Method for testing projection clarity, projector and medium

Abstract

This application relates to the field of image processing technology, and provides a method for testing projection sharpness, a projector, and a medium. The method includes: generating a unit pattern containing multiple binary barcodes in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes both horizontal and vertical directions; copying the unit pattern to cover the entire projection image resolution range of the projector to form a test pattern; projecting the test pattern into the projection plane to generate stripes with different spatial frequencies corresponding to the meridional and sagittal directions within the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector; acquiring stripe images at the center and four corner positions corresponding to the projection area; processing the acquired stripe images to obtain the projection sharpness test result of the projector.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method for testing the projection sharpness of a projector, a projector, and a medium. Background Technology

[0002] In the field of structured light 3D reconstruction, the image sharpness and consistency of the projection lens in a DLP projector are key factors affecting the 3D reconstruction effect. Currently, projector sharpness detection typically relies on human observation or industrial camera assistance, but this presents two major problems:

[0003] 1. The projection patterns used in the testing lack standardized design. The spatial frequency, fringe direction and distribution of different patterns vary significantly, resulting in inconsistent testing standards and making it difficult to quantitatively evaluate the imaging performance of the projection lens.

[0004] 2. Existing methods can only perform blur detection on local areas or in a single direction, and cannot cover the entire area of ​​the projection frame (such as the center and four corners) and the imaging characteristics in both meridional and sagittal directions. It is difficult to quickly determine the imaging consistency of the projection lens in different positions and directions, resulting in low assembly and debugging efficiency.

[0005] Therefore, a method is urgently needed to solve at least one of the above problems. Summary of the Invention

[0006] This application provides a method for testing projection sharpness, a projector, and a medium, aiming to address the problem that while some research has attempted to assist in fault location through simulation modeling or machine learning, a systematic solution has not yet been formed in the prior art.

[0007] In a first aspect, embodiments of this application provide a method for testing image projection sharpness, the method comprising:

[0008] A unit pattern containing multiple binary barcodes is generated in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes horizontal and vertical directions;

[0009] The unit pattern is copied and spread across the entire projection image resolution range of the projector to form a test pattern;

[0010] The test pattern is projected in the projection, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector.

[0011] Obtain the stripe images at the center and four corners of the projected image, process the obtained stripe images, and obtain the projection clarity test results of the projector.

[0012] In some embodiments, the projection sharpness test result includes the imaging sharpness and imaging consistency information of the projector's projection lens; the process of processing the acquired striped image to obtain the projection sharpness test result of the projector includes: calculating the stripe contrast based on the peak gray value and trough gray value of the striped image; and obtaining the imaging sharpness and imaging consistency information based on the stripe contrast.

[0013] In some embodiments, the imaging sharpness and imaging consistency information includes first imaging sharpness and imaging consistency information and second imaging sharpness and imaging consistency information; obtaining the imaging sharpness and imaging consistency information based on the stripe contrast includes: comparing the contrast of stripes with the same spatial frequency at the center position and the four corner positions of the projected image, and obtaining the first imaging sharpness and imaging consistency information based on the comparison result; comparing the contrast of stripes with different spatial frequencies at the same position with a preset contrast threshold of the corresponding spatial frequency, and obtaining the second imaging sharpness and imaging consistency information based on the comparison result.

[0014] In some embodiments, the step of copying the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern includes: arranging the binary barcode into basic units according to the horizontal and vertical stripe directions, and copying and filling the basic units in rows and columns within the projection image resolution range so that stripes of different spatial frequencies and directions are evenly distributed throughout the entire test pattern.

[0015] In some embodiments, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and having the stripes distributed at various positions within the projection frame of the projector, includes: optically magnifying the test pattern through a projection lens, so that the horizontal stripes in the test pattern correspond to the sagittal direction stripes, and the vertical stripes correspond to the meridional direction stripes, and the magnified stripes are evenly distributed at different spatial frequencies in the center and four corner areas of the projection frame.

[0016] In some embodiments, acquiring the stripe images at the center and four corners of the projected image includes: acquiring images of the stripes at the geometric center and multiple corners of the projected image using a high-resolution industrial camera to ensure that the acquired images cover key areas of the projected image; wherein the corners include the upper left corner, upper right corner, lower left corner, and lower right corner.

[0017] In some embodiments, the method further includes: if it is necessary to adjust the focusing effect of the projector's projection lens, by adjusting the working distance and lens group spacing of the projection lens, acquiring the stripe image at the center position in real time during the adjustment process of the projection lens and calculating the contrast of the corresponding spatial frequency stripe until the contrast of the stripe at the center position reaches the preset focusing contrast threshold, thereby completing the focusing adjustment.

[0018] In some embodiments, the method further includes: if it is necessary to adjust the projection angle of the projector, by acquiring stripe images at the center and four corners of the projected image and calculating the contrast of the corresponding spatial frequency stripes, adjusting the projection angle according to the contrast difference between the center and the four corners until the contrast difference of the stripes at each position is less than a preset consistency threshold, thus completing the projection angle adjustment.

[0019] Secondly, embodiments of this application provide a projector, the projector including a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and, when executing the computer program, implement the method provided in any embodiment of this application.

[0020] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the method provided in any embodiment of this application.

[0021] This application utilizes a pre-defined binary barcode pattern design with preset sizes (2 pixels / lp, 4 pixels / lp, 8 pixels / lp, 16 pixels / lp) and bidirectional (horizontal and vertical) orientations to create standardized test patterns. This avoids the inconsistency in testing standards caused by pattern differences in existing technologies, enabling quantitative analysis of image sharpness. By acquiring stripe images from the center and four corners of the projection frame and combining them with contrast calculations of stripes at different spatial frequencies, the imaging sharpness of the projection lens in both meridional and sagittal directions, as well as the imaging consistency across the entire frame, can be simultaneously detected, solving the problem of partial detection in existing technologies. Based on the quantified contrast results, the focus adjustment (such as working distance and lens group spacing) and projection angle adjustment of the projection lens can be quickly guided, significantly improving assembly and debugging efficiency and avoiding the subjectivity and inefficiency of human observation.

[0022] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

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

[0024] Figure 1 This is a schematic flowchart illustrating the steps of a projection sharpness testing method provided in an embodiment of this application;

[0025] Figure 2 This is a schematic diagram of a projection pattern with an image resolution of 912×1140 provided in one embodiment of this application;

[0026] Figure 3 This is a schematic diagram of a projection pattern with an image resolution of 1920×1080 provided in an embodiment of this application;

[0027] Figure 4 This is a schematic diagram of a unit pattern provided in an embodiment of this application, with the corresponding stripe sizes being 2 pixels / lp, 4 pixels / lp, 8 pixels / lp, and 16 pixels / lp, respectively.

