Camera roll angle calibration method based on coplanar plumb line group imaging

Abstract

The invention discloses a camera roll angle calibration method based on coplanar plumb line group imaging, relates to the technical field of parameter calibration of an aircraft flight pose vision measurement system, and aims to solve the problem of high-precision calibration of a camera roll angle of a two-axis turntable load. And a coplanar plumb line group calibration target is designed. The camera images plumb lines at different pitch angles of the rotary table, the included angle between each plumb line imaging straight line and an image longitudinal axis is calculated, a mapping straight line equation of the included angle and a plumb line serial number is fitted, and the roll angle of the camera is solved through intersection point optimization. The calibration target of the method is easy to manufacture, simple and convenient to operate and high in calibration precision, and can be widely applied to parameter calibration of an aircraft pose vision measurement system, a photoelectric theodolite and the like.

Description

Technical Field

[0001] This invention relates to the field of parameter calibration technology for aircraft flight attitude visual measurement systems, specifically a method for calibrating the roll angle of a camera based on an image composed of coplanar vertical lines. Background Technology

[0002] Two-axis turntables and their mounted cameras are core components of ground-based dynamic measurement systems such as aircraft attitude and position visual measurement systems. The calibration accuracy of the spatial rotation relationship (including azimuth, pitch, and roll angles) between the two-axis turntable's inner frame coordinate system and the camera's coordinate system directly affects the accuracy of aircraft attitude and position measurements in the north-south coordinate system. The precise calibration of the camera roll angle, as a critical parameter, is a technical bottleneck ensuring measurement accuracy.

[0003] Existing technologies are mainly divided into two categories: Hand-eye calibration methods: The Kronecker product is used to solve the hand-eye equation, and the spatial relationship between the turntable and the camera is nonlinearly optimized based on the AX=ZB model. These methods are limited by the turntable's degrees of freedom (only two rotation axes), have insufficient attitude sampling, and are sensitive to image noise during short-focus imaging, resulting in low robustness and limited roll angle calibration accuracy.

[0004] The forward and reverse mirror method calculates the azimuth and pitch angles through the imaging difference of the forward and reverse mirrors, but it cannot correlate the roll angle, making it difficult to achieve independent calibration of the roll angle.

[0005] In summary, existing technologies lack a high-precision, dedicated calibration method for the roll angle of a two-axis turntable-loaded camera, and there is an urgent need for a solution that is easy to operate, low-cost, and robust. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a high-precision calibration method for the roll angle of a camera under a two-axis turntable load. This method is based on the image-forming property of coplanar vertical lines, and obtains the roll angle by optimizing the solution of the intersection points of mapped lines. It can be combined with the forward and reverse mirror method to achieve overall accurate calibration of the spatial rotation relationship between the inner frame coordinate system of the two-axis turntable and the camera coordinate system, thereby improving the accuracy of dynamic measurement of aircraft flight attitude.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for calibrating the roll angle of a camera based on an image composed of coplanar vertical lines, comprising the following steps: S1. Construct a spatial transformation relationship model between a two-axis turntable and a camera, and define the camera roll angle γ as the rotation parameter between the turntable inner frame coordinate system and the camera coordinate system; S2. Deploy a coplanar plumb line group to calibrate the target. The target is composed of multiple coplanar plumb lines that are perpendicular to the horizontal plane. The plumb lines are evenly distributed in the horizontal direction in the plumb line coordinate system. S3. At different pitch angles of the turntable, the camera images the coplanar vertical line group to obtain multiple sets of image data; S4. For each pitch angle, extract the imaging center line of each plumb line in the image, and calculate the angle θ between the imaging center line of each plumb line and the vertical axis of the image. S5. For each pitch angle, fit a linear mapping equation between the included angle θ and the natural number of the vertical line to obtain multiple mapping lines; S6. Based on the intersection of all mapped lines, the optimal intersection coordinates are obtained through an optimization algorithm, and the ordinate value is the camera roll angle γ.

[0008] Preferably, the coplanar plumb line group target has 10 to 20 plumb lines, the width of the plumb line group is 500mm to 2000mm, the plumb lines are made of flexible material and are naturally suspended, and the ends are equipped with counterweights to maintain stability.

[0009] Preferably, the pitch angle of the turntable varies from -1° to 1°, and the pitch angle variation interval is from 0.02° to 0.1°.

[0010] Preferably, the extraction of the vertical centerline in step S4 employs a Gaussian curve fitting method, which includes converting the image to a grayscale image, fitting a Gaussian distribution line by line with the largest grayscale pixel as the center, calculating sub-pixel level center coordinates, and fitting the vertical imaging line equation based on the least squares method.

