CN110728638A - Image distortion correction method, vehicle machine and vehicle - Google Patents
Image distortion correction method, vehicle machine and vehicle Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of automobile electronics, and discloses an image distortion correction method, an automobile machine and an automobile. The image distortion correction method is applied to an automobile, the automobile is provided with an A column and an outer camera, the A column is provided with a display screen, and the method comprises the following steps: carrying out distortion calibration on the video of the display screen; acquiring a video to be corrected, which is shot by a camera outside the vehicle; carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system; performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction; and outputting the video with the distortion corrected to the display screen. Through the mode, the embodiment of the invention solves the technical problem of high video distortion degree presented by the existing A column, so that the A column can better present an actual scene.
Description
Technical Field
The invention relates to the technical field of automobile electronics, in particular to an image distortion correction method, an automobile machine and an automobile.
Background
The A column, named A-pilar in English, is a connecting column for connecting the roof and the front cabin of the vehicle at the front left and right, and is arranged between the engine cabin and the cab and above the left and right rearview mirrors. Because the A column is arranged between the engine compartment and the cockpit and above the left rearview mirror and the right rearview mirror, part of turning vision of a driver can be shielded, particularly left turning, and a vision blind area formed by shielding the vision of the driver by the A column in the driving process is called as an A column blind area.
The sectional area of the A-pillar is too small, so that the strength of the vehicle body is insufficient, and the visual field of a driver is influenced if the sectional area of the A-pillar is too large. In order to solve the problem, a camera is arranged outside the A column through an Augmented Reality (AR), a display screen is arranged inside the A column, and a camera picture is transmitted into the A column, so that the transparentization of the A column part is finally realized, the firmness of the traditional A column is kept, and the sight of a driver can clearly penetrate through the A column to see the road condition clearly.
In a computer vision system for road surface detection, in order to acquire scene video information of a large field of view, an optical system of a wide-angle lens camera, particularly a system of a short focal length and a wide-angle lens, is often used, and has a certain difference with an ideal pinhole perspective model, so that nonlinear optical distortions of different degrees exist between actual imaging and ideal imaging of an object outside a vehicle on a camera image plane. The distortion can be rapidly increased along with the increase of the view field, although the image definition is not influenced, the distortion of an optical system directly influences the geometric position accuracy of the imaging, and a straight line of a space is changed into a curve in the image space due to the existence of the distortion, so that the distortion of the image is caused.
At present, the image presentation of the column a generates certain distortion relative to a real scene, which causes image distortion, and how to perform distortion correction on the video image presented by the column a makes the content presented by the column a closer to the real scene is a problem to be solved by the invention.
Disclosure of Invention
The embodiment of the invention aims to provide an image distortion correction method, a car machine and an automobile, which solve the technical problem that the video distortion degree presented by the existing A column is high, and enable the A column to present an actual scene better.
In order to solve the above technical problems, embodiments of the present invention provide the following technical solutions:
in a first aspect, an embodiment of the present invention provides an image distortion correction method, which is applied to an automobile, where the automobile is provided with an a-pillar and an external camera, the a-pillar is provided with a display screen, and the method includes:
carrying out distortion calibration on the video of the display screen;
acquiring a video to be corrected, which is shot by a camera outside the vehicle;
carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system;
performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction;
and outputting the video with the distortion corrected to the display screen.
In some embodiments, the distortion scaling the video of the display screen includes:
acquiring a calibration template video shot by a camera outside a vehicle, and extracting angular points of the calibration template;
judging whether the angular points of the calibration template are successfully extracted or not;
if the angular point of the calibration template is successfully extracted, calculating an internal parameter matrix of the camera;
calculating an external parameter matrix of the camera;
and calculating calibration parameters according to the camera internal parameter matrix and the camera external parameter matrix.
In some embodiments, the calibration template is a checkerboard, and the extracting corner points of the calibration template specifically includes:
and determining the position information of each corner of the checkerboard through a corner detection algorithm.
In some embodiments, the method further comprises:
and determining the position information of the checkerboard according to the position information of each corner point of the checkerboard.
In some embodiments, the method further comprises:
and calculating the distortion coefficient of the camera outside the vehicle.
In some embodiments, the calculating a distortion coefficient for the off-board camera comprises:
establishing a distortion model of a camera and a display screen;
acquiring position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
In some embodiments, the transforming the coordinate system of the video to be rectified from the camera coordinate system to the pixel coordinate system includes:
and according to the distortion coefficient, determining a mapping relation between the image coordinate of the video to be corrected and the corresponding ideal coordinate value, and transforming the video to be corrected from a camera coordinate system to a pixel coordinate system.
In some embodiments, the performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate the video after distortion correction includes:
and interpolating the coordinates of the pixels calculated by the distortion correction algorithm of the camera and the display screen through an image interpolation algorithm, determining the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed, and generating the video after the distortion correction.