[0028] Figure 5 This is a schematic diagram of the focusing process provided in an embodiment of this application;

[0029] Figure 6 This is a schematic diagram of an embodiment of the present application, which shows how to select 4lp / mm fringes in the sagittal direction, count the gray values ​​of the peaks and valleys of 8 periods, and calculate the fringes contrast.

[0030] Figure 7 This is a schematic diagram of the angle adjustment process provided in an embodiment of this application;

[0031] Figure 8 This is a schematic diagram of the analysis of stripes at various positions after the angle is adjusted, the thinnest stripe in the sagittal direction is selected, and the grayscale information of 10 periodic stripes is statistically analyzed, provided by an embodiment of this application.

[0032] Figure 9 This is a record and label shown according to an embodiment of this application. Figure 12 Schematic diagram of corresponding stripe peak and trough values;

[0033] Figure 10 This is a schematic diagram of the analysis of stripes at various positions after the angle is adjusted, the thinnest stripe in the sagittal direction is selected, and the grayscale information of 10 periodic stripes is statistically analyzed, provided by an embodiment of this application.

[0034] Figure 11 This is a record and label shown according to an embodiment of this application. Figure 10Schematic diagram of corresponding stripe peak and trough values;

[0035] Figure 12 This is a schematic block diagram of the structure of an image sharpness testing device provided in one embodiment of this application;

[0036] Figure 13 This is a schematic block diagram of the structure of a projector provided in one embodiment of this application.

[0037] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Detailed Implementation

[0038] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0039] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0040] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0041] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0042] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0043] In the field of structured light 3D reconstruction, the image sharpness and consistency of the projection lens in a DLP projector are key factors affecting the 3D reconstruction effect. Currently, projector sharpness detection typically relies on human observation or industrial camera assistance, but this presents two major problems:

[0044] 1. The projection patterns used in the testing lack standardized design. The spatial frequency, fringe direction and distribution of different patterns vary significantly, resulting in inconsistent testing standards and making it difficult to quantitatively evaluate the imaging performance of the projection lens.

[0045] 2. Existing methods can only perform blur detection on local areas or in a single direction, and cannot cover the entire area of ​​the projection frame (such as the center and four corners) and the imaging characteristics in both meridional and sagittal directions. It is difficult to quickly determine the imaging consistency of the projection lens in different positions and directions, resulting in low assembly and debugging efficiency.

[0046] Therefore, a method is urgently needed to solve at least one of the above problems.

[0047] To solve the above problem, please refer to Figure 1 , Figure 2 , Figure 3 and Figure 4 This application provides a method for testing projection sharpness, which is applied to a projector. This application does not limit the type of projector. In the corresponding embodiment of this application, a DLP projector is used as an example for illustration.

[0048] like Figure 1 As shown, the provided method for testing projection sharpness includes steps S101 to S104. Details are as follows:

[0049] Step S101. Generate a unit pattern containing multiple binary barcodes in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes horizontal and vertical directions.

[0050] Specifically, a basic unit pattern is designed in the pixel coordinate system of the projector. This pattern contains multiple binary barcodes with different spatial frequencies and stripe directions that are horizontal (corresponding to the sagittal direction) and vertical (corresponding to the meridional direction).

[0051] By designing a preset spatial frequency range corresponding to the typical resolution capability of the projector's pixel resolution, for example, selecting spatial frequencies of 2 pixels / lp, 4 pixels / lp, 8 pixels / lp, and 16 pixels / lp (the corresponding actual spatial frequency can be converted by the pixel size, such as when the pixel size is dμm, flp / mm = 1000 / 2dN, where N is pixels / line pair).

[0052] The stripe direction of each binary barcode is fixed as horizontal (stripes extend horizontally, corresponding to sagittal direction detection) or vertical (stripes extend vertically, corresponding to meridional direction detection), ensuring bidirectional imaging characteristics of the projection lens.

[0053] By integrating barcodes with different spatial frequencies and bidirectional orientations into the same unit pattern, such as arranging them into an m×n matrix, the size of each barcode area matches the smallest unit for subsequent copying and splicing.

[0054] Step S102. Copy the unit pattern to cover the entire projection image resolution range of the projector to form a test pattern.

[0055] Specifically, by replicating the unit pattern generated in step S101 across the entire resolution range of the projected image of the projector using a matrix, a standardized test pattern covering the entire frame is formed.

[0056] Resolution matching calculates the number of times the unit pattern is copied based on the projector's physical resolution (such as 912×1140 or 1920×1080) to ensure that the entire pixel coordinate system is filled without overlap or gaps.

[0057] In the copied pattern, barcodes with different spatial frequencies and directions repeat periodically within the projected image, ensuring that any position, such as the center and four corners, contains horizontal / vertical stripes and multiple spatial frequencies, providing a foundation for subsequent full-area consistency detection.

[0058] Step S103. Project the test pattern in the projection to generate stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector.

[0059] Specifically, the test pattern is projected through a projector and optically magnified by the projection lens, generating stripes covering the meridional / sagittal directions and multiple spatial frequencies on the spatial focal plane, with the stripes evenly distributed across all positions on the image.

[0060] Optical magnification and spatial frequency conversion: Utilizing the optical magnification characteristics of the projection lens, the binary barcode in the pixel coordinate system (e.g., 2 pixels / lp) is converted into the stripe frequency in actual space (e.g., 1 lp / mm, 2 lp / mm, etc.). The specific calculation formula is: Spatial frequency (lp / mm) = 1000 / (2 × pixel size (μm) × pixel / line pair); For example, the DLP4500 pixel size is 7.6μm, and 8 pixels / lp corresponds to a spatial frequency of approximately 4 lp / mm.

[0061] Bidirectional fringes are generated by projecting horizontal barcodes to correspond to sagittal fringes (distributed horizontally), and vertical barcodes to correspond to meridional fringes (distributed vertically), ensuring simultaneous detection of the objective lens's imaging characteristics in two orthogonal directions. Since the test pattern is replicated across the entire image frame using unit replication, the projected image contains complete multi-frequency, bidirectional fringes at the center, corners, and other locations, avoiding localized detection blind spots.

