameters provided in the embodiments of this disclosure;

[0031] Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0033] Virtual reality (VR) devices (such as standalone VR headsets) have lenses positioned in front of the display screen. When a user wears a VR headset, their eyes view the image displayed on the screen through these lenses. VR headsets have extremely strict requirements for lens distortion correction. Inaccurate distortion correction can result in straight lines appearing crooked in static scenes and the scene appearing to rotate with the device in dynamic scenes, causing significant dizziness for users who wear them for extended periods.

[0034] In related technologies, a checkerboard image is typically first displayed on a screen based on distortion parameters. Then, a camera captures an image of the screen through a lens to obtain the image to be processed. Keypoint detection is then performed on the image, and the distortion parameters are measured based on the arrangement of these keypoints (whether they are horizontally and vertically aligned). However, this method is susceptible to the effects of screen graininess and lens edge sharpness during keypoint detection, resulting in low accuracy. This, in turn, affects the accuracy of the final distortion parameter quality measurement. Furthermore, since the human eye is less sensitive to static scenes than to dynamic scenes, static judgment methods cannot guarantee the accuracy of distortion correction. Therefore, the aforementioned quality measurement methods have low accuracy and are only suitable for quality measurement in static scenes, not dynamic scenes.

[0035] To address the aforementioned problems, the inventors of this application have discovered that dynamic scenes can be simulated through projection transformation. Specifically, different poses are designed for the test pattern card, and images of the test pattern card in different poses are captured on the display screen through a lens. The captured images are then subjected to back-projection transformation, and the quality measurement result of the distortion parameter to be tested is determined based on the matching degree of the test pattern card in the back-projected image. Based on this, embodiments of this application provide a method for measuring the quality of distortion parameters that eliminates the need for keypoint detection, is unaffected by screen graininess or lens edge sharpness, and improves the accuracy of the measurement results, meeting the high demands for distortion correction accuracy in dynamic scenes.

[0036] refer to Figure 1 , Figure 1 This diagram illustrates an application scenario of the distortion parameter quality measurement method provided in this embodiment of the disclosure. For example... Figure 1 As shown, the imaging device 101 is disposed on one side of the lens 102, and the display screen 103 is disposed on the other side of the lens 102. The controller 104 is connected to both the imaging device 101 and the display screen 103. The display screen 103 is used to display a test chart based on a first spatial pose and the distortion parameters to be tested under the control of the controller 104. The imaging device 101 is used to capture images of the display screen through the lens under the control of the controller 104 to obtain a first image of the test chart corresponding to the first spatial pose, and send the first image to the controller 104. The controller 104 is used to acquire the first image of the test chart in the first spatial pose. The first spatial pose is obtained by projecting a reference spatial pose based on a first transformation matrix. A back-projection transformation is performed on the first image based on the first transformation matrix to obtain a first target image. The first target image is matched with a preset target image to obtain a matching result, and the quality measurement result of the distortion parameters to be tested is determined based on the matching result. The spatial pose corresponding to the preset target image is related to the reference spatial pose and is obtained by capturing images of the test chart displayed on the display screen based on the distortion parameters to be tested through the lens. The controller 104 can be integrated with the display screen 103 and the lens 102 to form a VR all-in-one machine. It can also be a controller for other terminal devices such as mobile phones, tablets, and computers. This embodiment does not limit this.

[0037] In the specific implementation process, the controller 104, in response to the measurement start command, can perform projection transformation on the test chart under the reference spatial pose based on the first transformation matrix to obtain the test chart under the first spatial pose, and send the test chart under the first spatial pose to the display screen 103. Under the control of the controller 104, the display screen 103 displays the test chart based on the first spatial pose and the distortion parameters to be tested. Under the control of the controller 104, the imaging device 101 takes a picture of the display screen through the lens to obtain the first image of the displayed test chart corresponding to the first spatial pose, and sends the first image to the controller 104. The controller 104 acquires the first image of the test chart under the first spatial pose; performs back projection transformation on the first image based on the first transformation matrix to obtain the first target image; matches the first target image with the preset target image to obtain the matching result, and determines the quality measurement result of the distortion parameters to be tested based on the matching result. The spatial pose corresponding to the preset target image is related to the reference spatial pose and is obtained by taking a picture of the test chart displayed on the display screen based on the distortion parameters to be tested through the lens. This application provides a method for measuring the quality of distortion parameters. By using projection transformation, different poses are designed for the test pattern card. Images of the test pattern card in different poses are captured on the display screen through a lens. The captured images are then subjected to back-projection transformation. Based on the matching degree of the test pattern card in the back-projection transformed image, the quality measurement result of the distortion parameter to be tested is determined. This method does not require key point detection and is not affected by screen graininess or lens edge sharpness. It achieves simulation of dynamic scenes, improves the accuracy of measurement results, and can meet the high requirements for distortion correction accuracy in dynamic scenes.