[0011] Preferably, the equation of the mapping line in step S5 is: , Where k i Let b be the slope. i X is the intercept. p This refers to the natural number of the plumb line or its actual horizontal position.

[0012] Preferably, the optimization algorithm in step S6 is the least squares method, and the objective function is to minimize the sum of squared distances from the intersection point to all mapped lines, specifically: , Where M is the number of mapping lines.

[0013] Preferably, the calibration method is combined with the forward and reverse mirror calibration method to simultaneously calibrate the azimuth, pitch, and roll angles of the camera on the two-axis turntable load.

[0014] Preferably, the method is applicable to parameter calibration in aircraft pose visual measurement systems or photoelectric theodolites, wherein the horizontal error of the two-axis turntable is controlled to less than 1.0 arcsecond by an electronic level.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention discovers the image-forming property of coplanar vertical lines. This imaging property reflects the uniqueness of the existence of a vertical line within the coplanar vertical line group when a two-axis turntable forms an image of coplanar vertical lines, where the angle between the vertical line and the image's vertical axis is equal to the camera's roll angle. Based on this, this invention obtains a unique vertical line and its corresponding angle with the image's vertical axis—that is, the camera's roll angle—by optimizing the minimum point of multiple "angle-position mapping lines."

[0016] 2. A method for extracting the center line of a vertical line in a composite image is proposed. This method performs Gaussian fitting on the gray value distribution of the vertical line image line by line, effectively extracting the sub-pixel level image coordinates of the vertical line center line, and then fitting the complete equation of the vertical line center line. It has strong robustness against image noise and effectively ensures the calibration accuracy of the camera roll angle.

[0017] 3. The various error factors affecting the camera roll angle calibration have a relatively weak impact on the final calibration error, and the calibration method has high calibration accuracy. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the aircraft pose visual measurement system of the present invention; Figure 2 This is a model diagram of the scene coordinate system for camera roll angle calibration according to the present invention; Figure 3 This is an example diagram of the included angle-position mapping line under different pitch angles according to the present invention; Figure 4 This is a schematic diagram of the extraction of the center line of the plumb line in this invention; Figure 5 This is a physical image of the coplanar plumb line group calibration target of the present invention; Figure 6 This is an example diagram of the image formed by plumb lines at different azimuth angles according to the present invention; Figure 7 This is a diagram showing the mapping relationship between the included angle and the vertical line number in this invention; Figure 8 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figures 1 to 8This invention provides a technical solution: a method for calibrating the roll angle of a camera based on an image composed of coplanar vertical lines, comprising the following steps: S1. Construct a spatial transformation relationship model between a two-axis turntable and a camera, and define the camera roll angle γ as the rotation parameter between the turntable inner frame coordinate system and the camera coordinate system; like Figure 1 As shown, a spatial transformation model between a two-axis turntable and a camera is established. A turntable base coordinate system is defined with the turntable's rotation center as the origin. .in, The axis is the pitch axis of the turntable. The axis is the turntable orientation axis. The axes satisfy the right-hand rule of the coordinate system. Define the coordinate system of the inner frame of the turntable. The origin of the coordinate system coincides with the origin of the turntable base coordinate system, and the coordinates are rotated sequentially around the turntable base coordinate system. shaft and Axis rotation azimuth angle and pitch angle Afterwards, the turntable base coordinate system can coincide with the turntable inner frame coordinate system. This method defines the coordinate system within the turntable inner frame. The axis is the forward axis of the turntable. Camera coordinate system. The spatial transformation relationship between the coordinate system of the turntable and the coordinate system of the inner frame is fixed. The axis represents the camera's optical axis. The axis is to the right along the horizontal direction of the camera target surface. The axis points vertically downwards along the camera target surface. The coordinate system is around the inner frame of the turntable. Rotate the axis -90° and translate the origin of the turntable's inner frame coordinate system to the origin of the camera's coordinate system to obtain the auxiliary turntable's inner frame coordinate system. The azimuth axes of the inner frame coordinate system of the auxiliary turntable are rotated sequentially. Pitch axis, pitch axis Shaft and roll shaft Axis rotation angle ,angle and angle This allows the coordinate system of the auxiliary inner frame to completely coincide with the camera coordinate system. Angle The roll angle of the camera under the load of a two-axis turntable.