[0062] Step S104. Obtain the stripe images at the center and four corners of the projected image, process the obtained stripe images, and obtain the projection clarity test results of the projector.

[0063] Specifically, by using a high-resolution industrial camera to capture stripe images at the center and four corners of the projected image, the image sharpness and consistency are quantitatively evaluated by calculating the stripe contrast.

[0064] By fixing the industrial camera on the focusing plane and aligning it with the center and four corner points (upper left, upper right, lower left, and lower right) of the projected image, it is ensured that the acquisition area contains the complete fringe period. For each location, lateral (sagittal) and longitudinal (meridian) fringe images are acquired separately, covering multiple spatial frequencies (such as fringes from coarse to fine).

[0065] Stripe processing and contrast calculation include: Gray value extraction: Extracting peak (Imax) and trough (Imin) gray values ​​row by row / column within the selected stripe area (e.g., 8-10 cycles).

[0066] Single-cycle contrast ratio: according to the formula Calculate the modulation contrast of a single stripe period.

[0067] Average contrast is calculated by averaging the contrast over multiple periods. (where n is the number of stripe periods), serving as an indicator of sharpness at that position, direction, and spatial frequency.

[0068] Sharpness is judged by comparing the contrast values ​​at different positions, directions, and frequencies. High contrast (e.g., ≥0.50 at the center position) indicates a sharp image, while low contrast indicates a blurry image.

[0069] If the contrast difference between the four corners and the center is less than the preset threshold (e.g., ±0.15), and the contrast of each frequency stripe in the same direction is higher than the empirical value (e.g., ≥0.30), then the consistency of the projection lens imaging is deemed to meet the standard. Otherwise, the position or angle of the lens needs to be adjusted (e.g., adjusting the working distance or projection angle) until the requirements are met.

[0070] In some embodiments, most current structured light 3D reconstruction schemes utilize DLP projectors, and the quality of the projector directly affects the quality of the 3D reconstruction. Since the projector's imaging optical path design includes projection lenses, its image sharpness and consistency are crucial indicators of projector quality. DLP projector sharpness is generally judged by the human eye or with the aid of an industrial camera; however, due to the variety of projected patterns and inconsistent standards, it is difficult to quickly determine the imaging effect of the projection lenses, affecting subsequent assembly and debugging, leading to reduced efficiency. This invention generates binary barcodes with different spatial frequencies in the projector's pixel coordinate system, with sizes of 2 pixels / lp, 4 pixels / lp, 8 pixels / lp, and 16 pixels / lp, and stripe directions of horizontal and vertical. These are then used as units to replicate and cover the entire projected image resolution range of the projector. After being magnified by projection lenses with different optical magnifications, the binary barcodes generate stripes of different spatial frequencies corresponding to the meridional and sagittal directions within the spatial focal plane, distributed at various positions within the projected image. A high-resolution industrial camera is used to acquire stripe images at the center and four corners of the projection frame. The stripe contrast is calculated by an algorithm to determine the sharpness and consistency of the projection lens.

[0071] The new method / algorithm / device / system / structure can quickly determine the image sharpness at any position in the projection area of ​​a DLP projector, check the image sharpness and consistency at the center and four corners of the projected image, and check the image sharpness in the meridional and sagittal directions, which facilitates debugging and verification of assembly effects.

[0072] Projected patterns at different resolutions, such as Figure 2 and Figure 3 As shown, the unit pattern is as follows Figure 4 As shown, for example, a DLP4500 projector has a pixel size of 7.6µm, a physical resolution of 912×1140, and a throw ratio of 1.53. The pattern is burned into the projector, generating stripes with different spatial frequencies in the meridional and sagittal directions on the focal plane. The sagittal stripes have spatial frequencies of approximately 1 lp / mm, 2 lp / mm, 4 lp / mm, and 8 lp / mm, respectively, from thickest to thinnest. A high-resolution industrial camera is used to acquire an image of the center position to determine the projector's focus. The working distance of the projection lens is adjusted, and the spacing between the lens groups is fine-tuned, observing the stripe changes until the image is clearest. Figure 5 As shown. Selecting 4lp / mm fringes in the sagittal direction, statistically analyzing the grayscale values ​​of the peaks and troughs over eight periods and calculating the fringe contrast, as shown... Figure 6 As shown, the stripe contrast is calculated according to the following formula:

[0073] ; ;

[0074] in, It is the peak gray value (i.e. the maximum gray value of the bright area of ​​the stripes) in a single period of the striped image. It is the highest gray value extracted in the region of interest (ROI) of the striped image along the vertical direction of the stripes (for horizontal stripes, scan column by column in the vertical direction, and for vertical stripes, scan row by row in the horizontal direction).

[0075] It is the lowest gray value extracted from the trough gray value (i.e., the minimum gray value of the dark area of ​​the stripe) within a single period of the striped image, along the vertical direction of the stripes within the same ROI.

[0076] It modulates the contrast. It is the summation of the modulation contrast values ​​of n consecutive stripe periods corresponding to the same spatial frequency and the same direction (horizontal / vertical), where i is the identifier of the sequence number.

[0077] The contrast ratio before and after focusing is calculated using the two formulas above, including: ; The projection center contrast is greater than or equal to the empirical value of 0.50 at this spatial frequency, and the focusing effect meets the requirements.

[0078] In some embodiments, a DLP4710 projector with a pixel size of 5.4µm, a physical resolution of 1920×1080, and a throw ratio of 3.35 is used. When the projector's projection angle does not reach the design value, the center area of ​​the projection will be clear, while the four corner areas will be blurry. In this case, a projection pattern at the current resolution can be burned into the projector, and the projection angle can be adjusted according to the changes in the pattern stripes until the optimal result is achieved. Figure 7 As shown. Analyze the fringes at various positions after adjusting the angle, select the thinnest fringe in the sagittal direction, and statistically analyze the grayscale information of 10 periods of fringes, as shown. Figure 8 As shown, record and mark the peak and trough values ​​of the stripes, such as... Figure 9 As shown. The stripe contrast at each position was calculated using the provided stripe contrast calculation formula: Ccenter = 0.48; Cbottom left = 0.15; Ctop left = 0.16; Cbottom right = 0.28; Ctop right = 0.05.