In a second aspect, an embodiment of the present invention provides an image distortion correction device, which is applied to an automobile, where the automobile is provided with an a-pillar and an external camera, the a-pillar is provided with a display screen, and the device includes:
the distortion calibration unit is used for carrying out distortion calibration on the video of the display screen;
the device comprises a to-be-corrected video acquisition unit, a correction unit and a correction unit, wherein the to-be-corrected video acquisition unit is used for acquiring a to-be-corrected video shot by a camera outside a vehicle;
the coordinate system transformation unit is used for carrying out coordinate system transformation on the video to be corrected and transforming the video to a pixel coordinate system from a camera coordinate system;
the distortion correction video generation unit is used for performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction;
and the video output unit is used for outputting the video subjected to the distortion correction to the display screen.
In some embodiments, the distortion calibration unit is specifically configured to:
acquiring a calibration template video shot by a camera outside a vehicle, and extracting angular points of the calibration template;
judging whether the angular points of the calibration template are successfully extracted or not;
if the angular point of the calibration template is successfully extracted, calculating an internal parameter matrix of the camera;
calculating an external parameter matrix of the camera;
and calculating calibration parameters according to the camera internal parameter matrix and the camera external parameter matrix.
In some embodiments, the calibration template is a checkerboard, and the extracting corner points of the calibration template specifically includes:
and determining the position information of each corner of the checkerboard through a corner detection algorithm.
In some embodiments, the apparatus further comprises:
and the checkerboard position information unit is used for determining the position information of the checkerboard according to the position information of each corner point of the checkerboard.
In some embodiments, the apparatus further comprises:
and the distortion coefficient calculation unit is used for calculating the distortion coefficient of the camera outside the vehicle.
In some embodiments, the distortion coefficient calculation unit is specifically configured to:
establishing a distortion model of a camera and a display screen;
acquiring position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
In some embodiments, the coordinate system transformation unit is specifically configured to:
and according to the distortion coefficient, determining a mapping relation between the image coordinate of the video to be corrected and the corresponding ideal coordinate value, and transforming the video to be corrected from a camera coordinate system to a pixel coordinate system.
In some embodiments, the distortion correction video generation unit is specifically configured to:
and interpolating the coordinates of the pixels calculated by the distortion correction algorithm of the camera and the display screen through an image interpolation algorithm, determining the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed, and generating the video after the distortion correction.
In a third aspect, an embodiment of the present invention provides a vehicle machine, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described method of distortion calibration of an image.
In a fourth aspect, an embodiment of the present invention further provides an automobile, including: the camera comprises an A column, an external camera and an internal camera;
the camera outside the vehicle is used for shooting video data outside the vehicle at the A column, the camera inside the vehicle is used for shooting video data inside the vehicle at the A column, and the A column is provided with a display screen and used for displaying the video data outside the vehicle after distortion correction;
the vehicle machine is used for sending the vehicle-mounted video data after the distortion correction to the display screen.
In a fifth aspect, the embodiment of the present invention further provides a non-transitory computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, where the computer-executable instructions are configured to enable a vehicle machine to execute the distortion correction method for an image as described above.
The embodiment of the invention has the beneficial effects that: different from the prior art, the image distortion correction method provided by the embodiment of the invention is applied to an automobile, the automobile is provided with an A column and an automobile exterior camera, the A column is provided with a display screen, and the method comprises the following steps: carrying out distortion calibration on the video of the display screen; acquiring a video to be corrected, which is shot by a camera outside the vehicle; carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system; performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction; and outputting the video with the distortion corrected to the display screen. Through the mode, the embodiment of the invention solves the technical problem of high video distortion degree presented by the existing A column, so that the A column can better present an actual scene.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
FIG. 1 is a schematic diagram of a hardware architecture of an automobile according to an embodiment of the present invention;
FIG. 2 is a schematic view of a camera of an automobile according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for correcting image distortion according to an embodiment of the present invention;
FIG. 4 is a detailed flowchart of step S10 in FIG. 3;
FIG. 5 is a schematic flow chart of the distortion correction provided by the embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an apparatus for correcting image distortion according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a vehicle machine according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
At present, with the development of Augmented Reality (AR), an a-pillar of an automobile is generated, and the purpose of the a-pillar is to enable a driver to better understand a driving environment outside the automobile, and a visual error of a display image of the existing a-pillar is often large, so that a driving environment seen by the driver at the a-pillar is different from a real environment to a certain extent, and judgment of the driver is easily influenced.
Because the distortion can be rapidly increased along with the increase of the view field, although the image definition is not influenced, the distortion of an optical system directly influences the geometric position accuracy of the imaging, and a straight line in the space is changed into a curve in the image space due to the existence of the distortion, so that the distortion of the image is caused. The distortion is not significant in an optical system with a smaller field of view, but the large field of view optical system must take measures to eliminate the effect of the distortion. The presence of distortion is detrimental to image recognition, analysis and judgment. If the image distortion is large after the camera images, the image distortion is not small after the image distortion is converted into the space distance, which is not allowed in high-precision three-dimensional stereo measurement, visual detection and motion measurement. In order to improve the accuracy of quantitative analysis such as image detection and pattern matching, such distortion must be corrected, and the correction accuracy will directly affect the accuracy of quantitative analysis. The original appearance of the deformed image is restored, so that the identifiability of the image is greatly improved.