[0021] S2. Deploy a coplanar plumb line group to calibrate the target. The target is composed of multiple coplanar plumb lines that are perpendicular to the horizontal plane. The plumb lines are evenly distributed in the horizontal direction in the plumb line coordinate system. like Figure 2 As shown, a set of N coplanar vertical lines existing in space constitutes a coplanar vertical line coordinate system. The origin is located at the center of the plumb line group. The axis is horizontal to the right. The axes are vertically downwards. The two-axis turntable is positioned in front of the vertical axis group, and the turntable base coordinate system... middle The axis is perpendicular to the horizontal plane, causing the inner frame of the turntable to rotate. Axis rotation pitch angle The camera mounted on the turntable images the plumb line group. Based on the spatial transformation relationships between the plumb line coordinate system, the turntable base coordinate system, the turntable inner frame coordinate system, and the camera coordinate system, the direction vector of the imaging line of any plumb line in the plumb line coordinate system can be derived, thus obtaining the relationship between the plumb line imaging line and the image's vertical axis. Angle between axes .

[0022] S3. At different pitch angles of the turntable, the camera images the coplanar vertical line group to obtain multiple sets of image data; Control the turntable to rotate around the pitch axis at multiple different pitch angles. The camera then images the plumb line group, acquiring an image sequence. The pitch angle range, interval, and number of images can be set according to actual needs.

[0023] Properties of images formed by coplanar vertical lines: Turntable base coordinate system Axis and vertical coordinate system The axes are parallel, and the azimuth angle of the turntable-loaded camera is [not specified]. and pitch angle Zero, turntable pitch angle When non-zero, along the vertical coordinate system There exists a unique vertical line along the axial direction, whose imaging line intersects the vertical axis of the image. Angle between axes Equal to the camera roll angle And the position of this plumb line and included angle With turntable pitch angle Irrelevant.

[0024] Prove the properties of images formed by coplanar vertical lines: like Figure 2 As shown, when the turntable-loaded camera is shooting at the vertical line group, it is difficult to guarantee the vertical coordinate system. In the plane and the base coordinate system of the turntable The planes are completely parallel, and there is an azimuth angle between them. The vertical coordinate system is around... Axis rotation angle and around Axis rotation Then, it can be aligned with the coordinate axes of the turntable base coordinate system. Therefore, the rotation matrix from the vertical coordinate system to the turntable base coordinate system... for (1) The translation vector between the two coordinate systems is (2) The pitch angle of the turntable is At that time, the rotation matrix between the turntable base coordinate system and the turntable inner frame coordinate system is: (3) The translation vector between the turntable base coordinate system and the turntable inner frame coordinate system is zero. The rotation matrix between the turntable inner frame coordinate system and the camera coordinate system can be obtained based on the camera azimuth, pitch, and roll angles. for (4) The translation vector from the turntable's inner frame coordinate system to the camera coordinate system is (5) like Figure 2 As shown, in the vertical coordinate system, the spatial coordinates of any two points on the vertical line are: (6) Based on the spatial transformation relationship between the plumb line coordinate system and the camera coordinate system, the spatial coordinates of two points in the camera coordinate system can be obtained as follows: (7) make (8) therefore, (9) Through vector and The cross product operation between them can obtain the plane in the camera coordinate system. The normal vector is (10) Through the image plane normal vector With plane The cross product of normal vectors yields the direction vector of the line intersecting the two planes, i.e., the direction vector of the vertical line image. (11) Calculate the vertical line image and the vertical axis of the image. Angle between axes for (12) When the camera azimuth angle and pitch angle When both are zero, the derivation can be obtained as follows: (13) like It is necessary to make (14) Right now (15) Divide both sides of equation (15) by The derivation yields... (16) When calibrating the camera roll angle, among the parameters included on the right side of equation (16), the azimuth angle is... Camera roll angle Translation components Translation components Translation components Since all values ​​are fixed, it can be concluded that when the camera azimuth angle... and pitch angle All are zero, and the turntable pitch angle is zero. At that time, in the vertical coordinate system There is only one vertical line on the axis, and the angle between it and the vertical axis of the image is the camera roll angle. And the position of the plumb line With turntable pitch angle Irrelevant.

[0025] S4. For each pitch angle, extract the imaging center line of each plumb line in the image, and calculate the angle between the imaging center line of each plumb line and the vertical axis of the image. θ ; For each elevation angle image, extract the imaging center line of each plumb line, and calculate the relationship between this center line and the image. Angle between axes The centerline extraction employs a sub-pixel level method, with the included angle... θ Calculated by the slope of the straight line.