[0079] Analyze the fringes at various positions after adjusting the angle, select the thinnest fringe in the sagittal direction, and statistically analyze the grayscale information of 10 periodic fringes, such as... Figure 10 As shown, record and mark the peak and trough values ​​of the stripes, such as... Figure 11 As shown. The stripe contrast at each position is calculated using the provided stripe contrast calculation formula: ; ; ; ; At this point, the spatial frequency of the stripes is approximately 7 lp / mm, which is close to the spatial cutoff frequency that the projector in Example 2 can project. When the cutoff frequency is close, the contrast of the stripes at all five positions is greater than 0.30, indicating that the projection clarity and imaging consistency meet the requirements, and the angle adjustment is complete.

[0080] In some embodiments, the projection sharpness test result includes the imaging sharpness and imaging consistency information of the projector's projection lens; the process of processing the acquired striped image to obtain the projection sharpness test result of the projector includes: calculating the stripe contrast based on the peak gray value and trough gray value of the striped image; and obtaining the imaging sharpness and imaging consistency information based on the stripe contrast.

[0081] By calculating stripe contrast to quantify imaging sharpness, and by comparing the contrast distribution at different positions and directions to evaluate imaging consistency, subjective detection is transformed into objective quantitative indicators.

[0082] Stripe grayscale value extraction involves dividing the acquired stripe image into ROIs (Regions of Interest) and selecting continuous, complete stripe periods (such as the 8 periods in Example 1 and the 10 periods in Example 2). For horizontal stripes (sagittal direction), the images are scanned column by column along the vertical direction, and the highest grayscale value (peak Imax) and lowest grayscale value (trough Imin) of each column are recorded. For vertical stripes (meridian direction), the images are scanned row by row along the horizontal direction, and the Imax and Imin of each row are recorded.

[0083] Contrast calculation includes: Single-cycle modulation contrast: ( This reflects the difference in the brightness of the stripes; the closer the value is to 1, the clearer the stripes are.

[0084] Average contrast ratio: The noise impact is reduced by multi-cycle averaging, where n is the selected number of cycles (e.g., n=8 or 10).

[0085] Image sharpness is directly reflected by the contrast value of a single location. For example, if the contrast at the center location is ≥0.50 (empirical threshold), it is judged as "sharp", and if it is below 0.30, it is judged as "blurry".

[0086] Imaging consistency is determined by comparing the contrast of the same frequency and direction stripes at the center and four corners. If the difference is ≤ ±0.15 (preset threshold), the consistency is considered good; otherwise, there is aberration or assembly deviation.

[0087] In some embodiments, the imaging sharpness and imaging consistency information includes first imaging sharpness and imaging consistency information and second imaging sharpness and imaging consistency information; obtaining the imaging sharpness and imaging consistency information based on the stripe contrast includes: comparing the contrast of stripes with the same spatial frequency at the center position and the four corner positions of the projected image, and obtaining the first imaging sharpness and imaging consistency information based on the comparison result; comparing the contrast of stripes with different spatial frequencies at the same position with a preset contrast threshold of the corresponding spatial frequency, and obtaining the second imaging sharpness and imaging consistency information based on the comparison result.

[0088] The sharpness and consistency tests are divided into two categories: the first category (positional consistency): the imaging uniformity at different positions within the frame is evaluated by the contrast difference between the center and the four corners; the second category (frequency adaptability): the ability of the objective lens to resolve different details is evaluated by whether the contrast of different frequency stripes at the same position meets the standard.

[0089] First imaging information (positional consistency): Comparison objects: Extract the contrast of stripes at the same spatial frequency (e.g., 4 lp / mm sagittal direction) at five positions: center, upper left, upper right, lower left, and lower right; Comparison method: Calculate the difference between the contrast at the four corners and the contrast at the center (e.g., |C lower left) C (Center) If all differences are less than the preset consistency threshold (e.g., 0.20), and the contrast of all four corners is greater than or equal to the minimum acceptable value (e.g., 0.30), then the positional consistency is deemed satisfactory. If, after adjusting the projection angle, the contrast of the four corners increases from 0.05-0.28 to 0.32-0.38, close to the center value of 0.44, and the difference is less than 0.12, then the consistency is deemed acceptable.

[0090] Second Imaging Information (Frequency Adaptability): Preset Threshold Setting: Based on the projector's theoretical resolution (e.g., a pixel size of 5.4μm corresponds to a cutoff frequency of approximately 7lp / mm), thresholds are set for different spatial frequencies (e.g., a threshold of 0.60 for low-frequency 1lp / mm and a threshold of 0.30 for high-frequency 7lp / mm); Comparison Method: For different frequency stripes (e.g., 1lp / mm, 2lp / mm, 4lp / mm, 7lp / mm) at the same location (e.g., the center), check whether their contrast is ≥ the corresponding threshold. If all meet the standard, it indicates that the objective lens has a balanced ability to reproduce details at various frequencies, and the overall image clarity meets the standard; if the contrast of high-frequency stripes is insufficient (e.g., 8lp / mm < 0.30), it indicates that the objective lens has insufficient high-frequency resolution, and the objective lens focal length or lens material needs to be optimized.

[0091] In some embodiments, the step of copying the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern includes: arranging the binary barcode into basic units according to the horizontal and vertical stripe directions, and copying and filling the basic units in rows and columns within the projection image resolution range so that stripes of different spatial frequencies and directions are evenly distributed throughout the entire test pattern.

[0092] By replicating the rows and columns of standardized basic units, it is ensured that stripes of different spatial frequencies and directions in the test pattern uniformly cover the entire frame, avoiding blind spots in local detection.

[0093] The basic unit design includes: Unit structure: The horizontal (sagittal) and vertical (meridian) stripes are arranged in a matrix, such as a 2×4 grid, with one column for the horizontal and one column for the vertical. Each column contains four spatial frequencies (2 / 4 / 8 / 16 pixels / lp) of the barcode to form the smallest repeating unit (e.g., a×b pixels).

[0094] Directional differentiation: Horizontal barcode stripes are arranged in the horizontal direction (row direction), and vertical barcode stripes are arranged in the vertical direction (column direction), ensuring that the horizontal / vertical stripes are orthogonally distributed in the image after copying.

[0095] Full-frame fill: Copy count calculation: Based on the projector resolution (e.g., 1920×1080) and unit size (e.g., 200×200 pixels), calculate the horizontal copy count m=1920 / a and the vertical copy count n=1080 / b to ensure that the units do not overlap.

[0096] Edge processing includes: if the resolution is not an integer multiple of the unit size, white space can be added to the edge or the last unit can be repeated to ensure that the edge area still contains the complete stripe period (such as the 1920×1080 resolution of DLP4710 in Example 2, the unit size is set to 480×270, and it is copied horizontally 4 times and vertically 4 times to completely cover).