Therefore, in the application of the A column, the fundamental purpose of calibrating the camera with high precision is to find out the factors causing image distortion, further correct the image distortion and provide an ideal image for subsequent test processing, thereby improving the precision of the measurement result. As an important link of image preprocessing, image correction has its important application in many fields.
At present, the image presentation of the column a generates certain distortion relative to a real scene, which causes image distortion, and how to perform distortion correction on the video image presented by the column a makes the content presented by the column a closer to the real scene is a problem to be solved by the invention.
Based on the above, the invention provides an image distortion correction method, so that an A column can better present an actual scene.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware architecture of an automobile according to an embodiment of the present invention;
as shown in fig. 1, the automobile 100 includes: the vehicle-mounted device 10, the vehicle-mounted camera 20, the vehicle-mounted camera 30 and the display screen 40,
wherein, the car machine 10 is electronic equipment, the car machine 10 respectively with the car outer camera 20, camera 30 and display screen 40 communication connection in the car, for example: the car machine 10 is connected with the external camera 20, the internal camera 30 and the display screen 40 through cables or wirelessly, for example: the car machine is used for splicing two paths of external video data shot by the external camera 20 or two paths of internal video data shot by the internal camera 20, and in the embodiment of the invention, the car machine 10 includes but is not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such electronic devices include smart phones, multimedia phones, functional phones, and low-end phones.
(2) The mobile personal computer equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such electronic devices include: PDA, MID, and UMPC devices, etc., such as ipads.
(3) A portable entertainment device: such devices can display and play video content, and generally also have mobile internet access features. This type of device comprises: video players, handheld game consoles, and intelligent toys and portable car navigation devices.
(4) And other electronic equipment with a video playing function and an internet surfing function.
The external camera 20 and the internal camera 30 are both binocular cameras, please refer to fig. 2, and fig. 2 is a schematic diagram of an automobile camera provided by an embodiment of the present invention;
as shown in fig. 2, the camera 20 outside the vehicle is installed outside the a-pillar, and the camera 30 inside the vehicle is installed inside the a-pillar, wherein a display screen is installed inside the a-pillar, in the embodiment of the present invention, the display screen is a flexible display screen, and the pictures acquired by the camera 20 outside the vehicle are transmitted to the flexible display screen inside the a-pillar, so that the transparency of the a-pillar portion is realized.
Referring to fig. 3, fig. 3 is a schematic flowchart illustrating a method for correcting image distortion according to an embodiment of the present invention;
as shown in fig. 3, the image distortion correction method is applied to an automobile, wherein the automobile comprises an automobile machine, the automobile machine is an android device, the automobile machine is used for executing the image distortion correction method of the invention, the automobile is provided with an a-pillar and an automobile exterior camera, the a-pillar is provided with a display screen, the display screen is arranged on the inner side of the a-pillar, the display screen is a flexible display screen, and the method comprises the following steps:
step S10: carrying out distortion calibration on the video of the display screen;
referring to fig. 4 again, fig. 4 is a detailed flowchart of step S10 in fig. 3;
as shown in fig. 4, the distortion calibration of the video of the display screen includes:
step S11: inputting a calibration template video from a camera;
specifically, the automobile is provided with an outer camera, the outdoor camera is used for acquiring a real scene outside the column a, wherein the outer camera can be mounted on a left side rearview mirror of the automobile, in the embodiment of the invention, the calibration template is a checkerboard, the calibration template video is a checkerboard video acquired by the outer camera, and the calibration template video is input into a vehicle machine of the automobile and is calibrated by the vehicle machine of the automobile, wherein the vehicle machine is an electronic device, for example, a mobile terminal, such as an electronic device like an android device, and the like, wherein the outer camera is a high-definition camera, and the calibration template video can be LVDS high-definition video data.
Step S12: extracting angular points of the calibration template;
specifically, the extracting of the corner points of the calibration template includes: through the angular point detection algorithm, confirm the positional information of each angular point of check board, it is specific, right through Harris angular point detection algorithm the calibration template carries out angular point detection, wherein, right through Harris angular point detection algorithm the calibration template carries out angular point detection, including following step:
(1) acquiring image information of a calibration template according to the acquired calibration template video;
(2) performing Gaussian smoothing processing on the acquired image information of the calibration template;
(3) and establishing a corresponding image window function, comparing and judging the acquired image information of the calibration template with a set corresponding contrast value, and extracting angular point position information of the image of the calibration template.
