Periscope camera assembly position correction method, correction system and assembly method

Abstract

The present application relates to camera technical field, disclose a kind of periscope camera assembly position correction method, correction system and assembly method, position correction method includes: obtaining the test image that the sensor board is output under the illumination of test light source;The test image is executed dark edge detection algorithm, at least one uniformity index that characterizes image brightness uniformity is obtained;Determine at least one of the lens assembly, prism and sensor board as adjustment component, and according to the uniformity index determine the displacement of adjustment component;According to the displacement determined drive the adjustment component moves.In the present application, the uniformity index is obtained by dark edge detection algorithm, and the displacement of adjustment component is determined according to the uniformity index, which can avoid the non-uniform image caused by reasonable error in the production process of each component, prevent the periscope camera after assembly from appearing color cast, effectively improve the imaging quality and stability of the whole periscope camera.

Description

Technical Field

[0001] This invention relates to the field of camera technology, and in particular to a method, system and assembly method for position correction of a periscope camera component. Background Technology

[0002] A periscope camera is a special camera module used in devices such as mobile phones or cameras. It achieves high optical zoom within a relatively small space through a folded optical path design. The periscope camera employs a folded optical path design, where light is refracted as it enters the lens assembly. Optical elements such as prisms cause the light path to change by 90°, thus enabling shooting at a longer focal length. This design allows the periscope camera to be placed parallel to the device surface, no longer limited by lens height, providing greater flexibility for the device's internal design.

[0003] A periscope camera consists of a base, a prism mounted on the base, a lens assembly, and a sensor board. The prism changes the direction of the light path, enabling high zoom capabilities without increasing the device's thickness, meeting the demands of modern thinner and lighter devices. Existing prisms have light-blocking grooves at their bottom to block stray light, and these grooves are coated with light-blocking material. However, assembly errors often exist in the prism, lens assembly, and sensor board. These errors cause the position of the light-blocking groove to deviate from its designed position relative to the lens assembly and sensor board after the periscope camera is put into use. This deviation results in the light-blocking groove blocking a small portion of the effective light path, ultimately leading to color cast in the image. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is to provide a periscope camera component position correction method, correction system and assembly method to solve the problem of color distortion in the image caused by the offset of the installation position of the existing periscope camera.

[0005] To solve the above-mentioned technical problems, one technical solution adopted by the present invention is: providing a periscope camera component position correction method for actively aligning the components of a periscope camera after coarse positioning, wherein the periscope camera components include a prism, a lens assembly, and a sensor board; comprising the following steps:

[0006] Acquire the test image output by the sensor board under the illumination of the test light source;

[0007] A dark edge detection algorithm is performed on the test image to obtain at least one uniformity index characterizing the brightness uniformity of the image;

[0008] At least one of the lens assembly, prism, and sensor plate is selected as the adjustment component, and the displacement of the adjustment component is determined according to the uniformity index.

[0009] The adjustment component is driven to move according to the determined displacement.

[0010] The dark edge detection algorithm includes the following sub-steps:

[0011] A central sub-block is defined in the central region of the test image, and four corner sub-blocks are defined in the four corner regions of the test image; the test image has a first side and a second side set opposite to each other, the two corner sub-blocks on the first side form a first set of edge regions, and the two corner sub-blocks on the second side form a second set of edge regions;

[0012] Calculate the brightness feature values ​​of the central sub-block and each of the corner sub-blocks respectively;

[0013] A uniformity index is generated based on the ratio of the brightness feature value of each corner sub-block to the brightness feature value of the center sub-block.

[0014] When determining the displacement of the adjustment component based on the uniformity index, the sum of the uniformity indices of the first group of edge regions is first compared with the sum of the uniformity indices of the second group of edge regions. Based on the comparison result, a brightness feature value or uniformity index of a corner sub-block is selected from the first group of edge regions and the second group of edge regions as a representative value. Then, a representative difference value is obtained based on the difference between the two representative values. The corresponding displacement is obtained based on the pre-determined relationship curve between the displacement and the change in the representative difference value, or the corresponding displacement is obtained based on a pre-trained AI learning model that predicts the displacement based on the representative difference value.

[0015] Furthermore, the two corner sub-blocks of the first group of edge regions are respectively the first corner sub-block and the second corner sub-block, and the two corner sub-blocks of the second group of edge regions are respectively the third corner sub-block and the fourth corner sub-block; the uniformity index includes a first luminance ratio representing the ratio of the luminance characteristic value of the first corner sub-block to the luminance characteristic value of the central sub-block, a second luminance ratio representing the ratio of the luminance characteristic value of the second corner sub-block to the luminance characteristic value of the central sub-block, a third luminance ratio representing the ratio of the luminance characteristic value of the third corner sub-block to the luminance characteristic value of the central sub-block, and a fourth luminance ratio representing the ratio of the luminance characteristic value of the fourth corner sub-block to the luminance characteristic value of the central sub-block.

[0016] Furthermore, when defining the central sub-block and the corner sub-blocks of the two sets of edge regions in the test image, the test image is divided into n×n block grids of the same size; the central sub-block is formed by taking i×i block grids in the region where the center point of the test image is located, and the corner sub-block is formed by taking i×i block grids at the corner point of the test image; where n is a positive integer greater than 3, and i is a positive integer greater than or equal to 1.

[0017] Furthermore, determining the displacement of the adjustment component based on the uniformity index includes the following sub-steps:

[0018] Calculate the sum of the first brightness ratio and the second brightness ratio, and the sum of the third brightness ratio and the fourth brightness ratio, respectively;

[0019] Based on the relationship between the sum of the first and second luminance ratios, and the sum of the third and fourth luminance ratios, a first edge ratio is selected from the first and second luminance ratios, and a second edge ratio is selected from the third and fourth luminance ratios; the absolute value of the difference between the first and second edge ratios is calculated to obtain a luminance range value as a representative difference value; or,

[0020] Based on the relationship between the sum of the first and second brightness ratios and the sum of the third and fourth brightness ratios, a first edge brightness is selected from the brightness feature values ​​of the first and second corner sub-blocks, and a second edge brightness is selected from the brightness feature values ​​of the third and fourth corner sub-blocks; the absolute value of the difference between the first and second edge brightness is calculated to obtain a brightness difference value as a representative difference value.

[0021] The displacement of the adjustment component is determined based on the representative difference value.