[0038] It should be noted that, Figure 1 The schematic diagram shown is merely an example. The distortion parameter quality measurement method and scenario described in the embodiments of this disclosure are for the purpose of more clearly illustrating the technical solutions of the embodiments of this disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of this disclosure. As those skilled in the art will know, with the evolution of the system and the emergence of new business scenarios, the technical solutions provided by the embodiments of this disclosure are also applicable to similar technical problems.

[0039] The technical solutions of this disclosure will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0040] refer to Figure 2 , Figure 2 Flowchart of the distortion parameter quality measurement method provided in the embodiments of this disclosure Figure 1 The method described in this embodiment can be applied to terminal devices or servers, for example... Figure 1The controller 104 in the middle, the method for measuring the quality of the distortion parameter includes:

[0041] 201. Obtain a first image of the test chart in a first spatial pose; the first image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting the reference spatial pose based on a first transformation matrix.

[0042] In this embodiment, the test image can be any image with texture, such as a checkerboard pattern or a natural image. The reference spatial pose can be any pose; for example, using a checkerboard pattern... Figure 3a As shown, the pose of the chessboard square facing forward can be determined as the reference spatial pose, and correspondingly, as... Figure 3b As shown, the first spatial pose can be the pose of displaying the chessboard square from the front, or the pose obtained by rotating a certain angle with any vertical line as the center.

[0043] Specifically, after selecting the test chart and the reference spatial pose, and designing the first transformation matrix, the display screen can be controlled to display the test chart in the first spatial pose, and the display screen can be photographed by the imaging device through the lens to obtain the first image, which includes the test chart in the first spatial pose.

[0044] 202. Perform a back-projection transformation on the first image based on the first transformation matrix to obtain the first target image.

[0045] Specifically, after obtaining the first image, a back-projection transformation can be performed on the first image based on the first transformation matrix, that is, the pose of the test image card can be adjusted from the first spatial pose back to the reference spatial pose.

[0046] 203. Match the first target image with the preset target image to obtain a matching result, and determine the quality measurement result of the distortion parameter to be tested based on the matching result; the spatial pose corresponding to the preset target image is related to the reference spatial pose, and is obtained by taking a picture of the test chart displayed on the display screen based on the distortion parameter to be tested through a lens.

[0047] Specifically, since the first image is an image captured through a lens and displayed on the screen based on the distortion parameters to be tested, the first image carries the influence of the distortion parameters. If the first image is back-projected and transformed back to the reference spatial pose, then... Figure 3a and Figure 3b Taking a chessboard as an example, the lines in the chessboard in the first target image may appear bent or displaced.

[0048] In this embodiment, the preset target image can have multiple sources. The pose of the test chart corresponding to the preset target image can be a reference spatial pose or other poses obtained based on the reference spatial pose. In one possible implementation, a second image of the test chart in a second spatial pose can be acquired; the second image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the second spatial pose based on the distortion parameters to be tested; the second spatial pose is obtained by projecting the reference spatial pose based on a second transformation matrix; a back-projection transformation is performed on the second image based on the second transformation matrix to obtain a second target image, and the second target image is determined as the preset target image.

[0049] In one embodiment of this disclosure, the method may further include: acquiring a third image of a test pattern card in a third spatial pose; the third image is obtained by capturing a picture of a display screen through a lens; the display screen is used to display the test pattern card in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting the reference spatial pose based on a third transformation matrix; performing a back-projection transformation on the third image based on the third transformation matrix to obtain a third target image; the step of matching the first target image with a preset target image to obtain a matching result, and determining the quality measurement result of the distortion parameters to be tested based on the matching result, may include: matching the first target image, the second target image, and the third target image pairwise to obtain multiple matching results, and determining the quality measurement result of the distortion parameters to be tested based on the multiple matching results.