The image window function theoretically has no image gray value change when the image smooth region carries out movement detection along any direction, the image window function theoretically has no image gray value change when the image edge region carries out movement detection along the image edge direction region, and the gray value change of the image when the window function carries out movement detection along any direction in the image corner region is quite obvious. In the embodiment of the invention, the selection of the calibration template is arbitrary, any object containing proper representation can be used as the calibration template of the camera and the flexible screen, but the actual calibration process basically selects some regular calibration templates such as a chessboard, and the invention selects a black-and-white chessboard as the calibration template.
After determining the position information of each corner point of the checkerboard, the method further comprises the following steps:
and determining the position information of the checkerboard according to the position information of each corner point of the checkerboard.
Specifically, after the position information of each corner point of the checkerboard is determined through a corner point detection algorithm, the position information of each corner point of the checkerboard in a world coordinate system is determined through calculation.
Step S13: judging whether the angular points of the calibration template are successfully extracted or not;
specifically, whether the corner points of the calibration template are extracted successfully is judged, if yes, the step S14 is executed, and if not, the step S12 is executed again;
step S14: calculating an internal reference;
specifically, a camera intrinsic parameter matrix is calculated, wherein the position of each feature point on the checkerboard relative to the world coordinate system is accurately determined during manufacturing, and the camera intrinsic parameter matrix can be calculated after the projection position of the feature point of the checkerboard on the image of the a-pillar is obtained.
Step S15: calculating an external parameter;
specifically, the camera external parameter matrix is calculated.
Step S16: calculating calibration parameters;
specifically, according to the camera internal parameter matrix and the camera external parameter matrix, a homography matrix of a world coordinate system and an image coordinate system is calculated, and the homography matrix is the calibration parameter.
Step S20: acquiring a video to be corrected, which is shot by a camera outside the vehicle;
the utility model discloses a camera outside the car, including A post, camera outside the car, the camera is used for correcting the video of treating, and the camera is used for correcting the video of treating that the camera was shot outside the car, and the video of treating that obtains the camera shooting outside the car specifically includes: and splicing the two paths of video data acquired by the camera outside the vehicle to generate the video to be corrected.
Step S30: carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system;
specifically, the performing coordinate system transformation on the video to be corrected to transform the video to be corrected from a camera coordinate system to a pixel coordinate system includes:
calculating a distortion coefficient of the camera outside the vehicle;
and determining a mapping relation between the image coordinates of the video to be corrected and the corresponding ideal coordinate values according to the distortion coefficient of the camera outside the vehicle, carrying out coordinate system transformation on the video to be corrected, and transforming the video to be corrected from a camera coordinate system to a pixel coordinate system.
Wherein, the distortion coefficient of calculating the outer camera of car includes:
establishing a distortion model of a camera and a display screen;
acquiring position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
Specifically, if the distortion point of the point P (xcorrected) is (x, y), there is
By establishing a camera and display screen distortion model which is
xcorrected＝x(1+k1r2+k2r4)+[2p1xy+p2(r2+2x2)]
ycorrected＝y(1+k1r2+k2r4)+[2p2xy+p1(r2+2y2)]，
Extracting position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
The method comprises the steps of obtaining position information of corner points of a calibration template, calculating a rotation and translation matrix between a camera coordinate system and a pixel coordinate system according to the position information of the corner points of the calibration template and the position information of characteristic points of a display screen corresponding to the corner points, carrying out coordinate system transformation on a video to be corrected according to the rotation and translation matrix, and transforming the video to be corrected from the camera coordinate system to the pixel coordinate system.
Step S40: performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction;
specifically, the coordinates of the pixels are calculated by a camera and display screen distortion correction algorithm, wherein the camera and display screen distortion correction algorithm is the camera and display screen distortion model, namely
The coordinates of the pixels are calculated through the distortion correction algorithm of the camera and the display screen, and in the field of computer vision processing, because the coordinate values of the images are discrete integers, the processed image information coordinate values are often not coincided with the position coordinates of the original image in a one-to-one correspondence manner, that is, the coordinates calculated by the distortion correction algorithm of the camera and the flexible screen are possibly not integer points corresponding to the original image, so that the definition of the images cannot meet the requirement at the moment, and the calculated coordinates of the pixels need to be interpolated.
Specifically, the coordinates of the pixels calculated by the distortion correction algorithm of the camera and the display screen are interpolated through an image interpolation algorithm, the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed are determined, and the video after the distortion correction is generated.
In the embodiment of the present invention, the image interpolation algorithm includes, but is not limited to: the interpolation method includes a nearest point interpolation method, a bilinear interpolation method and a cubic convolution method, and preferably, the interpolation is performed through the bilinear interpolation method in the embodiment of the invention. The bilinear interpolation method is a commonly used interpolation algorithm in computer vision image processing, gives consideration to the requirements of interpolation precision and algorithm simplicity, is linear interpolation expansion of an interpolation function with two variables, and has the core idea of performing linear interpolation in two directions respectively. The principle is that the pixel value of the point to be sampled is linearly interpolated in the horizontal and vertical directions of the pixel value of 4 points adjacent to the pixel value in the original image, namely, the corresponding weight is determined according to the distance between the point to be sampled and the surrounding 4 adjacent points, thereby calculating the pixel value of the point to be sampled.