[0022] Furthermore, the method for selecting the first edge ratio and the second edge ratio is as follows:

[0023] If the sum of the first brightness ratio and the second brightness ratio is greater than the sum of the third brightness ratio and the fourth brightness ratio, then the larger of the first brightness ratio and the second brightness ratio is taken as the first edge ratio, and the smaller of the third brightness ratio and the fourth brightness ratio is taken as the second edge ratio.

[0024] Otherwise, the smaller of the first luminance ratio and the second luminance ratio is taken as the first edge ratio, and the larger of the third luminance ratio and the fourth luminance ratio is taken as the second edge ratio; or,

[0025] The method for selecting the first edge brightness and the second edge brightness is as follows:

[0026] If the sum of the first brightness ratio and the second brightness ratio is greater than the sum of the third brightness ratio and the fourth brightness ratio, the larger of the brightness characteristic values ​​of the first corner sub-block and the second corner sub-block is taken as the first edge brightness, and the smaller of the brightness characteristic values ​​of the third corner sub-block and the fourth corner sub-block is taken as the second edge brightness.

[0027] Otherwise, the smaller of the brightness feature values ​​of the first corner sub-block and the second corner sub-block is taken as the first edge brightness, and the larger of the brightness feature values ​​of the third corner sub-block and the fourth corner sub-block is taken as the second edge brightness.

[0028] Furthermore, the method for determining the displacement of the adjustment component based on the representative difference value is as follows:

[0029] Using a pre-established AI learning model, the brightness range value or brightness difference value is input into the AI ​​learning model, and the displacement amount that makes the uniformity index meet the preset conditions is output.

[0030] The AI ​​learning model is trained by collecting multiple sets of positional offset data and corresponding brightness range or brightness difference values. The positional offset data includes the displacement of the lens assembly and / or sensor plate relative to the prism; and / or...

[0031] The method for determining the displacement of the adjustment component based on the representative difference value includes the following sub-steps:

[0032] The measurement yields a first relationship curve between the displacement of the lens assembly relative to the prism along a first direction and the change in the brightness range or brightness difference value, and a second relationship curve between the displacement of the sensor plate relative to the prism along the first direction and the change in the brightness range or brightness difference value; the first direction is perpendicular to the axis of symmetry of the first side and the second side.

[0033] When the lens assembly is determined as the adjustment assembly, the displacement of the lens assembly is determined according to the first relationship curve; when the sensor plate is determined as the adjustment assembly, the displacement of the sensor plate is determined according to the second relationship curve; when there are multiple adjustment assemblies, the displacement of each adjustment assembly is determined by combining the first relationship curve and the second relationship curve.

[0034] The present invention also provides a periscope camera assembly method, comprising the following steps:

[0035] The lens assembly, prism, and sensor plate are coarsely positioned according to a preset location; the lens assembly faces one incident surface of the prism, and the sensor plate faces one exit surface of the prism.

[0036] A light source plate is fixedly placed on the object side of the lens assembly to provide a light source to the lens assembly;

[0037] The position of the lens assembly, prism, and sensor board is corrected using the periscope camera assembly position correction method described in any of the above embodiments.

[0038] After completing the position calibration, the lens assembly, prism, and sensor plate are fixed with adhesive.

[0039] Furthermore, the coarse positioning of the lens assembly, prism, and sensor board according to preset positions includes the following sub-steps:

[0040] The lens assembly, prism, and sensor board are sequentially loaded onto the support platform, and the prism is fixed in place.

[0041] The lens assembly and sensor plate are respectively clamped and moved relative to the prism to move them to preset positions; thereby aligning the lens assembly with the incident surface and the sensor plate with the exit surface.

[0042] The attitude of the lens assembly, prism and sensor board are measured separately until the relative tilt and vertical distance reach the preset attitude.

[0043] A light source plate is fixedly placed along the optical axis on the object side of the lens assembly.

[0044] The present invention also provides a periscope camera component position correction system for correcting the position of components of a periscope camera, wherein the periscope camera components include a prism, a lens assembly, and a sensor board, comprising:

[0045] A light source plate is fixedly mounted on the object side of the lens assembly to provide a uniform surface light source;

[0046] An active alignment device for driving the prism, lens assembly and sensor plate to move relative to the prism in at least one degree of freedom;

[0047] A control unit, communicatively connected to the sensor board and the active alignment device, is configured to perform the periscope camera assembly position correction method as described in any of the preceding claims.

[0048] In summary, the periscope camera component position correction method, correction system, and assembly method of the present invention have at least the following beneficial effects:

[0049] This invention uses a dark edge detection algorithm to detect the brightness uniformity of a test image, thereby obtaining a uniformity index. Based on this index, the displacement of adjustment components is determined, allowing for adjustment of the relative positions of the prism, lens assembly, and sensor plate. This avoids image inhomogeneity caused by reasonable errors in the manufacturing process of each component, preventing color casts in the assembled periscope camera and effectively improving the overall imaging quality and stability of the periscope camera. During the detection process, the image is meshed and divided into blocks. Five sub-blocks—the four corners and the center—are compared to calculate the brightness range or difference value. The corresponding adjustment displacement value can be obtained based on this value, enabling rapid adjustment and significantly improving the adjustment speed. Attached Figure Description

[0050] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0051] Figure 1 This is a flowchart of an embodiment of the periscope camera component position correction method of the present invention.

[0052] Figure 2 This is a schematic diagram illustrating the sub-distinction on the test image when the first and second sides are the left and right sides of the test image.

[0053] Figure 3 This is a schematic diagram illustrating the sub-distinction on the test image when the first and second sides are the upper and lower sides of the test image.

[0054] Figure 4 A flowchart for determining the displacement of the adjustment component based on the uniformity index.

[0055] Figure 5 This is a flowchart of an embodiment of the periscope camera assembly method of the present invention.

[0056] Figure 6 This is a schematic diagram showing the distribution of the prism, lens assembly, photosensitive component, sensor board, and light source board of a periscope camera.

[0057] The meanings of the labels in the attached diagram are as follows:

[0058] Prism 1; slotted structure 10; incident surface 11; exit surface 12; lens assembly 2; sensor board 3; light source board 4. Detailed Implementation

[0059] The following disclosure provides various embodiments or instances for implementing different features of this application. Specific examples of components and arrangements will be described below to simplify this application. Of course, these are merely examples and are not intended to limit this application. For example, in the following description, forming a first component above or on a second component may include embodiments where the first and second components are in direct contact, or embodiments where other components may be formed between the first and second components such that the first and second components are not in direct contact. Additionally, reference numerals and / or characters may be repeated in various instances within this application. Such repetition is for simplification and clarity and does not, in itself, indicate a relationship between the various embodiments and / or configurations.