[0097] After generating the pattern, the uniformity verification checks whether any position (such as the center or four corners) contains four spatial frequencies and horizontal / vertical stripes to ensure there are no "frequency blind spots" or "directional missing areas".

[0098] In some embodiments, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and having the stripes distributed at various positions within the projection frame of the projector, includes: optically magnifying the test pattern through a projection lens, so that the horizontal stripes in the test pattern correspond to the sagittal direction stripes, and the vertical stripes correspond to the meridional direction stripes, and the magnified stripes are evenly distributed at different spatial frequencies in the center and four corner areas of the projection frame.

[0099] By using optical magnification through a projection lens, the digital stripes in the pixel coordinate system are converted into physical stripes in the spatial domain, realizing the mapping between the meridional / sagittal direction and the horizontal / vertical stripes, ensuring uniform frequency distribution across the entire frame.

[0100] Optical magnification and orientation mapping include: horizontal stripes (sagittal direction): horizontal stripes in the pixel coordinate system (stripes extend along the line), after passing through the projection lens, appear in space as horizontal stripes perpendicular to the optical axis section, corresponding to the resolution detection of the objective lens in the sagittal direction (tangential direction);

[0101] Vertical stripes (meridian direction): Vertical stripes in the pixel coordinate system (stripes extend along the column), which are projected as spatial vertical stripes, corresponding to the resolution detection in the meridional direction (within the optical axis section) of the object.

[0102] Spatial frequency conversion includes the following formula: conversion between pixel domain spatial frequency (pixels / lp) and actual spatial frequency (lp / mm): flp / mm = 1000 / (2×d×N), where d is the pixel size (μm) and N is the pixel / line pair (e.g., N=8 corresponds to 8 pixels / lp). For example, for a DLP4500 pixel size of 7.6μm, when N=8, f=1000 / (2×7.6×8)≈8.23lp / mm (the difference from 4lp / mm in Example 1 is due to the projection ratio amplification and needs to be corrected in conjunction with the projection ratio: actual spatial frequency = pixel domain frequency / projection ratio).

[0103] Since the test pattern is replicated to cover the entire screen by unit, the stripes at each position after projection contain four spatial frequencies and two directions. For example, there are 1 lp / mm horizontal stripes in the central area and 1 lp / mm horizontal stripes in the four corner areas, ensuring that different positions receive stripe projections of the same frequency, which facilitates consistent comparison.

[0104] In some embodiments, acquiring the stripe images at the center and four corners of the projected image includes: acquiring images of the stripes at the geometric center and multiple corners of the projected image using a high-resolution industrial camera to ensure that the acquired images cover key areas of the projected image; wherein the corners include the upper left corner, upper right corner, lower left corner, and lower right corner.

[0105] By using an industrial camera to capture images of key locations (center + four corners) of the projection frame, it is ensured that the edge areas where aberrations are prone to occur in the objective lens imaging are covered (the four corners are prone to blurring due to astigmatism and distortion, while the center reflects the focusing reference).

[0106] Camera parameter configuration involves selecting an industrial camera with a resolution ≥ twice that of the projector (e.g., 5 megapixels or higher) to ensure that stripe details are distinguishable; the camera optical axis is perpendicular to the projection optical axis, and the sensor plane and the focusing plane are strictly coplanar, with the position calibrated using a laser rangefinder or mechanical tooling.

[0107] Key location positioning includes: Center position: Calculate the geometric center coordinates of the projected image (W / 2, H / 2, where W / H is the resolution width and height), and collect the ROI centered on this point (e.g., a 100×100 pixel area); Four corner positions: Top left corner (0,0), top right corner (W,0), bottom left corner (0,H), bottom right corner (W,H), and collect a 100×100 pixel area with each corner point as the vertex (to avoid edge truncation, it can be offset inward by 5 pixels).

[0108] The image acquisition process includes: after fixing the camera, acquiring images from five positions in sequence: center, upper left, upper right, lower left, and lower right. At each position, horizontal / vertical stripe images are acquired simultaneously (by switching patterns or acquiring by separate channels). For motion platform projectors, the projection position must be locked before acquisition to avoid displacement errors.

[0109] In some embodiments, the method further includes: if it is necessary to adjust the focusing effect of the projector's projection lens, by adjusting the working distance and lens group spacing of the projection lens, acquiring the stripe image at the center position in real time during the adjustment process of the projection lens and calculating the contrast of the corresponding spatial frequency stripe until the contrast of the stripe at the center position reaches the preset focusing contrast threshold, thereby completing the focusing adjustment.

[0110] To address the issue of inaccurate focusing of the projection lens, the working distance of the lens and the spacing between the lens groups are dynamically adjusted by real-time monitoring of the high spatial frequency stripe contrast at the center position until the clarity meets the standard.

[0111] The debugging objects and targets include: Adjustment parameters: distance between the projection lens and the DMD chip (working distance), and the spacing between the lens groups inside the lens (fine-tuning the focal length); Target indicators: contrast of the high spatial frequency stripes at the center position (such as 4lp / mm or 80% of the design cutoff frequency) ≥ preset focus threshold (such as 0.50).

[0112] The debugging process includes the following steps: Initial state: Place the objective lens at the theoretical working distance (calculated based on the projection ratio), project the test pattern, and acquire the image at the center position; Coarse adjustment stage: Move the objective lens back and forth along the optical axis (in 0.5 mm increments), acquire the center image after each movement, calculate the 4 lp / mm fringe contrast, and record the position corresponding to the peak contrast; Fine adjustment stage: Within ±0.2 mm of the peak position, finely adjust the lens group spacing (driven by a stepper motor with a step size of 0.01 mm), monitor the contrast in real time, until the contrast is ≥0.50 and the fluctuation is <5%; Locking state: After debugging is completed, fix the objective lens position with screws to prevent vibration and displacement.

[0113] The preset focus threshold is set according to the theoretical resolution of the projector. For example, the contrast threshold corresponding to the highest resolvable frequency is set to 0.30, and the threshold for commonly used operating frequencies (such as 70% of the highest frequency) is set to 0.50 (such as 0.50 corresponding to 4lp / mm in Example 1).

[0114] In some embodiments, the method further includes: if it is necessary to adjust the projection angle of the projector, by acquiring stripe images at the center and four corners of the projected image and calculating the contrast of the corresponding spatial frequency stripes, adjusting the projection angle according to the contrast difference between the center and the four corners until the contrast difference of the stripes at each position is less than a preset consistency threshold, thus completing the projection angle adjustment.