Step S50: and outputting the video with the distortion corrected to the display screen.
Specifically, after the coordinates of the pixels are interpolated, the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed are determined, that is, the coordinates of the pixels of the image of the video to be corrected of the pixel coordinate system are determined, so that the video after the distortion correction is generated, and the video after the distortion correction is output to the display screen, wherein the display screen is a display screen arranged on the inner side of the column a, and the display screen is a flexible display screen.
Referring to fig. 5 again, fig. 5 is a schematic flow chart of the aberration correction according to the embodiment of the invention;
as shown in fig. 5, the process of the aberration correction includes:
step S501: inputting a video to be corrected from a camera;
the utility model discloses a camera outside the car, including A post, camera outside the car, the camera is used for correcting the video of treating, and the camera is used for correcting the video of treating that the camera was shot outside the car, and the video of treating that obtains the camera shooting outside the car specifically includes: and splicing the two paths of video data acquired by the camera outside the vehicle to generate the video to be corrected.
Step S502: performing spatial transformation;
specifically, the coordinate system of the video to be corrected is transformed from the camera coordinate system to the pixel coordinate system.
Step S503: interpolation between video pixels;
specifically, the video to be corrected in the pixel coordinate system is subjected to inter-pixel interpolation to generate a video after distortion correction.
Step S504: outputting the video subjected to the distortion correction to a flexible screen;
specifically, after the coordinates of the pixels are interpolated, the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed are determined, that is, the coordinates of the pixels of the image of the video to be corrected of the pixel coordinate system are determined, so that the video after the distortion correction is generated, and the video after the distortion correction is output to the display screen, wherein the display screen is a display screen arranged on the inner side of the column a, and the display screen is a flexible display screen.
In an embodiment of the present invention, before outputting the distortion-corrected video to the display screen, the method further includes:
and performing video post-processing on the video after the distortion correction, wherein the video post-processing comprises:
cutting the video after the distortion correction according to the difference of the installation positions of the camera outside the vehicle and the display screen so as to enable the video displayed on the display screen to be basically aligned with an actual scene;
and performing light compensation processing on the video subjected to distortion correction according to the intensity of the ambient light, so that the light intensity of the video to be output is basically consistent with that of the actual scene.
In an embodiment of the present invention, a method for correcting distortion of an image is provided, where the method is applied to an automobile, the automobile is provided with an a-pillar and an external camera, the a-pillar is provided with a display screen, and the method includes: carrying out distortion calibration on the video of the display screen; acquiring a video to be corrected, which is shot by a camera outside the vehicle; carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system; performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction; and outputting the video with the distortion corrected to the display screen. Through the mode, the embodiment of the invention solves the technical problem of high video distortion degree presented by the existing A column, so that the A column can better present an actual scene.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an apparatus for correcting image distortion according to an embodiment of the present invention; wherein, the distortion correcting device of this image is applied to the car, the car is provided with A post and the outer camera of car, the A post is provided with the display screen, the display screen is flexible display screen.
As shown in fig. 6, the image distortion correcting apparatus 60 includes:
a distortion calibration unit 61, configured to perform distortion calibration on a video of the display screen;
a to-be-corrected video acquiring unit 62 for acquiring a to-be-corrected video shot by the vehicle exterior camera;
a coordinate system transformation unit 63, configured to perform coordinate system transformation on the video to be corrected, and transform the video to be corrected from a camera coordinate system to a pixel coordinate system;
a distortion correction video generation unit 64, configured to perform inter-pixel interpolation on a video to be corrected in the pixel coordinate system, and generate a video after distortion correction;
a video output unit 65, configured to output the video with the distortion corrected to the display screen.
In some embodiments, the distortion calibration unit 61 is specifically configured to:
acquiring a calibration template video shot by a camera outside a vehicle, and extracting angular points of the calibration template;
judging whether the angular points of the calibration template are successfully extracted or not;
if the angular point of the calibration template is successfully extracted, calculating an internal parameter matrix of the camera;
calculating an external parameter matrix of the camera;
and calculating calibration parameters according to the camera internal parameter matrix and the camera external parameter matrix.
In some embodiments, the calibration template is a checkerboard, and the extracting corner points of the calibration template specifically includes:
and determining the position information of each corner of the checkerboard through a corner detection algorithm.
In some embodiments, the image distortion correction apparatus 60 further includes:
a checkerboard position information unit (not shown) for determining position information of the checkerboard according to the position information of each corner point of the checkerboard.
In some embodiments, the image distortion correction apparatus 60 further includes:
and a distortion coefficient calculation unit (not shown) for calculating a distortion coefficient of the vehicle exterior camera.
In some embodiments, the distortion coefficient calculation unit is specifically configured to:
establishing a distortion model of a camera and a display screen;
acquiring position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
In some embodiments, the coordinate system transformation unit 63 is specifically configured to:
and according to the distortion coefficient, determining a mapping relation between the image coordinate of the video to be corrected and the corresponding ideal coordinate value, and transforming the video to be corrected from a camera coordinate system to a pixel coordinate system.