[0026] Plumb line centerline extraction: Along the horizontal axis of the image, the grayscale values ​​of the plumb line exhibit a symmetrical distribution. Considering the imaging characteristics of the plumb line, to more accurately and stably extract the sub-pixel coordinates of the plumb line centerline, this method employs Gaussian curve fitting to extract the plumb line centerline and calculate the angle between the plumb line imaging line and the vertical axis of the image. Specifically, the acquired plumb line image is first converted into a single-channel grayscale image, and then the plumb line image is divided into sections based on the plumb line distribution. NEach image contains only one vertical line. For each vertical line image, the pixel position with the maximum gray value is found row by row. Using this position as the center, a Gaussian curve is fitted using the gray values ​​of the pixels on either side of it, such as... Figure 4 As shown. The maximum value of the Gaussian curve and its corresponding sub-pixel coordinates are calculated and used as the center of the vertical line corresponding to each row of pixels, thus obtaining the center line of each vertical line. Based on the sub-pixel coordinates of each row in the center line of the vertical line, the vertical line imaging line is fitted.

[0027] S5. For each pitch angle, fit a linear mapping equation between the included angle θ and the natural number of the vertical line to obtain multiple mapping lines; like Figure 3 As shown, for each pitch angle, the fitted mapping line equations are respectively For, among which and They represent the first The slope and intercept of the mapped line.

[0028] S6. Based on the intersection points of all mapped lines, the optimal intersection point coordinates are obtained through an optimization algorithm. The ordinate value of this optimal intersection point is the camera roll angle γ. The optimal intersection point coordinates are also obtained based on the mapped lines at all pitch angles through an optimization algorithm. Where the ordinate θ is the camera roll angle γ. The optimization objective is to minimize the sum of squared distances from the intersection point to all straight lines.

[0029] Based on the image properties of the coplanar plumb lines described above, the coplanar plumb line group is imaged at different turntable pitch angles. By determining the position of the plumb line that maintains a constant angle with the vertical axis of the image and is equal to the camera roll angle, the camera roll angle can be calibrated.

[0030] Specifically, the pitch axis around the turntable Shaft rotation M Next, at each turntable pitch angle Next, the camera images the plumb line group. The imaging lines of the plumb lines are obtained using a plumb line centerline extraction method, and the angle between each plumb line imaging line and the image's vertical axis is calculated based on the slope of the imaging lines. At different turntable pitch angles, fit multiple included angles in the plumb line group respectively. and corresponding vertical line position The mapping line between the two points (referred to as the "angle-position mapping line"). The fitted mapping line equations are as follows: ,in and They represent the first The slope and intercept of the mapped line. For example... Figure 3 As shown, in Within the tilt angle range of the turntable, images are captured on the plumb line group at 0.1° intervals to obtain mapping lines with different slopes corresponding to different turntable tilt angles. Ideally, the camera roll angle and the corresponding plumb line position can be obtained directly from the intersection of the mapping lines with different slopes. In actual calibration, due to various error factors, the fitted lines may not intersect at a single point. Therefore, this method first obtains the pairwise intersection points of all mapped lines, and then calculates the average value of all intersection points. To further improve the robustness of the camera roll angle calibration, this method uses the average value of the intersection points as the initial value, and uses least squares optimization to obtain the closest point to all mapped lines, which is used as the final solution for the camera roll angle and the corresponding plumb line position. In actual calibration, it is not necessary to obtain the specific plumb line position in the plumb line coordinate system. You can directly use the natural number index to replace the position. Establish the included angle Find the equation of the mapping line between the vertical line and the natural number sequence of the image line, and solve for the camera roll angle. The coplanar plumb line target consists of 10 to 20 plumb lines, with a width of 500mm to 2000mm. The plumb lines are made of flexible material and hang naturally, with counterweights at their ends for stability. The 10 to 20 plumb lines ensure sufficient sampling points to improve calibration accuracy. The target width of 500mm to 2000mm ensures uniform spacing between the plumb lines, covering the camera's field of view. The plumb lines are made of flexible material and hang naturally from the top of the support frame. Counterweights are placed at their ends in a water tank to accelerate them to stillness and maintain stability.

[0031] An LED background panel is set at the front of the target to improve the contrast between the plumb line and the background and reduce the influence of light and shadow.

[0032] The pitch angle of the turntable varies from -1° to 1° to balance the operating range and accuracy. The pitch angle variation interval is from 0.02° to 0.1° to ensure that the mapped straight line has sufficient difference.