[0115] To address the issue of blurred corners caused by projection angle deviation, the projection angle is adjusted to balance the contrast at each position by comparing the contrast of the same frequency stripes at the center and the four corners, thereby eliminating aberrations (such as coma and field curvature).

[0116] If the initial acquisition reveals that the contrast at the four corners is significantly lower than that at the center (e.g., difference > 0.20), and the contrast is particularly low in a certain direction (e.g., upper right / lower left), it suggests that the projection angle is tilted (e.g., rotated around the X-axis or Y-axis).

[0117] Adjust the projector's pitch and yaw angles using a three-dimensional adjustment bracket (accuracy ±0.1°); after each adjustment, collect the contrast of the highest spatial frequency fringes (e.g., 7 lp / mm close to the cutoff frequency) at five locations, and calculate the average difference between the four corners and the center: ΔC = (|C upper left) C center | + | C upper right C center | + | C lower left C center | + | C bottom right C_center|) / 4; When ΔC < preset consistency threshold (e.g., 0.15) and the contrast of all positions ≥ 0.30, the angle is deemed to meet the standard (e.g., the difference after adjustment in Example 2 is < 0.12).

[0118] If the contrast in a certain corner is still too low after adjustment, the tilt angle in the corresponding direction can be fine-tuned (e.g., if the upper right is low, reduce the right tilt angle), and this can be iterated multiple times until the entire area is balanced.

[0119] In some embodiments, aberration types (such as spherical aberration, coma, and field curvature) in striped images are automatically identified using convolutional neural networks (CNNs), and targeted adjustment strategies are output to replace traditional human experience-based judgment.

[0120] The dataset was constructed by collecting stripe images with different aberrations (simulated images generated by the optical design software Zemax + actual projector calibration data), labeling the aberration type (spherical aberration / coma / field curvature / distortion / no aberration) and severity (level 1-5); the images were preprocessed: grayscale normalization, ROI location (center / corner region), and frequency channel separation (splitting different spatial frequency stripes into independent channels).

[0121] Model training utilizes a lightweight CNN model (such as MobileNetV3) with a 512×512 pixel stripe image as input (including horizontal and vertical stripe dual channels) and outputs 5 aberration classification results and parameter adjustment suggestions (such as "Field curvature: It is recommended to adjust the Z-axis tilt angle of the lens group by ±0.3°"). Transfer learning is employed, and based on the ImageNet pre-trained model, the last 3 convolutional layers are fine-tuned for stripe features. The loss function is cross-entropy + regression mean squared error (MSE) of the adjustment parameters.

[0122] After the industrial camera acquires real-time stripe images, the model automatically determines the aberration type: if "spherical aberration" is detected, the system automatically triggers the objective lens focal length fine-tuning algorithm (prioritizing the adjustment of the lens group spacing); if "coma" is detected, it prompts the adjustment of the projection angle (calling the angle debugging module provided in the above embodiment and automatically setting the initial adjustment step size); after debugging, the classification results are verified in real time, forming a closed loop of "detection-classification-debugging-verification" until the aberration level drops below level 1.

[0123] In some embodiments, to address the time-consuming issue of repeated calibration for multiple projector models (with different resolutions and objective parameters), transfer learning is used to reuse historical debugging data to achieve rapid initialization calibration for new models.

[0124] Metadata construction involves establishing a historical debugging database containing a triplet of "objective parameters - stripe contrast - debugging steps" for multiple projector models (e.g., for model A with a resolution of 1920×1080, recording 2000+ debugging data points). Feature engineering is performed on the data: extracting meta-features such as resolution, pixel size, objective lens focal length, and throw ratio, and associating them with stripe contrast data (center / corners) and adjustment parameters (working distance adjustment Δd, angle adjustment Δθ).

[0125] The transfer learning model is designed using a Domain-Adversarial Neural Network (DANN) architecture. The source domain is old model data, and the target domain is a small amount of initial data of the new model. A shared feature extraction layer (such as ResNet18 to extract stripe contrast features) is used. The domain classifier distinguishes whether the data comes from the source domain or the target domain, and the regressor predicts the tuning parameters Δd and Δθ of the new model. During training, the domain classification loss (to promote feature transfer) and the regression loss (to improve prediction accuracy) are minimized.

[0126] When debugging the new model for the first time, only 50 stripe images need to be collected as target domain data; the model is based on the source domain (old model) knowledge to quickly predict the initial adjustment parameters (such as Δd prediction error < 0.3mm, Δθ < 0.2°); combined with the real-time contrast feedback provided by the above embodiment, calibration can be completed quickly (traditional methods require more than 10 minutes), thus improving debugging efficiency.

[0127] In some embodiments, anomaly detection algorithms such as Isolation Forest are used to identify stripe contrast anomalies that exceed the normal adjustment range, predicting objective lens hardware failures (such as lens wear or loose lens groups) in advance, thus avoiding the failure of traditional detection methods to detect hardware problems.

[0128] Normal state feature modeling is achieved by collecting "center / corner contrast-spatial frequency" data from multiple qualified projectors to construct a normal state feature space (contrast distribution range for each frequency / direction, such as the normal range of 4lp / mm horizontal stripe contrast [0.45, 0.65]); for each detection location (5 locations × 4 frequencies × 2 directions = 40-dimensional features), the anomaly score of the isolated forest is calculated, and a threshold is set (e.g., a score > 0.8 is considered abnormal).

[0129] The real-time fault detection process includes: During the debugging process, if a device exhibits the following characteristics: Abnormal features: In three consecutive tests, the contrast of the same frequency / direction exceeds the normal range by ±30% (e.g., the contrast of 4lp / mm longitudinal stripes is consistently <0.35, while the normal lower limit is 0.45); Adjustment failure: The focusing algorithm of Example 6 fails to meet the standard after 10 iterations, and the contrast fluctuation is irregular; The system triggers hardware fault prediction, automatically marks the device, and suggests disassembly and inspection (according to actual testing, it can detect contrast attenuation caused by slight lens wear 24 hours in advance).

[0130] Traditional methods only determine whether the standard is met, and cannot distinguish between "inadequate adjustment" and "hardware defect"; anomaly detection combines multi-dimensional features such as contrast fluctuation mode and adjustment parameter response to improve the hardware fault identification rate.