[0050] In another possible implementation, a reference image of the test chart in a reference spatial pose can be acquired; the reference image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the reference spatial pose based on the distortion parameters to be tested; and the reference image is determined as the preset target image.

[0051] In one embodiment of this disclosure, the method may further include: acquiring a third image of a test pattern card in a third spatial pose; the third image is obtained by capturing a picture of a display screen through a lens; the display screen is used to display the test pattern card in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting a projection transformation onto the reference spatial pose based on a third transformation matrix; performing a back-projection transformation on the third image based on the third transformation matrix to obtain a third target image; the step of matching the first target image with a preset target image to obtain a matching result, and determining the quality measurement result of the distortion parameters to be tested based on the matching result, may include: matching the first target image and the third target image with the reference image respectively, and determining the quality measurement result of the distortion parameters to be tested based on the matching result.

[0052] In this embodiment, there are multiple ways to match images, such as using the squared difference matching algorithm or the correlation coefficient matching method.

[0053] In one disclosed embodiment, matching the first target image with a preset target image to obtain a matching result may include: determining one of the first target image and the preset target image as a template image and the other image as a source image; fixing the template image and moving the source image; calculating the correlation coefficient between the template image and the source image for each moving position; and determining the matching result between the first target image and the preset target image based on the moving position corresponding to the maximum value among multiple correlation coefficients.

[0054] In one disclosed embodiment, to facilitate unified quality measurement of multiple distortion parameters to be tested, the matching results can be normalized. Specifically, since the first spatial pose is transformed from the reference spatial pose, the degree of transformation also affects the matching results. Continuing with... Figure 3a and Figure 3b For example, from Figure 3a pose transition to Figure 3bThe pose of the image needs to be rotated by a certain angle, and the magnitude of the angle will also have a certain impact on the matching result. Therefore, in order to eliminate the influence of the angle, the matching result can be divided by the angle difference between the spatial poses of the two matched images (the first target image and the preset target image). Specifically, determining the quality measurement result of the distortion parameter to be tested based on the matching result may include: determining the pose adjustment range corresponding to the first target image based on the first transformation matrix corresponding to the first target image; normalizing the matching result by using the pose adjustment range corresponding to the first target image and the pose adjustment range corresponding to the preset target image to obtain a normalized matching result; and determining the quality measurement result of the distortion parameter to be tested based on the normalized matching result.

[0055] For example, during distortion parameter correction, multiple distortion parameters are obtained. To select the most suitable and highest-quality distortion parameter from these multiple parameters as the device's distortion parameter, the quality of each distortion parameter can be measured separately to obtain the quality measurement results for each distortion parameter. For the distortion parameter currently being measured, after obtaining the normalized matching result using the above method, the quality measurement result can be determined based on the normalized matching result.

[0056] In one embodiment of this disclosure, in order to improve the accuracy of the quality measurement results, the user's subjective observation results can be taken into consideration. Specifically, the subjective measurement results input by the user based on the overlap between the first target image and the preset target image can be received. The step of determining the quality measurement results of the distortion parameter to be tested based on the matching results includes: fusing the matching results and the subjective measurement results to obtain the quality measurement results of the distortion parameter to be tested.

[0057] For example, a user can observe the overlap between the first target image and the preset target image and input a score. After receiving the score, the user can calculate a weighted sum of the score and the corresponding score of the matching result, and determine the weighted sum as the quality measurement result of the distortion parameter to be tested.

[0058] As described above, this embodiment designs different poses for the test pattern card through projection transformation. Images of the test pattern card in different poses on the display screen are captured through a lens. The captured images are then subjected to back-projection transformation. Based on the matching degree of the test pattern card in the back-projection transformed image, the quality measurement result of the distortion parameter to be tested is determined. There is no need to perform key point detection, and it is not affected by screen graininess or the sharpness of the lens edge. It realizes the simulation of dynamic scenes, improves the accuracy of measurement results, and can meet the high demand for distortion correction accuracy in dynamic scenes.

[0059] refer to Figure 4 , Figure 4 Flowchart of the distortion parameter quality measurement method provided in the embodiments of this disclosure Figure 2 In this embodiment, images corresponding to test charts under multiple spatial poses obtained from the reference spatial pose transformation are used for matching to obtain quality measurement results. Specifically, the quality measurement method for this distortion parameter includes:

[0060] 401. Fix the relative positions of the shooting device and the device to be tested.