[0033] In step S4, the extraction of the vertical centerline employs a Gaussian curve fitting method, which includes converting the image to grayscale, fitting a Gaussian distribution line by line with the largest grayscale pixel as the center, calculating sub-pixel-level center coordinates, and fitting the vertical imaging line equation based on the least squares method. Figure 4 As shown, the acquired color image is converted to a single-channel grayscale image, and the image is manually divided into N independent regions (N is the number of plumb lines), each region containing one plumb line. For each plumb line region, the following steps are performed line by line: 1. Find the pixel position with the largest grayscale value in the current row.

[0034] 2. Taking this position as the center, take the gray values ​​of 5 pixels to the left and right, and perform Gaussian curve fitting on the gray value distribution.

[0035] 3. Fitting a Gaussian curve G(x) = Aexp( (x μ) 2 / (2σ 2 ), where μ is the sub-pixel center coordinate. Based on the sub-pixel center points extracted from all rows, the equation of the vertical imaging line is fitted using the least squares method to calculate the included angle θ.

[0036] The equation of the mapping line in step S5 is: , Where k i Let b be the slope. i X is the intercept. p This refers to the natural number of the plumb line or its actual horizontal position.

[0037] The optimization algorithm in step S6 is the least squares method, and the objective function is to minimize the sum of squared distances from the intersection point to all mapped lines. The specific formula is as follows: , Where M is the number of mapping lines. The calibration method is combined with the forward and reverse mirror calibration method to simultaneously calibrate the azimuth, pitch, and roll angles of the camera on the two-axis turntable load. The roll angle calibration results are integrated with the forward and reverse mirror calibration results to obtain a complete turntable-camera spatial transformation relationship, thereby improving the overall measurement accuracy.

[0038] The method is applicable to parameter calibration in aircraft attitude visual measurement systems or photoelectric theodolites, wherein the horizontal error of the two-axis turntable is controlled to less than 1.0 arcsecond by an electronic level.

[0039] Example 1: Calibration Implementation under Standard Experimental Environment 1.1 Experimental System Setup In an indoor experimental environment, according to Figure 1 The diagram shows a complete aircraft pose visual measurement system. The core components of the system include: Two-axis turntable: azimuth axis rotation range 0°~360°, pitch axis rotation range -20°~190°, static angle accuracy ±10 arcseconds.

[0040] Camera: Equipped with a 30.2mm fixed-focus lens, image resolution of 2048×1440 pixels, and pixel size of 5μm×5μm.

[0041] Control system: Turntable motion control and image acquisition system based on industrial control computer.

[0042] 1.2 Preparation of calibration targets according to Figure 5 The following diagram shows the fabrication of a coplanar plumb line calibration target, with specific parameters as follows: Support frame: aluminum alloy structure, dimensions 1200mm×800mm×50mm.

[0043] Plumb line: 16 nylon lines with a diameter of 1.5mm, evenly distributed within a width of 1030mm.

[0044] Counterweight system: Each nylon line has a 500g lead weight suspended at the end and is placed in a water tank with a depth of 100mm.

[0045] Background panel: LED light-emitting panel, size 1200mm×800mm, providing uniform backlighting.

[0046] 1.3 Detailed steps of the calibration process Step 1: System Initialization and Leveling Use an electronic level to precisely level the two-axis turntable, ensuring that the perpendicularity error between the turntable base coordinate system azimuth axis and the horizontal plane is less than 1 arcsecond.

[0047] Adjust the camera's installation position and calibrate it with a theodolite to ensure that the camera's optical axis is parallel to the turntable's forward axis, and ensure that the camera's azimuth and pitch angles are less than 0.01°.

[0048] Place the coplanar plumb line target group directly in front of the turntable, with the center of the target aligned with the rotation center of the turntable, at a distance of about 3 meters.

[0049] Step 2: Image Acquisition Sequence Design The turntable's pitch angle range was set to ±0.5°. Image sequences were acquired at 25 different pitch angles at 0.04° intervals.

[0050] The results are as follows Figure 6 Examples of images formed by plumb lines at different azimuth angles are shown.

[0051] Step 3: Precisely extract the center line of the plumb line against Figure 4 The plumb line imaging features shown are processed using the following procedure: Image preprocessing: Converting color images to grayscale images.

[0052] Vertical region segmentation: Manually segment the image into 16 independent vertical regions.