In some embodiments, the distortion correction video generating unit 64 is specifically configured to:
and interpolating the coordinates of the pixels calculated by the distortion correction algorithm of the camera and the display screen through an image interpolation algorithm, determining the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed, and generating the video after the distortion correction.
In an embodiment of the present invention, an image distortion correction device is applied to an automobile, the automobile is provided with an a-pillar and an external camera, the a-pillar is provided with a display screen, and the image distortion correction device includes: the distortion calibration unit is used for carrying out distortion calibration on the video of the display screen; the device comprises a to-be-corrected video acquisition unit, a correction unit and a correction unit, wherein the to-be-corrected video acquisition unit is used for acquiring a to-be-corrected video shot by a camera outside a vehicle; the coordinate system transformation unit is used for carrying out coordinate system transformation on the video to be corrected and transforming the video to a pixel coordinate system from a camera coordinate system; the distortion correction video generation unit is used for performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction; and the video output unit is used for outputting the video subjected to the distortion correction to the display screen. Through the mode, the video processing method and the video processing device can solve the technical problem that the video distortion degree presented by the A column is high at present, so that the A column presents an actual scene better.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a vehicle machine according to an embodiment of the present invention.
The vehicle machine can be mobile communication equipment, mobile personal computer equipment, portable entertainment equipment and other electronic equipment with video playing function and internet function.
As shown in fig. 7, the car machine 70 includes one or more processors 71 and a memory 72. Fig. 7 illustrates an example of one processor 71.
The processor 71 and the memory 72 may be connected by a bus or other means, such as the bus connection in fig. 7.
The memory 72, which is a non-volatile computer-readable storage medium, may be used for storing non-volatile software programs, non-volatile computer-executable programs, and modules, such as units (e.g., units shown in fig. 6) corresponding to a distortion correction method for an image according to an embodiment of the present invention. The processor 71 executes various functional applications of the image distortion correction method and data processing, that is, functions of the respective modules and units of the above method embodiment image distortion correction method and the above apparatus embodiment, by executing the nonvolatile software program, instructions, and modules stored in the memory 72.
The memory 72 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 72 may optionally include memory located remotely from the processor 71, and such remote memory may be connected to the processor 71 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The modules are stored in the memory 72 and, when executed by the one or more processors 61, perform the method of image distortion correction in any of the method embodiments described above, e.g., performing the various steps shown in fig. 3 described above; the functions of the respective modules or units described in fig. 6 can also be implemented.
Embodiments of the present invention also provide a non-transitory computer storage medium storing computer-executable instructions, which are executed by one or more processors, such as one of the processors 71 in fig. 7, to enable the one or more processors to perform the image distortion correction method in any of the above method embodiments, such as performing the above steps shown in fig. 3; the functions of the various units described in fig. 6 may also be implemented.
The above-described embodiments of the apparatus or device are merely illustrative, wherein the unit modules described as separate parts may or may not be physically separate, and the parts displayed as module units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network module units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a general hardware platform, and certainly can also be implemented by hardware. Based on such understanding, the technical solutions mentioned above may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute the method according to each embodiment or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; within the idea of the invention, also technical features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. The image distortion correction method is applied to an automobile, and is characterized in that the automobile is provided with an A column and an outer camera, the A column is provided with a display screen, and the method comprises the following steps:
carrying out distortion calibration on the video of the display screen;
acquiring a video to be corrected, which is shot by a camera outside the vehicle;
carrying out coordinate system transformation on the video to be corrected, and transforming the video to a pixel coordinate system from a camera coordinate system;
performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate a video after distortion correction;
and outputting the video with the distortion corrected to the display screen.
2. The method of claim 1, wherein the distortion scaling of the video of the display screen comprises:
acquiring a calibration template video shot by a camera outside a vehicle, and extracting angular points of the calibration template;
judging whether the angular points of the calibration template are successfully extracted or not;
if the angular point of the calibration template is successfully extracted, calculating an internal parameter matrix of the camera;
calculating an external parameter matrix of the camera;
and calculating calibration parameters according to the camera internal parameter matrix and the camera external parameter matrix.
3. The method according to claim 1, wherein the calibration template is a checkerboard, and the extracting corner points of the calibration template specifically comprises:
and determining the position information of each corner point of the checkerboard through a corner point detection algorithm.
4. The method of claim 3, further comprising:
and determining the position information of the checkerboard according to the position information of each corner point of the checkerboard.
5. The method of claim 4, further comprising:
and calculating the distortion coefficient of the camera outside the vehicle.
6. The method of claim 5, wherein the calculating a distortion coefficient for the off-board camera comprises:
establishing a distortion model of a camera and a display screen;
acquiring position information of angular points of a plurality of images of the vehicle exterior camera and the display screen;
and determining undetermined coefficients calibrated by the cameras and the display screen according to the position information of the angular points of the images of the plurality of cameras and the display screen, and determining the calibrated undetermined coefficients as distortion coefficients of the cameras outside the vehicle.