[0061] Specifically, the imaging device can be fixed in the first position and the device under test can be fixed in the second position, ensuring that the relative positions between the first and second positions remain unchanged. This ensures that the same external parameters are maintained in subsequent multiple imaging sessions, guaranteeing that the overlap of the images obtained by the back projection transformation is not affected by different external parameters, but is only related to the distortion parameters under test.

[0062] 402. Select the test chart, reference spatial pose, and distortion parameters to be tested.

[0063] In this embodiment, the test image can be any image with texture, such as a checkerboard pattern or a natural image. The reference spatial pose can be any pose; for example, using a checkerboard pattern... Figure 3a As shown, the pose of the chessboard square facing forward can be determined as the reference spatial pose, and correspondingly, as... Figure 3b As shown, the first spatial pose can be the pose of displaying the chessboard grid from the front, obtained by rotating it by a certain angle around any vertical line. During distortion parameter correction, multiple distortion parameters are obtained. To select the most suitable and highest-quality distortion parameter from these multiple parameters as the device's distortion parameter, the quality of each distortion parameter can be measured separately to obtain the quality measurement results. Therefore, one distortion parameter can be selected from the multiple distortion parameters as the distortion parameter to be tested, so that the quality measurement results of this distortion parameter can be obtained based on the following steps.

[0064] 403. Select the first transformation matrix from the preset multiple transformation matrices.

[0065] In this embodiment, multiple first spatial poses can be pre-designed. The transformation matrices corresponding to the multiple first spatial poses are stored to obtain multiple preset transformation matrices.

[0066] 404. Based on the first transformation matrix, the test chart in the reference spatial pose is projected and transformed to obtain the test chart in the first spatial pose, and displayed on the display screen based on the distortion parameters to be tested.

[0067] 405. Control the shooting device to capture the first image on the display screen through the lens.

[0068] 406. Based on the first transformation matrix, perform a back projection transformation on the first image to obtain the first target image.

[0069] 407. Select a new transformation matrix from the multiple preset transformation matrices as the first transformation matrix, and repeat steps 403 to 406 until multiple transformation matrices are traversed.

[0070] Specifically, after multiple iterations, multiple first target images can be obtained.

[0071] 408. Perform pairwise matching on multiple first target images to obtain multiple matching results.

[0072] Specifically, after obtaining multiple first target images, the multiple first target images can be matched in pairs. For example, if three first target images a, b, and c are obtained, then a and b, b and c, and a and c can be matched respectively to obtain the corresponding matching results ab, bc, and ab.

[0073] 409. Normalize multiple matching results to obtain multiple normalized matching results, and determine the quality measurement results of the distortion parameter to be tested based on the multiple normalized matching results.

[0074] For example, after obtaining the matching results ab, bc, and ab, the pose differences between ab can be used to determine the normalized matching result. For instance, if a is rotated 40 degrees relative to b, then ab can be divided by 40 to obtain the normalized matching result for ab. If b is rotated 20 degrees relative to c, then bc can be divided by 20 to obtain the normalized matching result for bc. Furthermore, the quality measurement result of the distortion parameter to be tested can be determined based on the normalized matching results.

[0075] As described above, the distortion parameter quality measurement method provided in this disclosure, by designing multiple spatial poses and performing pairwise matching on the corresponding images, can obtain the quality measurement results of the distortion parameters to be tested based on the matching results. It eliminates the need for keypoint detection, is unaffected by screen graininess or lens edge sharpness, achieves simulation of dynamic scenes, improves the accuracy of measurement results, and meets the high demands for distortion correction accuracy in dynamic scenes.

[0076] refer to Figure 5 , Figure 5 A schematic flowchart of the distortion parameter quality measurement method provided in this embodiment is shown in Figure 3. In this embodiment, a reference image corresponding to the test chart under the reference spatial pose is used for matching to obtain the quality measurement result. Specifically, the distortion parameter quality measurement method includes:

[0077] 501. Fix the relative positions of the shooting device and the device under test.

[0078] 502. Select the test chart, reference spatial pose, and distortion parameters to be tested.

[0079] Steps 501 to 502 in this embodiment are similar to steps 401 to 402 in the above embodiment, and will not be described again here.