[0060] Furthermore, spatial relation terms such as "below," "under," "below," "above," and "above" may be used herein to readily describe the relationship between one element or component and another element (or component) or component (or component) as shown in the figure. In addition to the orientations shown in the figure, spatial relation terms will encompass various different orientations of the device in use or operation. The device may be positioned in other ways (rotated 90 degrees or in other orientations) and will be interpreted accordingly through the spatial relation descriptors used herein.

[0061] Furthermore, the technical portions described in this application and the appended claims are primarily the improved technical portions of this application, and do not limit the object protected by this application to only having these technical portions. Other known essential components (structures and / or methods) and / or non-essential components of the object protected, besides the technical portions described in this application and the appended claims, are not included in this application and the appended claims because they do not fall within the scope of improvement of this application; however, this does not mean that the object protected by this application does not possess these known components.

[0062] Please see Figure 1 , Figure 1 This is a flowchart of an embodiment of the periscope camera component position correction method of the present invention. The periscope camera component position correction method of this embodiment is used to actively align the components of a periscope camera after coarse positioning. The periscope camera components include a prism 1, a lens assembly 2, and a sensor plate 3. The bottom of the prism 1 has a slotted structure 10 for blocking stray light. The sensor plate 3 generally includes an imaging chip, an FPC circuit board, a filter, and a filter holder, etc., and is mainly used for imaging. The periscope camera component position correction method of this embodiment includes the following steps:

[0063] S310. Acquire the test image output by the sensor board 3 under test light source illumination. During the manufacturing and testing of the periscope camera, the sensor board 3 outputs its generated test image under specific test light source illumination. Specifically, this process is a core step in verifying the quality and function of the image sensor. The test system provides light with known brightness, color temperature, and spectral distribution to the image sensor through a highly standardized optical system (such as the light source board 4). At this time, the photosensitive unit array (pixels) inside the sensor performs photoelectric conversion, converting the received light signal into a corresponding electrical signal, which is then processed by on-chip or external signal processing circuitry to finally output a digital test image.

[0064] S320. Perform a dark edge detection algorithm on the test image to obtain at least one uniformity index characterizing the brightness uniformity of the image. In this step, the dark edge detection algorithm may include the following sub-steps:

[0065] S321. Define a central sub-block in the central region of the test image, and define four corner sub-blocks in the four corner regions of the test image. The test image has a first side and a second side arranged opposite to each other. The two corner sub-blocks of the first side form a first set of edge regions, and the two corner sub-blocks of the second side form a second set of edge regions. Specifically, the two corner sub-blocks of the first set of edge regions are the first corner sub-block and the second corner sub-block, respectively, and the two corner sub-blocks of the second set of edge regions are the third corner sub-block and the fourth corner sub-block, respectively. It should be noted that the selection method of the first side and the second side is not fixed; they can be the left and right sides of the test image, or the top and bottom sides of the test image. When the selection methods of the first side and the second side are different, the positions of the first corner sub-block, the second corner sub-block, the third corner sub-block, and the fourth corner sub-block may also change.

[0066] For example, please see Figure 2 When the first side is the left side of the test image and the second side is the right side of the test image (i.e., the first side and the second side are symmetrical), the first corner sub-block and the second corner sub-block are located in the upper left corner and the lower left corner of the test image, respectively, and the third corner sub-block and the fourth corner sub-block are located in the upper right corner and the lower right corner of the test image, respectively.

[0067] Please see Figure 3 When the first side is the top side of the test image and the second side is the bottom side of the test image (i.e., the first side and the second side are symmetrical), the first corner sub-block and the second corner sub-block are located in the upper left and upper right corner areas of the test image, respectively, and the third corner sub-block and the fourth corner sub-block are located in the lower left and lower right corner areas of the test image, respectively.

[0068] When defining the central sub-block and the corner sub-blocks of the two sets of edge regions in the test image, the test image is divided into n×n block grids of the same size; the central sub-block is formed by taking i×i block grids in the area where the center point of the test image is located, and the corner sub-block is formed by taking i×i block grids at the corner point of the test image; where n is a positive integer greater than 3, and i is a positive integer greater than or equal to 1, generally n>3i.

[0069] The image is divided into an n×n grid of blocks, making the image processing more symmetrical and balancing data adaptability to some extent. This results in more uniform sampling and reduced differences in the length and width directions of the image, better matching the isotropic physical characteristics of lens assembly 2 itself. Furthermore, the symmetrical grid division allows for the replication of processing algorithms in the length and width directions during subsequent logical calculations. Five sub-blocks are selected from the center and four corners of the multiple grid blocks to capture the maximum brightness difference with the fewest data points. The center of the grid block, being the region with the shortest direct light path and least attenuation, is typically the most stable pixel location in the image. Since the brightness attenuation of the lens module is usually radially symmetrical, and according to the physical law of illuminance attenuation, the edge illuminance is proportional to the fourth power of the cosine of the incident angle of light. The incident angles at the four corners are the largest, so they are the areas most prone to uneven brightness. In addition, the selection of the four corners can also check the symmetry of the lens assembly 2 to a certain extent. Moreover, this method requires relatively less data, only accounting for a small part of the whole image, and can be used as a quick evaluation method for whether the image brightness is uniform. It can also more comprehensively evaluate the assembly error in the diagonal direction.

[0070] For example, the test image can be divided into a 20×20 grid, with five sub-blocks (center and four corners) of 1 / 10 width. Each sub-block consists of 2×2 blocks; that is, n=20, i=2. In this way, each sub-block contains four blocks, and the entire image is regularly divided. Subsequent interpolation algorithms are easier to implement, and the calculation process avoids abnormal brightness values ​​caused by strong textures, noise, or blemishes in individual blocks. By obtaining the brightness and averaging it within the 2×2 blocks, adjacent blocks can be covered within a small area, while avoiding excessive sampling and ensuring low data processing volume. This can smooth out local anomalies to a certain extent, making the obtained brightness values ​​closer to the true illumination level of the area and reducing sampling errors.

[0071] Please continue reading. Figure 3The following example illustrates the scenario where the first corner sub-block is located in the upper left corner of the test image, the second corner sub-block is located in the upper right corner of the test image, the third corner sub-block is located in the lower left corner of the test image, and the fourth corner sub-block is located in the lower right corner of the test image. In this case, the first side is the upper side of the test image, and the second side is the lower side of the test image.