7. The method according to claim 6, wherein the transforming the video to be rectified from a camera coordinate system to a pixel coordinate system comprises:
and according to the distortion coefficient, determining a mapping relation between the image coordinate of the video to be corrected and the corresponding ideal coordinate value, and transforming the video to be corrected from a camera coordinate system to a pixel coordinate system.
8. The method according to claim 1, wherein the performing inter-pixel interpolation on the video to be corrected of the pixel coordinate system to generate the video with distortion corrected comprises:
and interpolating the coordinates of the pixels calculated by the distortion correction algorithm of the camera and the display screen through an image interpolation algorithm, determining the coordinates of the pixels of the image of the video to be corrected after the coordinate system is transformed, and generating the video after the distortion correction.
9. The utility model provides a car machine, its characterized in that includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
10. An automobile, comprising: the camera comprises an A column, an external camera and an internal camera;
the camera outside the vehicle is used for shooting video data outside the vehicle at the A column, the camera inside the vehicle is used for shooting video data inside the vehicle at the A column, and the A column is provided with a display screen and used for displaying the video data outside the vehicle after distortion correction;
the vehicle machine of claim 9, configured to send the distortion corrected vehicle exterior video data to a display screen.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111391755A (en) * | 2020-03-10 | 2020-07-10 | 京东方科技集团股份有限公司 | Display method, device and system of blind area image |
| CN111731187A (en) * | 2020-06-19 | 2020-10-02 | 杭州视为科技有限公司 | Automobile A-pillar blind area image display system and method |
| CN111915683A (en) * | 2020-07-27 | 2020-11-10 | 湖南大学 | Image position calibration method, intelligent device and storage medium |
| CN111951193A (en) * | 2020-08-21 | 2020-11-17 | 安谋科技（中国）有限公司 | Method and apparatus for correcting horizontal distortion of image |
| CN112634372A (en) * | 2020-11-27 | 2021-04-09 | 中山大学 | Real-time binocular camera correction method and device and storage medium |
| CN112712474A (en) * | 2020-12-16 | 2021-04-27 | 杭州小伴熊科技有限公司 | Perspective correction method and system for video stream dynamic image |
| CN113052920A (en) * | 2021-04-26 | 2021-06-29 | 歌尔光学科技有限公司 | Camera calibration method, device and computer readable storage medium |
| CN113239735A (en) * | 2021-04-15 | 2021-08-10 | 重庆利龙科技产业(集团)有限公司 | Automobile transparent A column system based on binocular camera and implementation method |
| CN114590202A (en) * | 2022-03-30 | 2022-06-07 | 润芯微科技(江苏)有限公司 | System and method for visualizing external part of automobile A column and automobile A column |
| CN117541517A (en) * | 2024-01-05 | 2024-02-09 | 深圳市欧冶半导体有限公司 | Dual-curvature imaging method, device, computer equipment and storage medium of CMS |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103358996A (en) * | 2013-08-13 | 2013-10-23 | 吉林大学 | Automobile A pillar perspective vehicle-mounted display device |
| CN206141433U (en) * | 2016-10-28 | 2017-05-03 | 重庆长安汽车股份有限公司 | Eliminate car view blind zone's device |
| CN107757481A (en) * | 2017-09-08 | 2018-03-06 | 吉林大学 | A kind of adjustable automobile transparent A column devices for adapting to driver's eyepoint height |
| CN108171673A (en) * | 2018-01-12 | 2018-06-15 | 京东方科技集团股份有限公司 | Image processing method, device, vehicle-mounted head-up-display system and vehicle |
| CN108340836A (en) * | 2018-04-13 | 2018-07-31 | 华域视觉科技(上海)有限公司 | A kind of automobile A column display system |
| CN108819895A (en) * | 2018-05-23 | 2018-11-16 | 浙江吉利汽车研究院有限公司 | A kind of vehicle-mounted panoramic image system |
| CN108876749A (en) * | 2018-07-02 | 2018-11-23 | 南京汇川工业视觉技术开发有限公司 | A kind of lens distortion calibration method of robust |
| CN109146980A (en) * | 2018-08-12 | 2019-01-04 | 浙江农林大学 | The depth extraction and passive ranging method of optimization based on monocular vision |
| CN109204144A (en) * | 2018-11-09 | 2019-01-15 | 椤圭ズ | A kind of the virtual reality display system and method for vehicle periphery scene |
| CN110246079A (en) * | 2019-05-23 | 2019-09-17 | 上海交通大学 | Camera distortion antidote, system and medium based on B-spline surface fitting |