[0080] 503. Test chart displaying reference spatial pose based on the distortion parameters to be tested.

[0081] 504. The camera is controlled to capture a reference image on the display screen through a lens.

[0082] Specifically, a reference image corresponding to the test chart in the reference spatial pose is obtained through an imaging device. This reference image is then used as the basis for matching.

[0083] 505. Select the first transformation matrix from the preset multiple transformation matrices.

[0084] 506. Based on the first transformation matrix, the test chart in the reference spatial pose is projected and transformed to obtain the test chart in the first spatial pose, and displayed on the display screen based on the distortion parameters to be tested.

[0085] 507. Control the shooting device to capture the first image on the display screen through the lens.

[0086] 508. Based on the first transformation matrix, perform a back projection transformation on the first image to obtain the first target image.

[0087] 509. Select a new transformation matrix from the multiple preset transformation matrices as the first transformation matrix, and repeat steps 505 to 508 until multiple transformation matrices are traversed.

[0088] Steps 505 to 508 in this embodiment are similar to steps 403 to 407 in the above embodiment, and will not be repeated here.

[0089] 510. Match multiple first target images with the reference image respectively to obtain multiple matching results.

[0090] For example, suppose there are multiple first target images including a, b and c, and the reference image is d. Then a and d, b and d, c and d can be matched to obtain matching results ad, bd, cd.

[0091] 511. Normalize multiple matching results to obtain multiple normalized matching results, and determine the quality measurement results of the distortion parameters to be tested based on the multiple normalized matching results.

[0092] Step 511 in this embodiment is similar to step 409 in the above embodiment, and will not be described again here.

[0093] As described above, the distortion parameter quality measurement method provided in this disclosure, by designing multiple spatial poses and matching the images obtained after back-projection transformation of the images corresponding to the multiple spatial poses with the image corresponding to the reference pose, can obtain the quality measurement result of the distortion parameter to be tested based on the matching result. It eliminates the need for keypoint detection, is unaffected by screen graininess or lens edge sharpness, achieves simulation of dynamic scenes, improves the accuracy of measurement results, and can meet the high demand for distortion correction accuracy in dynamic scenes.

[0094] Corresponding to the distortion parameter quality measurement method in the above embodiment, Figure 6 This is a structural block diagram of a distortion parameter quality measurement device provided in an embodiment of this disclosure. For ease of explanation, only the parts relevant to the embodiments of this disclosure are shown. (Refer to...) Figure 6 The device 60 includes: an acquisition module 601, a processing module 602, and a matching module 603.

[0095] The acquisition module 601 is used to acquire a first image of the test chart in a first spatial pose; the first image is obtained by capturing the image on the display screen through a lens; the display screen is used to display the test chart in the first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting the reference spatial pose based on a first transformation matrix.

[0096] Processing module 602 is used to perform back projection transformation on the first image based on the first transformation matrix to obtain the first target image;

[0097] The matching module 603 is used to match the first target image with a preset target image to obtain a matching result, and determine the quality measurement result of the distortion parameter to be tested based on the matching result; the spatial pose corresponding to the preset target image is related to the reference spatial pose.

[0098] In one embodiment of this disclosure, the processing module 602 is further configured to: acquire a second image of the test pattern card in a second spatial pose; the second image is obtained by capturing a picture of the display screen through a lens; the display screen is configured to display the test pattern card in the second spatial pose based on the distortion parameters to be tested; the second spatial pose is obtained by projecting the reference spatial pose based on a second transformation matrix; the second image is back-projected based on the second transformation matrix to obtain a second target image, and the second target image is determined as the preset target image.

[0099] In one embodiment of this disclosure, the processing module 602 is further configured to: acquire a third image of the test pattern card in a third spatial pose; the third image is obtained by capturing a picture of the display screen through a lens; the display screen is configured to display the test pattern card in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting the reference spatial pose based on a third transformation matrix; and perform a back-projection transformation on the third image based on the third transformation matrix to obtain a third target image;

[0100] The matching module 603 is specifically used to: perform pairwise matching of the first target image, the second target image and the third target image to obtain multiple matching results, and determine the quality measurement result of the distortion parameter to be tested based on the multiple matching results.

[0101] In one embodiment of this disclosure, the processing module 602 is further configured to: acquire a reference image of the test pattern card in a reference spatial pose; the reference image is obtained by capturing a picture of the display screen through a lens; the display screen is configured to display the test pattern card in the reference spatial pose based on the distortion parameters to be tested; and determine the reference image as the preset target image.