[0072] S322. Calculate the brightness characteristic values ​​of the central sub-block and each of the corner sub-blocks respectively. When i=2, the central sub-block, the first corner sub-block, the second corner sub-block, the third corner sub-block, and the fourth corner sub-block are all 2×2 blocks. In this case, the formula for calculating the brightness characteristic value of the block can be as follows:

[0073] G = (GR + GB) / 2

[0074] Where G represents the brightness feature value of the block; GR represents the green pixel value located in the red pixel row of the block; and GB represents the green pixel value located in the blue pixel row of the block.

[0075] The above formula calculates the luminance value of the green channel using raw image data from a Bayer array. In a Bayer array, one row of pixels is arranged alternately as R, GR, R, GR, ..., with these green pixels in the same row as red pixels. Another row of pixels is arranged alternately as GB, B, GB, B, ..., with these green pixels in the same row as blue pixels. Since the human eye is most sensitive to green, and the number of green pixels in a Bayer array is twice that of red / blue, when calculating the luminance of a pixel location or performing uniformity analysis of the green channel, the two types of green pixels are often counted separately and then averaged to eliminate the influence of differences in row and column positions. This average value G can then be used as the luminance feature value of the block for subsequent luminance uniformity correction, white balance, or focus evaluation.

[0076] S323. Based on the ratio of the luminance feature value of each corner sub-block to the luminance feature value of the central sub-block, a uniformity index is generated for each. In this embodiment, the uniformity index includes a first luminance ratio Y1_Ratio representing the ratio of the luminance feature value of the first corner sub-block to the luminance feature value of the central sub-block, a second luminance ratio Y2_Ratio representing the ratio of the luminance feature value of the second corner sub-block to the luminance feature value of the central sub-block, a third luminance ratio Y3_Ratio representing the ratio of the luminance feature value of the third corner sub-block to the luminance feature value of the central sub-block, and a fourth luminance ratio Y4_Ratio representing the ratio of the luminance feature value of the fourth corner sub-block to the luminance feature value of the central sub-block. The luminance ratio can be expressed as a percentage.

[0077] The formula for calculating the first luminance ratio Y1_Ratio is:

[0078] Y1_Ratio=(area1 / area0)×100%

[0079] The formula for calculating the second luminance ratio Y2_Ratio is:

[0080] Y2_Ratio=(area2 / area0)×100%

[0081] The formula for calculating the third luminance ratio Y3_Ratio is:

[0082] Y3_Ratio=(area3 / area0)×100%

[0083] The formula for calculating the fourth luminance ratio, Y4_Ratio, is:

[0084] Y4_Ratio=(area4 / area0)×100%

[0085] Where area0 represents the brightness characteristic value of the central sub-block; area1 represents the brightness characteristic value of the first corner sub-block; area2 represents the brightness characteristic value of the second corner sub-block; area3 represents the brightness characteristic value of the third corner sub-block; and area4 represents the brightness characteristic value of the fourth corner sub-block.

[0086] In this embodiment, Y1_Ratio = Y_LT_Ratio; Y2_Ratio = Y_RT_Ratio; Y3_Ratio = Y_LB_Ratio; Y4_Ratio = Y_RB_Ratio. Wherein, Y_LT_Ratio represents the ratio of the luminance feature value of the upper-left sub-block to the luminance feature value of the central sub-block; Y_RT_Ratio represents the ratio of the luminance feature value of the upper-right sub-block to the luminance feature value of the central sub-block; Y_LB_Ratio represents the ratio of the luminance feature value of the lower-left sub-block to the luminance feature value of the central sub-block; and Y_RB_Ratio represents the ratio of the luminance feature value of the lower-right sub-block to the luminance feature value of the central sub-block.

[0087] S330. Determine at least one of the lens assembly 2, prism 1, and sensor plate 3 as an adjustment component, and determine the displacement of the adjustment component based on the uniformity index. When determining the displacement of the adjustment component based on the uniformity index, first compare the sum of the uniformity indices of the first group of edge regions with the sum of the uniformity indices of the second group of edge regions. Based on the comparison result, select the brightness feature value or uniformity index of a corner sub-block from the first group of edge regions and the second group of edge regions as a representative value. Then, obtain a representative difference value based on the difference between the two representative values. Obtain the corresponding displacement based on the pre-determined relationship curve between the displacement and the change in the representative difference value, or obtain the corresponding displacement based on a pre-trained AI learning model that predicts the displacement based on the representative difference value.

[0088] You can choose one of the lens assembly 2 and the sensor plate 3 as the adjustment component, so that only one component needs to be adjusted; of course, you can also choose to adjust the prism 1. In this case, you generally need to choose one or two more of the lens assembly 2 and the sensor plate 3 together with the prism 1 as the adjustment component.

[0089] Please see Figure 4 Determining the displacement of the adjustment component based on the uniformity index may include the following sub-steps:

[0090] S331. Calculate the sum of the first brightness ratio Y1_Ratio and the second brightness ratio Y2_Ratio, and the sum of the third brightness ratio Y3_Ratio and the fourth brightness ratio Y4_Ratio, respectively.

[0091] S332. Based on the relationship between the sum of the first brightness ratio and the second brightness ratio, and the sum of the third brightness ratio and the fourth brightness ratio, select a first edge ratio (i.e., a representative value of the sum of the first group of edge regions) from the first brightness ratio and the second brightness ratio, and select a second edge ratio (i.e., a representative value of the sum of the second group of edge regions) from the third brightness ratio and the fourth brightness ratio.

[0092] Specifically, if the sum of the first brightness ratio Y1_Ratio and the second brightness ratio Y2_Ratio is greater than the sum of the third brightness ratio Y3_Ratio and the fourth brightness ratio Y4_Ratio, then the larger of the first brightness ratio Y1_Ratio and the second brightness ratio Y2_Ratio is taken as the first edge ratio Y1_edge, and the smaller of the third brightness ratio Y3_Ratio and the fourth brightness ratio Y4_Ratio is taken as the second edge ratio Y2_edge.

[0093] Otherwise, the smaller of the first brightness ratio Y1_Ratio and the second brightness ratio Y2_Ratio is taken as the first edge ratio Y1_edge, and the larger of the third brightness ratio Y3_Ratio and the fourth brightness ratio Y4_Ratio is taken as the second edge ratio Y2_edge.

[0094] Next, the absolute value of the difference between the first edge ratio Y1_edge and the second edge ratio Y2_edge is calculated to obtain the brightness range value Y_Range as a representative difference value.