| CN110276734A (en) * | 2019-06-24 | 2019-09-24 | Oppo广东移动通信有限公司 | Image distortion correction method and apparatus |
-
2019
- 2019-09-25 CN CN201910913907.XA patent/CN110728638A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103358996A (en) * | 2013-08-13 | 2013-10-23 | 吉林大学 | Automobile A pillar perspective vehicle-mounted display device |
| CN206141433U (en) * | 2016-10-28 | 2017-05-03 | 重庆长安汽车股份有限公司 | Eliminate car view blind zone's device |
| CN107757481A (en) * | 2017-09-08 | 2018-03-06 | 吉林大学 | A kind of adjustable automobile transparent A column devices for adapting to driver's eyepoint height |
| CN108171673A (en) * | 2018-01-12 | 2018-06-15 | 京东方科技集团股份有限公司 | Image processing method, device, vehicle-mounted head-up-display system and vehicle |
| CN108340836A (en) * | 2018-04-13 | 2018-07-31 | 华域视觉科技(上海)有限公司 | A kind of automobile A column display system |
| CN108819895A (en) * | 2018-05-23 | 2018-11-16 | 浙江吉利汽车研究院有限公司 | A kind of vehicle-mounted panoramic image system |
| CN108876749A (en) * | 2018-07-02 | 2018-11-23 | 南京汇川工业视觉技术开发有限公司 | A kind of lens distortion calibration method of robust |
| CN109146980A (en) * | 2018-08-12 | 2019-01-04 | 浙江农林大学 | The depth extraction and passive ranging method of optimization based on monocular vision |
| CN109204144A (en) * | 2018-11-09 | 2019-01-15 | 椤圭ズ | A kind of the virtual reality display system and method for vehicle periphery scene |
| CN110246079A (en) * | 2019-05-23 | 2019-09-17 | 上海交通大学 | Camera distortion antidote, system and medium based on B-spline surface fitting |
| CN110276734A (en) * | 2019-06-24 | 2019-09-24 | Oppo广东移动通信有限公司 | Image distortion correction method and apparatus |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111391755B (en) * | 2020-03-10 | 2021-10-12 | 京东方科技集团股份有限公司 | Display method, device and system of blind area image |
| CN111391755A (en) * | 2020-03-10 | 2020-07-10 | 京东方科技集团股份有限公司 | Display method, device and system of blind area image |
| CN111731187A (en) * | 2020-06-19 | 2020-10-02 | 杭州视为科技有限公司 | Automobile A-pillar blind area image display system and method |
| CN111915683A (en) * | 2020-07-27 | 2020-11-10 | 湖南大学 | Image position calibration method, intelligent device and storage medium |
| CN111951193A (en) * | 2020-08-21 | 2020-11-17 | 安谋科技（中国）有限公司 | Method and apparatus for correcting horizontal distortion of image |
| CN111951193B (en) * | 2020-08-21 | 2024-02-02 | 安谋科技（中国）有限公司 | Horizontal distortion correction method and horizontal distortion correction device for image |
| CN112634372A (en) * | 2020-11-27 | 2021-04-09 | 中山大学 | Real-time binocular camera correction method and device and storage medium |
| CN112634372B (en) * | 2020-11-27 | 2024-02-20 | 中山大学 | Real-time binocular camera correction method, device and storage medium |
| CN112712474A (en) * | 2020-12-16 | 2021-04-27 | 杭州小伴熊科技有限公司 | Perspective correction method and system for video stream dynamic image |
| CN113239735A (en) * | 2021-04-15 | 2021-08-10 | 重庆利龙科技产业(集团)有限公司 | Automobile transparent A column system based on binocular camera and implementation method |
| CN113239735B (en) * | 2021-04-15 | 2024-04-12 | 重庆利龙中宝智能技术有限公司 | Automobile transparent A column system based on binocular camera and implementation method |
| CN113052920A (en) * | 2021-04-26 | 2021-06-29 | 歌尔光学科技有限公司 | Camera calibration method, device and computer readable storage medium |
| CN113052920B (en) * | 2021-04-26 | 2022-11-22 | 歌尔光学科技有限公司 | Camera calibration method, device and computer readable storage medium |
| CN114590202A (en) * | 2022-03-30 | 2022-06-07 | 润芯微科技(江苏)有限公司 | System and method for visualizing external part of automobile A column and automobile A column |
| CN117541517A (en) * | 2024-01-05 | 2024-02-09 | 深圳市欧冶半导体有限公司 | Dual-curvature imaging method, device, computer equipment and storage medium of CMS |
| CN117541517B (en) * | 2024-01-05 | 2024-03-08 | 深圳市欧冶半导体有限公司 | Dual-curvature imaging method, device, computer equipment and storage medium of CMS |
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Address after: 230000 a10-01, 13 / F, block a, building J1, phase II, innovation industrial park, No. 2800, innovation Avenue, high tech Zone, Hefei, Anhui Province Applicant after: Hefei Jiangcheng Technology Co.,Ltd. Address before: 518000 Room 202, Jinke office building, No. 8, Qiongyu Road, Science Park community, Yuehai street, Nanshan District, Shenzhen, Guangdong Province Applicant before: SHENZHEN JIANG CHENG TECHNOLOGY Co.,Ltd. |
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| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200124 |