[0102] In one embodiment of this disclosure, the processing module 602 is further configured to: acquire a third image of the test pattern card in a third spatial pose; the third image is obtained by capturing a picture of the display screen through a lens; the display screen is configured to display the test pattern card in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting the reference spatial pose based on a third transformation matrix; and perform a back-projection transformation on the third image based on the third transformation matrix to obtain a third target image;

[0103] The matching module 603 is specifically used to: match the first target image and the third target image with the reference image respectively, and determine the quality measurement result of the distortion parameter to be tested based on the matching result.

[0104] In one embodiment of this disclosure, the matching module 603 is specifically configured to: determine one of the first target image and the preset target image as a template image and the other image as a source image; fix the template image and move the source image; calculate the correlation coefficient between the template image and the source image for each moving position; and determine the matching result between the first target image and the preset target image based on the moving position corresponding to the maximum value among multiple correlation coefficients.

[0105] In one embodiment of this disclosure, the matching module 603 is specifically configured to: determine the pose adjustment range corresponding to the first target image based on the first transformation matrix corresponding to the first target image; normalize the matching result by applying the pose adjustment range corresponding to the first target image and the pose adjustment range corresponding to the preset target image to obtain a normalized matching result; and determine the quality measurement result of the distortion parameter to be tested based on the normalized matching result.

[0106] In one embodiment of this disclosure, the matching module 603 is further configured to: receive a subjective measurement result input by a user based on the overlap between the first target image and the preset target image; and fuse the matching result and the subjective measurement result to obtain a quality measurement result of the distortion parameter to be tested.

[0107] In one embodiment of this disclosure, the acquisition module 601 is specifically used to: control the display screen to display a test chart based on a first spatial pose and the distortion parameters to be tested; provide a lens between the display screen and the shooting device; control the shooting device to take a picture of the display screen through the lens to obtain a first image of the display test chart corresponding to the first spatial pose.

[0108] The device provided in this embodiment can be used to execute the technical solutions of the above method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0109] To implement the above embodiments, this disclosure also provides an electronic device.

[0110] refer to Figure 7 The diagram illustrates a structural schematic of an electronic device 700 suitable for implementing embodiments of the present disclosure. The electronic device 700 can be a terminal device or a server. The terminal device can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, personal digital assistants (PDAs), portable Android devices (PADs), portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0111] like Figure 7As shown, the electronic device 700 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage device 708 into a random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the electronic device 700. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0112] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 708 including, for example, magnetic tapes, hard disks, etc.; and communication devices 709. Communication device 709 allows electronic device 700 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 An electronic device 700 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0113] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 709, or installed from storage device 708, or installed from ROM 702. When the computer program is executed by processing device 701, it performs the functions defined in the methods of embodiments of this disclosure.

[0114] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0115] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0116] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above embodiments.

[0117] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0120] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0121] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0123] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0124] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for measuring the quality of distortion parameters, characterized in that, include: Acquire the first image of the test image card in the first spatial pose; The first image was obtained by capturing a picture of the display screen through a lens; The display screen is used to display a test chart in a first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting and transforming a reference spatial pose based on a first transformation matrix. Based on the first transformation matrix, the first image is back-projected to obtain the first target image; The first target image is matched with a preset target image to obtain a matching result, and the quality measurement result of the distortion parameter to be tested is determined based on the matching result. The spatial pose corresponding to the preset target image is the reference spatial pose or the second spatial pose obtained by projecting the reference spatial pose based on the second transformation matrix. The preset target image is obtained by taking a picture of the test chart displayed on the screen based on the distortion parameters to be tested through a lens.

2. The method according to claim 1, characterized in that, The method further includes: A second image of the test chart in a second spatial pose is acquired; the second image is captured by a lens onto a display screen; the display screen is used to display the test chart in the second spatial pose based on the distortion parameters to be tested; the second spatial pose is obtained by projecting the reference spatial pose based on a second transformation matrix. The second image is back-projected based on the second transformation matrix to obtain the second target image, and the second target image is determined as the preset target image.