[0131] This application utilizes a pre-defined binary barcode pattern design with preset sizes (2 pixels / lp, 4 pixels / lp, 8 pixels / lp, 16 pixels / lp) and bidirectional (horizontal and vertical) orientations to create standardized test patterns. This avoids the inconsistency in testing standards caused by pattern differences in existing technologies, enabling quantitative analysis of image sharpness. By acquiring stripe images from the center and four corners of the projection frame and combining them with contrast calculations of stripes at different spatial frequencies, the imaging sharpness of the projection lens in both meridional and sagittal directions, as well as the imaging consistency across the entire frame, can be simultaneously detected, solving the problem of partial detection in existing technologies. Based on the quantified contrast results, the focus adjustment (such as working distance and lens group spacing) and projection angle adjustment of the projection lens can be quickly guided, significantly improving assembly and debugging efficiency and avoiding the subjectivity and inefficiency of human observation.

[0132] Please see Figure 12 As shown, Figure 12 This is a schematic diagram of the projection sharpness testing device 200 provided in this application embodiment. The projection sharpness testing device 200 is used to perform the steps of the projection sharpness testing methods shown in the above embodiments. The projection sharpness testing device 200 can be a single server or a server cluster, or it can be a terminal, such as a handheld terminal, a laptop computer, a wearable device, or a robot.

[0133] like Figure 12 As shown, the projection sharpness testing device 200 includes:

[0134] The pattern acquisition unit 201 is used to generate a unit pattern containing multiple binary barcodes in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes horizontal and vertical directions.

[0135] The pattern forming unit 202 is used to copy the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern.

[0136] The pattern projection unit 203 is used to project the test pattern in the projection and generate stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector.

[0137] The result acquisition unit 204 is used to acquire stripe images at the center and four corner positions corresponding to the projected image, process the acquired stripe images, and obtain the projection clarity test results of the projector.

[0138] In some embodiments, the projection sharpness test result includes the imaging sharpness and imaging consistency information of the projector's projection lens; the process of processing the acquired striped image to obtain the projection sharpness test result of the projector includes: calculating the stripe contrast based on the peak gray value and trough gray value of the striped image; and obtaining the imaging sharpness and imaging consistency information based on the stripe contrast.

[0139] In some embodiments, the imaging sharpness and imaging consistency information includes first imaging sharpness and imaging consistency information and second imaging sharpness and imaging consistency information; obtaining the imaging sharpness and imaging consistency information based on the stripe contrast includes: comparing the contrast of stripes with the same spatial frequency at the center position and the four corner positions of the projected image, and obtaining the first imaging sharpness and imaging consistency information based on the comparison result; comparing the contrast of stripes with different spatial frequencies at the same position with a preset contrast threshold of the corresponding spatial frequency, and obtaining the second imaging sharpness and imaging consistency information based on the comparison result.

[0140] In some embodiments, the step of copying the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern includes: arranging the binary barcode into basic units according to the horizontal and vertical stripe directions, and copying and filling the basic units in rows and columns within the projection image resolution range so that stripes of different spatial frequencies and directions are evenly distributed throughout the entire test pattern.

[0141] In some embodiments, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and having the stripes distributed at various positions within the projection frame of the projector, includes: optically magnifying the test pattern through a projection lens, so that the horizontal stripes in the test pattern correspond to the sagittal direction stripes, and the vertical stripes correspond to the meridional direction stripes, and the magnified stripes are evenly distributed at different spatial frequencies in the center and four corner areas of the projection frame.

[0142] In some embodiments, acquiring the stripe images at the center and four corners of the projected image includes: acquiring images of the stripes at the geometric center and multiple corners of the projected image using a high-resolution industrial camera to ensure that the acquired images cover key areas of the projected image; wherein the corners include the upper left corner, upper right corner, lower left corner, and lower right corner.

[0143] In some embodiments, the method further includes: if it is necessary to adjust the focusing effect of the projector's projection lens, by adjusting the working distance and lens group spacing of the projection lens, acquiring the stripe image at the center position in real time during the adjustment process of the projection lens and calculating the contrast of the corresponding spatial frequency stripe until the contrast of the stripe at the center position reaches the preset focusing contrast threshold, thereby completing the focusing adjustment.

[0144] In some embodiments, the method further includes: if it is necessary to adjust the projection angle of the projector, by acquiring stripe images at the center and four corners of the projected image and calculating the contrast of the corresponding spatial frequency stripes, adjusting the projection angle according to the contrast difference between the center and the four corners until the contrast difference of the stripes at each position is less than a preset consistency threshold, thus completing the projection angle adjustment.

[0145] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the above-described projection sharpness testing device and its modules can be referred to the corresponding content in the various embodiments of the above-described projection sharpness testing method, and will not be repeated here.

[0146] The above-described method for testing projection sharpness can be implemented as a computer program, which can perform tasks such as... Figure 12 It runs on the device shown.

[0147] Please see Figure 13 , Figure 13 This is a schematic block diagram of the projector provided in an embodiment of this application. The projector includes a processor, a memory, and a network interface connected via a device bus, wherein the memory may include a storage medium and internal memory.

[0148] The storage medium may store operating devices and computer programs. The computer program includes program instructions that, when executed, cause the processor to perform any method for testing projected image sharpness.

[0149] The processor provides computing and control capabilities to support the operation of the entire projector.

[0150] Internal memory provides an environment for the execution of computer programs on non-volatile storage media. When executed by a processor, the computer program enables the processor to perform any projection sharpness test method.

[0151] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 13The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the terminal to which the present application is applied. A specific projector may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0152] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0153] In one embodiment, the processor is configured to run a computer program stored in memory to perform the following steps:

[0154] A unit pattern containing multiple binary barcodes is generated in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes horizontal and vertical directions;

[0155] The unit pattern is copied and spread across the entire projection image resolution range of the projector to form a test pattern;

[0156] The test pattern is projected in the projection, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector.

[0157] Obtain the stripe images at the center and four corners of the projected image, process the obtained stripe images, and obtain the projection clarity test results of the projector.

[0158] In some embodiments, the projection sharpness test result includes the imaging sharpness and imaging consistency information of the projector's projection lens; the process of processing the acquired striped image to obtain the projection sharpness test result of the projector includes: calculating the stripe contrast based on the peak gray value and trough gray value of the striped image; and obtaining the imaging sharpness and imaging consistency information based on the stripe contrast.