[0095] The above steps can be used to determine whether there is uneven brightness: Calculate the brightness ratio of the sub-blocks at the four corners relative to the sub-block at the center based on the brightness characteristic values, and calculate the brightness range Y_Range based on the four brightness ratios. Since the brightness range Y_Range = the maximum brightness ratio of the side with the larger sum of the brightness ratios of the sub-blocks - the minimum brightness ratio of the side with the smaller sum of the brightness ratios of the sub-blocks, if the brightness range Y_Range is 0, it indicates that the brightness of the test image is uniform; if the brightness range Y_Range is not 0, it indicates that there is uneven brightness in the test image.

[0096] The range value is obtained by comparing the relative brightness percentages of the four corners and selecting the maximum value, then subtracting the minimum value from the maximum value. This is a key step in image brightness uniformity assessment and correction. The range value determines the subsequent brightness compensation level, resulting in a normalized attenuation ratio. This provides a target benchmark for automatic exposure or digital gain, allowing for the acquisition of a compensation gain range while avoiding overcompensation and the introduction of excessive noise. The range value also allows detection of whether the attenuation at the four corners is consistent. A range value of 0 indicates uniform image brightness distribution without dark edges. A range value greater than 0 indicates a deviation between lens assembly 2 and / or sensor plate 3 and prism 1, thus enabling the evaluation of the symmetry of lens assembly 2, etc. Furthermore, the range value reflects the extreme points of the four boundaries in the image, thus better determining the distribution pattern of these five sub-blocks.

[0097] Of course, when the first side and the second side are selected as the left and right sides respectively, the same method can be used to calculate the brightness range value. Please refer to [link / reference needed]. Figure 2 At this point, the first set of edge regions is the left edge region, including the upper left corner block and the lower left corner block; the second set of edge regions is the right edge region, including the upper right corner block and the lower right corner block. The sum of the brightness ratios of the left edge region and the sum of the brightness ratios of the right edge region are compared in the same calculation method. If the brightness value of the left edge is greater than the brightness value of the right edge, the maximum value of the left edge is subtracted from the minimum value of the right edge, and vice versa. The brightness range value Y_Range is calculated.

[0098] Since the brightness range is a ratio, directly using the brightness range value for calculation increases the computational load. To facilitate subsequent data testing and calculation, this embodiment can also define a brightness difference value, which is used instead of the brightness range value as a representative difference value for calculation. In this case, in step S332, the first edge brightness is selected from the brightness feature value area1 of the first corner sub-block and the brightness feature value area2 of the second corner sub-block, and the second edge brightness is selected from the brightness feature value area3 of the third corner sub-block and the brightness feature value area4 of the fourth corner sub-block.

[0099] Specifically, if (Y1_Ratio+Y2_Ratio)>(Y3_Ratio+Y4_Ratio), then the larger of the brightness feature values ​​area1 of the first corner sub-block and area2 of the second corner sub-block is taken as the first edge brightness (i.e., the representative value of the sum of the first set of edge regions), and the smaller of the brightness feature values ​​area3 of the third corner sub-block and area4 of the fourth corner sub-block is taken as the second edge brightness (i.e., the representative value of the sum of the second set of edge regions). The brightness difference value obtained by subtracting the second edge brightness from the first edge brightness is taken as the representative difference value, i.e., max(area1,area2)-min(area3,area4). If (Y1_Ratio + Y2_Ratio) < (Y3_Ratio + Y4_Ratio), then the smaller of the brightness feature values ​​area1 of the first corner sub-block and area2 of the second corner sub-block is taken as the first edge brightness. The larger of the brightness feature values ​​area3 of the third corner sub-block and area4 of the fourth corner sub-block is taken as the second edge brightness. The brightness difference value is obtained by subtracting the first edge brightness from the second edge brightness, i.e., max(area3, area4) - min(area1, area2). In this way, the specific situation and gradient of the brightness difference can be obtained, so as to diagnose the position of the brightness deviation and thus decompose the specific compensation direction and gradient information.

[0100] Of course, since (Y1_Ratio+Y2_Ratio) and (area1+area2) are directly proportional, and (Y3_Ratio+Y4_Ratio) and (area3+area4) are also directly proportional, the comparison result of (area1+area2) and (area3+area4) can be used instead of the comparison result of (Y1_Ratio+Y2_Ratio) and (Y3_Ratio+Y4_Ratio), and the final result is the same.

[0101] S333. Determine the displacement of the adjustment component based on the representative difference value (i.e., brightness range value or brightness difference value). The method for determining the displacement of the adjustment component based on the brightness range value is as follows:

[0102] Using a pre-established AI learning model, the brightness range value or brightness difference value is input into the AI ​​learning model, and the displacement amount that makes the uniformity index meet the preset conditions is output. The AI ​​learning model is obtained by collecting multiple sets of positional offset data and corresponding brightness range values ​​or brightness difference values, whereby the positional offset data includes the displacement of the lens assembly and / or sensor plate relative to the prism.

[0103] This step may include the following sub-steps:

[0104] S333a, by measuring and obtaining a first relationship curve of the displacement of the lens assembly 2 relative to the prism 1 along the first direction and the change of the brightness range value or brightness difference value, and a second relationship curve of the displacement of the sensor plate 3 relative to the prism 1 along the first direction and the change of the brightness range value or brightness difference value; the first direction is perpendicular to the axis of symmetry of the first side and the second side.

[0105] S333b: When lens assembly 2 is determined as the adjustment component, the displacement of lens assembly 2 is determined according to the first relationship curve; when sensor plate 3 is determined as the adjustment component, the displacement of sensor plate 3 is determined according to the second relationship curve; when there are multiple adjustment components, the displacement of each adjustment component is determined by combining the first relationship curve and the second relationship curve.

[0106] The displacement of each adjustment component can be determined directly using steps S333a and S333b, or by executing steps S333a and S333b through an AI learning model.