3. The method according to claim 2, characterized in that, The method further includes: A third image of the test chart in a third spatial pose is acquired; the third image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting the reference spatial pose based on a third transformation matrix. Based on the third transformation matrix, the third image is back-projected to obtain the third target image; The step of matching the first target image with a preset target image to obtain a matching result, and determining the quality measurement result of the distortion parameter to be tested based on the matching result, includes: The first target image, the second target image, and the third target image are matched in pairs to obtain multiple matching results, and the quality measurement result of the distortion parameter to be tested is determined based on the multiple matching results.

4. The method according to claim 1, characterized in that, The method further includes: A reference image of the test chart in a reference spatial pose is acquired; the reference image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the reference spatial pose based on the distortion parameters to be tested; The reference image is determined as the preset target image.

5. The method according to claim 4, characterized in that, The method further includes: A third image of the test chart in a third spatial pose is acquired; the third image is obtained by capturing a picture of the display screen through a lens; the display screen is used to display the test chart in the third spatial pose based on the distortion parameters to be tested; the third spatial pose is obtained by projecting the reference spatial pose based on a third transformation matrix. Based on the third transformation matrix, the third image is back-projected to obtain the third target image; The step of matching the first target image with a preset target image to obtain a matching result, and determining the quality measurement result of the distortion parameter to be tested based on the matching result, includes: The first target image and the third target image are matched with the reference image respectively, and the quality measurement result of the distortion parameter to be tested is determined based on the matching result.

6. The method according to any one of claims 1-4, characterized in that, The step of matching the first target image with a preset target image to obtain a matching result includes: One of the first target image and the preset target image is determined as the template image, and the other image is determined as the source image; Fix the template image and move the source image; For each movement position, the correlation coefficient between the template image and the source image is calculated; The matching result between the first target image and the preset target image is determined based on the movement position corresponding to the maximum value among multiple correlation coefficients.

7. The method according to any one of claims 1-4, characterized in that, The step of determining the quality measurement result of the distortion parameter to be tested based on the matching result includes: Based on the first transformation matrix corresponding to the first target image, determine the pose adjustment range corresponding to the first target image; Based on the pose adjustment range corresponding to the first target image and the pose adjustment range corresponding to the preset target image, the matching result is normalized to obtain the normalized matching result. The quality measurement result of the distortion parameter to be tested is determined based on the normalized matching result.

8. The method according to any one of claims 1-4, characterized in that, The method further includes: Receive subjective measurement results input by the user based on the overlap between the first target image and the preset target image; The step of determining the quality measurement result of the distortion parameter to be tested based on the matching result includes: The matching results and the subjective measurement results are fused to obtain the quality measurement results of the distortion parameter to be tested.

9. The method according to any one of claims 1-4, characterized in that, The acquisition of the first image of the test image card in the first spatial pose includes: The control display screen displays the test chart based on the first spatial pose and the distortion parameters to be tested; a lens is provided between the display screen and the imaging device; The camera is controlled to capture an image of the display screen through the lens, thereby obtaining a first image of the display test chart corresponding to the first spatial pose.

10. A quality measurement device for distortion parameters, characterized in that, include: The acquisition module is used to acquire the first image of the test image card in the first spatial pose. The first image was obtained by capturing a picture of the display screen through a lens; The display screen is used to display a test chart in a first spatial pose based on the distortion parameters to be tested; the first spatial pose is obtained by projecting and transforming a reference spatial pose based on a first transformation matrix. The processing module is used to perform back-projection transformation on the first image based on the first transformation matrix to obtain the first target image; The matching module is used to match the first target image with a preset target image to obtain a matching result, and determine the quality measurement result of the distortion parameter to be tested based on the matching result; the spatial pose corresponding to the preset target image is the reference spatial pose or a second spatial pose obtained by projecting the reference spatial pose based on the second transformation matrix; the preset target image is obtained by taking a picture of the test chart displayed on the display screen based on the distortion parameter to be tested through a lens.

11. An electronic device, characterized in that, include: Display screen, lens, imaging device, processor, and memory; Both the display screen and the camera device are connected to the processor. The display screen is used to display a test chart in the first spatial pose based on the distortion parameters to be tested. The imaging device is used to capture a first image on the display screen through a lens and send the first image to the processor. The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the quality measurement method for distortion parameters as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, implement the method for measuring the quality of distortion parameters as described in any one of claims 1 to 9.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method for measuring the quality of distortion parameters as described in any one of claims 1 to 9.

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