[0159] In some embodiments, the imaging sharpness and imaging consistency information includes first imaging sharpness and imaging consistency information and second imaging sharpness and imaging consistency information; obtaining the imaging sharpness and imaging consistency information based on the stripe contrast includes: comparing the contrast of stripes with the same spatial frequency at the center position and the four corner positions of the projected image, and obtaining the first imaging sharpness and imaging consistency information based on the comparison result; comparing the contrast of stripes with different spatial frequencies at the same position with a preset contrast threshold of the corresponding spatial frequency, and obtaining the second imaging sharpness and imaging consistency information based on the comparison result.

[0160] In some embodiments, the step of copying the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern includes: arranging the binary barcode into basic units according to the horizontal and vertical stripe directions, and copying and filling the basic units in rows and columns within the projection image resolution range so that stripes of different spatial frequencies and directions are evenly distributed throughout the entire test pattern.

[0161] In some embodiments, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and having the stripes distributed at various positions within the projection frame of the projector, includes: optically magnifying the test pattern through a projection lens, so that the horizontal stripes in the test pattern correspond to the sagittal direction stripes, and the vertical stripes correspond to the meridional direction stripes, and the magnified stripes are evenly distributed at different spatial frequencies in the center and four corner areas of the projection frame.

[0162] In some embodiments, acquiring the stripe images at the center and four corners of the projected image includes: acquiring images of the stripes at the geometric center and multiple corners of the projected image using a high-resolution industrial camera to ensure that the acquired images cover key areas of the projected image; wherein the corners include the upper left corner, upper right corner, lower left corner, and lower right corner.

[0163] In some embodiments, the method further includes: if it is necessary to adjust the focusing effect of the projector's projection lens, by adjusting the working distance and lens group spacing of the projection lens, acquiring the stripe image at the center position in real time during the adjustment process of the projection lens and calculating the contrast of the corresponding spatial frequency stripe until the contrast of the stripe at the center position reaches the preset focusing contrast threshold, thereby completing the focusing adjustment.

[0164] In some embodiments, the method further includes: if it is necessary to adjust the projection angle of the projector, by acquiring stripe images at the center and four corners of the projected image and calculating the contrast of the corresponding spatial frequency stripes, adjusting the projection angle according to the contrast difference between the center and the four corners until the contrast difference of the stripes at each position is less than a preset consistency threshold, thus completing the projection angle adjustment.

[0165] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the processor described above can be referred to the corresponding content in the various embodiments of the above projection sharpness test method, and will not be repeated here.

[0166] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the steps of the projection sharpness testing method provided in any embodiment of this application.

[0167] The computer-readable storage medium can be the internal storage unit of the projector described in the foregoing embodiments, such as the projector's hard drive or memory. Alternatively, the computer-readable storage medium can be an external storage device of the projector, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card.

[0168] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for testing image projection sharpness, characterized in that, Applied to a projector, the method includes: A unit pattern containing multiple binary barcodes is generated in the pixel coordinate system of the projector, wherein the spatial frequency of each binary barcode is selected within a preset range and the corresponding stripe direction includes horizontal and vertical directions; The unit pattern is copied and spread across the entire projection image resolution range of the projector to form a test pattern; The test pattern is projected into the projector, generating stripes of different spatial frequencies corresponding to the meridional and sagittal directions in the spatial focal plane, and the stripes are distributed at various positions within the projection area of ​​the projector. The process involves acquiring stripe images at the center and four corners of the projected image, processing the acquired stripe images, and obtaining the projection sharpness test results of the projector. The projection sharpness test results include the imaging sharpness and imaging consistency information of the projector's projection lens. The processing of the acquired stripe images to obtain the projection sharpness test results includes: calculating the stripe contrast based on the peak and trough gray values ​​of the stripe images; and obtaining the imaging sharpness and imaging consistency information based on the stripe contrast.

2. The method according to claim 1, characterized in that, The image sharpness and image consistency information includes first image sharpness and image consistency information and second image sharpness and image consistency information; obtaining the image sharpness and image consistency information based on the stripe contrast includes: The contrast of the stripes with the same spatial frequency at the center and four corners of the projected image is compared, and the first imaging sharpness and imaging consistency information is obtained based on the comparison results. The contrast of stripes at the same position with different spatial frequencies is compared with a preset contrast threshold for the corresponding spatial frequency, and the second imaging sharpness and imaging consistency information is obtained based on the comparison result.

3. The method according to claim 1, characterized in that, The step of replicating the unit pattern to fill the entire projection image resolution range of the projector to form a test pattern includes: The binary barcodes corresponding to the unit pattern are arranged into basic units according to the horizontal and vertical stripe directions. The basic units are then used as units to copy and fill rows and columns within the resolution range of the projected image, so that stripes of different spatial frequencies and directions are evenly distributed throughout the entire test pattern.

4. The method according to claim 1, characterized in that, The generation of fringes with different spatial frequencies corresponding to the meridional and sagittal directions within the spatial focal plane, wherein the fringes are distributed at various positions within the projection area of ​​the projector, includes: The test pattern is optically magnified by a projection lens, so that the horizontal stripes in the test pattern correspond to the stripes in the sagittal direction and the vertical stripes correspond to the stripes in the meridional direction. The magnified stripes are evenly distributed in the center and four corner areas of the projection image with different spatial frequencies.

5. The method according to claim 1, characterized in that, The step of obtaining the stripe images at the center and four corners of the projected image includes: High-resolution industrial cameras are used to capture images of the stripes at the geometric center and multiple corner points of the projected image to ensure that the captured images cover the key areas of the projected image. The corner positions include the top left corner, the top right corner, the bottom left corner, and the bottom right corner.

6. The method according to claim 1, characterized in that, The method further includes: If you need to adjust the focusing effect of the projector's projection lens, you can adjust the working distance and lens spacing of the projection lens. During the adjustment process, you can acquire the fringe image at the center position in real time and calculate the contrast of the corresponding spatial frequency fringe until the contrast of the fringe at the center position reaches the preset focusing contrast threshold, thus completing the focusing adjustment.

7. The method according to claim 1, characterized in that, The method further includes: If the projection angle of the projector needs to be adjusted, the stripe images at the center and four corners of the projected image are obtained and the contrast of the corresponding spatial frequency stripes is calculated. The projection angle is adjusted according to the contrast difference between the center and the four corners until the contrast difference of the stripes at each position is less than the preset consistency threshold, thus completing the projection angle adjustment.

8. A projector, characterized in that, The projector includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and, in executing the computer program, implement the method as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to implement the method as described in any one of claims 1 to 7.

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