[0107] In this embodiment, the brightness difference value is used as the adjustment target. Specifically, an xoy coordinate system is established on the image with the central sub-block as point O. The left and right directions of the image correspond to the x-axis, and the top and bottom directions correspond to the y-axis. In this embodiment, since the comparison is divided into top and bottom, the first direction is the y-axis. At this time, the prism 1 can be fixed, and the lens assembly 2 can be moved along the y-axis in a predetermined step, and the change in brightness difference value caused by each movement is recorded. In this embodiment, the brightness difference value of ±2 is used as the preset value for testing. The actual test data and calculation results are shown in Table 1. Wherein, LT represents the brightness value of the upper left corner, RT represents the brightness value of the upper right corner, LB represents the brightness value of the lower left corner, RB represents the brightness value of the lower right corner, and Y-TB represents the calculated brightness difference value between the upper and lower ends. TB represents the change in brightness difference caused by moving a unit distance after compensation to achieve uniform brightness. The test results obtained by fixing the prism 1 and moving the sensor plate 3 along the y-axis in a predetermined step are similar to those in Table 1 and will not be repeated here.

[0108]

[0109] Table 1

[0110] In addition, this embodiment also tested the first end and the second end as the left and right ends, respectively. In this case, the first direction is the x-axis. The prism 1 is fixed, and the lens assembly 2 is moved along the x-axis in predetermined steps. The change in brightness difference value caused by each movement is recorded. The actual test data and calculation results are shown in Table 2. In Table 2, Y-LR represents the calculated brightness difference value between the left and right ends, and LR represents the change in brightness difference caused by moving a unit distance after compensation to achieve uniform brightness. The test results obtained by fixing the prism 1 and moving the sensor plate 3 along the x-axis in predetermined steps are similar to those in Table 2 and will not be repeated here.

[0111]

[0112] Table 2

[0113] As shown in Tables 1 and 2, the change in brightness difference value is positively correlated with the change in brightness difference caused by moving a unit distance. The smaller the brightness difference value, the smaller the final change in brightness difference. Moreover, regardless of whether the movement is in the x-direction or the y-direction, the same trend of change is ultimately observed. This precisely illustrates that the optical behavior of the lens assembly 2 or the sensor plate 3 relative to the image in both directions is symmetrical or consistent. This indicates that a unified model can be established to perform compensation in both directions, and a uniform image can ultimately be obtained through this method.

[0114] After establishing a coordinate system based on the data in Table 2, a linear curve was plotted. Finally, the linear relationship formula was derived from the linear curve as follows:

[0115] Y=ax+b

[0116] Where Y represents the adjusted brightness difference value, x represents the amount of movement of the component along the first direction (e.g., the movement along the x-direction when the first end and the second end are the left and right ends respectively, and the movement along the y-direction when the first end and the second end are the top and bottom ends respectively), a is the change in brightness difference caused by the unit distance of movement, and b is the initial brightness difference value. It should be noted that the final linear relationship is not limited to the above formula.

[0117] S340. Drive the adjustment component to move according to the determined displacement. The above linear relationship can be introduced into the active alignment device (AA device). The active alignment device learns the linear changes recorded in this process until the brightness difference value is moved to the design position during the movement to obtain a uniform image. Thus, the algorithm formula can be directly used to quickly compensate and avoid color cast in the assembled periscope camera.

[0118] In this embodiment, a dark edge detection algorithm is used to detect the brightness uniformity of the test image, thereby obtaining a uniformity index. Based on the uniformity index, the displacement of the adjustment components is determined, thus adjusting the relative positions of prism 1, lens assembly 2, and sensor plate 3. This avoids image unevenness caused by reasonable errors in the manufacturing process of each component, prevents color cast in the assembled periscope camera, and effectively improves the overall imaging quality and stability of the periscope camera. Furthermore, during the detection process, the image is gridded and divided into blocks. Five sub-blocks—the four corners and the center—are compared to calculate the brightness range or brightness difference value. The corresponding adjustment displacement value can be obtained based on the brightness range or brightness difference value, allowing for rapid adjustment and significantly improving the adjustment speed.

[0119] Please see Figure 5 , Figure 5 This is a flowchart illustrating an embodiment of the periscope camera assembly method of the present invention. The periscope camera assembly method of this embodiment includes the following steps:

[0120] S100, please refer to Figure 6 The lens assembly 2, prism 1, and sensor plate 3 are coarsely positioned according to a preset location; the lens assembly 2 faces an incident surface of the prism 1, and the sensor plate 3 faces an exit surface of the prism 1. Coarse positioning of the lens assembly 2, prism 1, and sensor plate 3 according to the preset location may include the following sub-steps:

[0121] S110, Loading: Load the lens assembly 2, prism 1, and sensor plate 3 sequentially onto the support platform and fix the prism 1 in place. In this step, an active alignment device can be used to load the lens assembly 2 onto the LUT platform (Lens Under Test platform), and the prism 1 and sensor plate 3 onto the SUT platform (Sensor Under Test platform), wherein the lens assembly 2 and sensor plate 3 are respectively located on opposite sides of the prism 1. Then, the SUT platform uses vacuum suction to position the prism 1. It should be noted that the prism 1 is trapezoidal and has an incident surface 11 and an exit surface 12, both of which are located on the same side of the prism 1.

[0122] S120, Positioning: Clamp the lens assembly 2 and the sensor plate 3 respectively and move them relative to the prism 1 to move the lens assembly 2 and the sensor plate 3 to a preset position; thereby making the lens assembly 2 correspond to the incident surface and the sensor plate 3 correspond to the exit surface.

[0123] In this step, the first gripper is used to grasp the lens assembly 2 and move it initially to a preset position corresponding to the incident surface of the prism 1. The second gripper is used to grasp the sensor plate 3 and move it initially to a preset position corresponding to the exit surface of the prism 1. Afterwards, the prism 1, lens assembly 2, and sensor plate 3 are positioned visually from front to back to ensure they are in the preset positions. If any component is not in the preset position, its position can be moved and adjusted using the corresponding gripper or the SUT platform.

[0124] S130. Inspection: Perform attitude measurements on lens assembly 2, prism 1, and sensor plate 3 respectively until the relative tilt and vertical distance reach the preset attitude. After initial visual positioning, perform laser attitude measurements on prism 1, lens assembly 2, and sensor plate 3 respectively. By measuring their relative tilt and vertical distance using lasers, for components that are not in the preset position or attitude, adjust their complete attitude using the corresponding grippers or SUT platform. Finally, reposition prism 1, lens assembly 2, and sensor plate 3 again using visual positioning to ensure the accuracy of each component.

[0125] S200: A light source plate 4 is fixedly placed on the object side of the lens assembly 2 to provide a light source to the lens assembly 2. In this step, the light source plate 4 remains stationary and emits light to the lens assembly 2. The light is focused by the lens assembly 2 onto the incident surface and undergoes three reflections in the prism 1 before exiting from the exit surface to the sensor plate 3 for imaging processing.