[0053] Sub-pixel center extraction: For each vertical line region, perform the following row-by-row: Find the position of the maximum grayscale value in the current row; take the grayscale values ​​of 5 pixels to the left and right of this position as the center, and perform Gaussian curve fitting on the grayscale value distribution; Fit the Gaussian function: G(x)=Aexp( (x μ) 2 / (2σ 2 )) , calculate the sub-pixel level center coordinates μ.

[0054] Based on the obtained sub-pixel center point coordinates, the least squares method is used to fit the equation of the vertical line imaging line.

[0055] Step 4: Calculate the included angle and establish the mapping relationship Calculate the angle θ between the imaging line of each plumb line and the vertical axis (ov axis) of the image, for each pitch angle. Establish a mapping relationship between the included angle θ and the natural number sequence (1-16) of the vertical line.

[0056] Fitting linear equations: , where X p These are the vertical line numbers (1-16).

[0057] The results are as follows Figure 7 The diagram shows the mapping relationship between the included angle and the vertical line number.

[0058] Step 5: Optimize and solve the roll angle 1. Calculate the pairwise intersections of the 25 mapping lines, resulting in a total of C(25,2)=300 intersections.

[0059] 2. Calculate the average value (θ) of all intersection points. avg X avg ) as the initial solution.

[0060] 3. Solve for the optimal solution (θ) based on least squares optimization. opt X opt ): , The ordinate θ of the optimal solution opt This is the camera roll angle γ.

[0061] Example 2: Experiment on changes in azimuth angle of different targets To verify the robustness of the method to changes in target orientation, multiple sets of experiments were conducted: Experimental conditions: Keep the turntable position unchanged. Change the target azimuth angle : -20°, -10°, 0°, +10°, +20°.

[0062] Repeat the entire process of Example 1 at each azimuth angle. Experimental results: The calibration results under different target azimuth angles are as follows, and the standard deviation of the roll angle calibration is 2.02 arcseconds.

[0063]

[0064] Table 1 As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

Claims

1. A method for calibrating the roll angle of a camera based on an image composed of coplanar vertical lines, characterized in that: Includes the following steps: S1. Construct a spatial transformation relationship model between a two-axis turntable and a camera, and define the camera roll angle γ as the rotation parameter between the turntable inner frame coordinate system and the camera coordinate system; S2. Deploy a coplanar plumb line group to calibrate the target. The target is composed of multiple coplanar plumb lines that are perpendicular to the horizontal plane. The plumb lines are evenly distributed in the horizontal direction in the plumb line coordinate system. S3. At different pitch angles of the turntable, the camera images the coplanar vertical line group to obtain multiple sets of image data; S4. For each pitch angle, extract the imaging center line of each plumb line in the image, and calculate the angle θ between the imaging center line of each plumb line and the vertical axis of the image. S5. For each pitch angle, fit a linear mapping equation between the included angle θ and the natural number of the vertical line to obtain multiple mapping lines; S6. Based on the intersection of all mapped lines, the optimal intersection coordinates are obtained through an optimization algorithm, and the ordinate value is the camera roll angle γ.

2. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The coplanar plumb line group target has 10 to 20 plumb lines, the width of the plumb line group is 500mm to 2000mm, the plumb lines are made of flexible material and are naturally suspended, and the ends are equipped with counterweights to maintain stability.

3. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The pitch angle of the turntable varies from -1° to 1°, and the pitch angle variation interval is from 0.02° to 0.1°.

4. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: In step S4, the extraction of the vertical center line adopts the Gaussian curve fitting method, which includes converting the image into a grayscale image, fitting a Gaussian distribution line by line with the largest grayscale pixel as the center, calculating the sub-pixel level center coordinates, and fitting the vertical imaging line equation based on the least squares method.

5. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The equation of the mapping line in step S5 is: ， Where k i Let b be the slope. i X is the intercept. p This refers to the natural number of the plumb line or its actual horizontal position.

6. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The optimization algorithm in step S6 is the least squares method, and the objective function is to minimize the sum of squared distances from the intersection point to all mapped lines. The specific formula is as follows: ， Where M is the number of mapping lines.

7. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The calibration method, combined with the forward and reverse mirror calibration method, is used to simultaneously calibrate the azimuth, pitch, and roll angles of the camera on the two-axis turntable load.

8. The camera roll angle calibration method based on coplanar vertical lines forming an image according to claim 1, characterized in that: The method is applicable to parameter calibration in aircraft attitude visual measurement systems or photoelectric theodolites, wherein the horizontal error of the two-axis turntable is controlled to less than 1.0 arcsecond by an electronic level.

Images