[0126] S300. The position correction method of the periscope camera assembly described in any of the above embodiments is used to correct the position of the lens assembly 2, prism 1, and sensor plate 3. The image output by the sensor plate 3 is divided into multiple block grids, and multiple sub-blocks are selected from different positions on the multiple block grids, thereby discretizing the complete image. By selecting local positions instead of the global mean, interference such as noise caused by full image processing can be avoided in the entire improvement process. Replacing the whole image with local sub-blocks can effectively reduce the computational load. The brightness difference value is calculated, and the lens assembly 2 and / or sensor plate 3 are moved according to the obtained brightness difference value for correction compensation.

[0127] If higher accuracy is required, this step can be repeated. When repeating this step, the first and second ends can be reselected. For example, if the top and bottom of the test image are used as the first and second ends respectively during the first execution of this step, in subsequent executions, it is not necessary to continue using the top and bottom of the test image as the first and second ends respectively. Instead, the left and right ends of the test image can be used as the first and second ends respectively, or the two selection methods can be alternated until a uniform image is obtained, thus completing the calibration.

[0128] It should be noted that after obtaining the brightness difference value, the sensor plate 3 is usually used as the main adjustment component. The positions of the prism 1 and lens assembly 2 are usually determined in the early positioning, but the movement of the prism 1 and / or lens assembly 2 is not excluded.

[0129] S400. After completing the position correction, apply adhesive to fix the lens assembly 2, prism 1 and sensor board 3. After the adhesive has solidified, the periscope camera assembly is completed.

[0130] In this embodiment, before the periscope camera is put into use, the brightness uniformity of the image is detected. During the detection process, the image is gridded and divided into blocks. Five blocks, including the four corners and the center, are compared and calculated to quickly obtain the brightness range value or brightness difference value. By importing the brightness range value or brightness difference value into the active alignment device to control the relative position adjustment of the lens assembly 2, sensor plate 3 or prism 1, the image can be quickly adjusted to be uniform, avoiding the image non-uniformity caused by reasonable errors in the production process of each component. This effectively improves the imaging quality and stability of the entire periscope camera and ensures that the positions of prism 1, lens assembly 2 and sensor plate 3 are in the optimal position.

[0131] This invention also discloses a periscope camera component position correction system for correcting the position of periscope camera components, wherein the periscope camera components include a prism 1, a lens assembly 2, and a sensor plate 3. The periscope camera component position correction system includes a light source plate 4, an active alignment device, and a control unit. The light source plate 4 is fixedly disposed on the object side of the lens assembly 2 and is used to provide a uniform surface light source. The active alignment device is used to drive the prism 1, lens assembly 2, and sensor plate 3 to move relative to the prism 1 in at least one degree of freedom. The control unit is communicatively connected to the sensor plate 3 and the active alignment device, and the control unit is configured to perform the periscope camera component position correction method described above.

[0132] The control unit may include an image acquisition module, a dark edge algorithm module, a displacement determination module, and a movement control module. The image acquisition module is used to acquire the test image output by the sensor board 3; and to complete step S310 in the periscope camera component position correction method described above.

[0133] The dark edge algorithm module is used to perform a dark edge detection algorithm on the test image to obtain a uniformity index; thus completing step S320 in the periscope camera component position correction method described above.

[0134] The displacement determination module is used to determine the displacement of the adjustment component based on the uniformity index, thus completing steps S331 to S333 in the periscope camera component position correction method described above. The displacement determination module may include an AI learning model, which takes the brightness range or brightness difference value calculated based on the uniformity index as input and the displacement as output.

[0135] The motion control module is used to send control commands to the active alignment device to drive the adjustment component to move, thereby working with the active alignment device to complete step S340 in the periscope camera component position correction method described above.

[0136] The periscope camera component position correction system of the present invention detects the brightness uniformity of the test image through a dark edge algorithm module to obtain a uniformity index. The displacement determination module determines the displacement of the adjustment components based on the uniformity index, thereby adjusting the relative positions of the prism 1, lens assembly 2, and sensor plate 3. This avoids image non-uniformity caused by reasonable errors in the production process of each component, prevents color cast in the assembled periscope camera, and effectively improves the imaging quality and stability of the entire periscope camera. Furthermore, it can obtain the corresponding adjustment displacement based on the brightness range value or brightness difference value, thereby enabling rapid adjustment and greatly improving the adjustment speed.

[0137] The above embodiments merely illustrate preferred implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention should be determined by the appended claims.

Claims

1. A method for position correction of a periscope camera assembly, used to actively align the components of a periscope camera after coarse positioning, wherein the periscope camera assembly includes a prism, a lens assembly, and a sensor plate; characterized in that, Includes the following steps: Acquire the test image output by the sensor board under the illumination of the test light source; A dark edge detection algorithm is performed on the test image to obtain at least one uniformity index characterizing the brightness uniformity of the image; At least one of the lens assembly, prism, and sensor plate is selected as the adjustment component, and the displacement of the adjustment component is determined according to the uniformity index. The adjustment component is driven to move according to the determined displacement. The dark edge detection algorithm includes the following sub-steps: A central sub-block is defined in the central region of the test image, and four corner sub-blocks are defined in the four corner regions of the test image; the test image has a first side and a second side set opposite to each other, the two corner sub-blocks on the first side form a first set of edge regions, and the two corner sub-blocks on the second side form a second set of edge regions; Calculate the brightness feature values ​​of the central sub-block and each of the corner sub-blocks respectively; A uniformity index is generated based on the ratio of the brightness feature value of each corner sub-block to the brightness feature value of the center sub-block. When determining the displacement of the adjustment component based on the uniformity index, the sum of the uniformity indices of the first group of edge regions is first compared with the sum of the uniformity indices of the second group of edge regions. Based on the comparison result, the brightness characteristic value or uniformity index of a corner sub-block is selected from the first group of edge regions and the second group of edge regions respectively as a representative value. Then, based on the difference between the two representative values, a representative difference value is obtained. The corresponding displacement is obtained according to the pre-determined relationship curve between the displacement and the change in the representative difference value, or the corresponding displacement is obtained according to a pre-trained AI learning model that predicts the displacement based on the representative difference value.

2. The periscope camera component position correction method as described in claim 1, characterized in that: The two corner sub-blocks of the first group of edge regions are the first corner sub-block and the second corner sub-block, and the two corner sub-blocks of the second group of edge regions are the third corner sub-block and the fourth corner sub-block, respectively. The uniformity index includes a first luminance ratio, which represents the ratio of the luminance characteristic value of the first corner sub-block to the luminance characteristic value of the central sub-block; a second luminance ratio, which represents the ratio of the luminance characteristic value of the second corner sub-block to the luminance characteristic value of the central sub-block; a third luminance ratio, which represents the ratio of the luminance characteristic value of the third corner sub-block to the luminance characteristic value of the central sub-block; and a fourth luminance ratio, which represents the ratio of the luminance characteristic value of the fourth corner sub-block to the luminance characteristic value of the central sub-block.

3. The periscope camera component position correction method as described in claim 2, characterized in that: When defining the central sub-block and the corner sub-blocks of the two sets of edge regions in the test image, the test image is divided into n×n block grids of the same size; the central sub-block is formed by taking i×i block grids in the region where the center point of the test image is located, and the corner sub-block is formed by taking i×i block grids at the corner point of the test image; where n is a positive integer greater than 3, and i is a positive integer greater than or equal to 1.

4. The periscope camera component position correction method as described in claim 2, characterized in that, Determining the displacement of the adjustment component based on the uniformity index includes the following sub-steps: Calculate the sum of the first brightness ratio and the second brightness ratio, and the sum of the third brightness ratio and the fourth brightness ratio, respectively; Based on the relationship between the sum of the first brightness ratio and the second brightness ratio, and the sum of the third brightness ratio and the fourth brightness ratio, a first edge ratio is selected from the first brightness ratio and the second brightness ratio, and a second edge ratio is selected from the third brightness ratio and the fourth brightness ratio; the absolute value of the difference between the first edge ratio and the second edge ratio is calculated to obtain the brightness range value as the representative difference value; or, Based on the relationship between the sum of the first brightness ratio and the second brightness ratio, and the sum of the third brightness ratio and the fourth brightness ratio, the first edge brightness is selected from the brightness feature values ​​of the first corner sub-block and the second corner sub-block, and the second edge brightness is selected from the brightness feature values ​​of the third corner sub-block and the fourth corner sub-block. Calculate the absolute value of the difference between the brightness of the first edge and the brightness of the second edge, and use the brightness difference value as the representative difference value. The displacement of the adjustment component is determined based on the representative difference value.

5. The periscope camera component position correction method as described in claim 4, characterized in that, The method for selecting the first edge ratio and the second edge ratio is as follows: If the sum of the first brightness ratio and the second brightness ratio is greater than the sum of the third brightness ratio and the fourth brightness ratio, then the larger of the first brightness ratio and the second brightness ratio is taken as the first edge ratio, and the smaller of the third brightness ratio and the fourth brightness ratio is taken as the second edge ratio. Otherwise, the smaller of the first luminance ratio and the second luminance ratio is taken as the first edge ratio, and the larger of the third luminance ratio and the fourth luminance ratio is taken as the second edge ratio; or, The method for selecting the first edge brightness and the second edge brightness is as follows: If the sum of the first brightness ratio and the second brightness ratio is greater than the sum of the third brightness ratio and the fourth brightness ratio, the larger of the brightness characteristic values ​​of the first corner sub-block and the second corner sub-block is taken as the first edge brightness, and the smaller of the brightness characteristic values ​​of the third corner sub-block and the fourth corner sub-block is taken as the second edge brightness. Otherwise, the smaller of the brightness feature values ​​of the first corner sub-block and the second corner sub-block is taken as the first edge brightness, and the larger of the brightness feature values ​​of the third corner sub-block and the fourth corner sub-block is taken as the second edge brightness.

6. The periscope camera component position correction method as described in claim 4, characterized in that, The method for determining the displacement of the adjustment component based on the representative difference value is as follows: Using a pre-established AI learning model, the brightness range value or brightness difference value is input into the AI ​​learning model, and the displacement amount that makes the uniformity index meet the preset conditions is output. The AI ​​learning model is trained by collecting multiple sets of positional offset data and corresponding brightness range or brightness difference values. The positional offset data includes the displacement of the lens assembly and / or sensor plate relative to the prism; and / or... The method for determining the displacement of the adjustment component based on the representative difference value includes the following sub-steps: The measurement yields a first relationship curve between the displacement of the lens assembly relative to the prism along a first direction and the change in the brightness range or brightness difference value, and a second relationship curve between the displacement of the sensor plate relative to the prism along the first direction and the change in the brightness range or brightness difference value; the first direction is perpendicular to the axis of symmetry of the first side and the second side. When the lens assembly is determined as the adjustment assembly, the displacement of the lens assembly is determined according to the first relationship curve; when the sensor plate is determined as the adjustment assembly, the displacement of the sensor plate is determined according to the second relationship curve; when there are multiple adjustment assemblies, the displacement of each adjustment assembly is determined by combining the first relationship curve and the second relationship curve.

7. A method for assembling a periscope camera, characterized in that, Includes the following steps: The lens assembly, prism, and sensor plate are coarsely positioned according to a preset location; the lens assembly faces one incident surface of the prism, and the sensor plate faces one exit surface of the prism. A light source plate is fixedly placed on the object side of the lens assembly to provide a light source to the lens assembly; The position correction method for the periscope camera assembly as described in any one of claims 1 to 6 is used to correct the position of the lens assembly, prism, and sensor board. After completing the position calibration, the lens assembly, prism, and sensor plate are fixed with adhesive.

8. The periscope camera assembly method as described in claim 7, characterized in that, The coarse positioning of the lens assembly, prism, and sensor board according to the preset positions includes the following sub-steps: The lens assembly, prism, and sensor board are sequentially loaded onto the support platform, and the prism is fixed in place. The lens assembly and sensor plate are respectively clamped and moved relative to the prism to move them to preset positions; thereby aligning the lens assembly with the incident surface and the sensor plate with the exit surface. The attitude of the lens assembly, prism and sensor board are measured separately until the relative tilt and vertical distance reach the preset attitude. A light source plate is fixedly placed along the optical axis on the object side of the lens assembly.

9. A periscope camera component position correction system for correcting the position of components of a periscope camera, wherein the periscope camera components include a prism, a lens assembly, and a sensor board, characterized in that, include: A light source plate is fixedly mounted on the object side of the lens assembly to provide a uniform surface light source; An active alignment device for driving the prism, lens assembly and sensor plate to move relative to the prism in at least one degree of freedom; A control unit is communicatively connected to the sensor board and the active alignment device, and the control unit is configured to perform the periscope camera assembly position correction method as described in any one of claims 1 to 6.

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