AR glasses waveguide ghosting dynamic correction method based on brightness optimization

Abstract

The invention relates to an AR glasses waveguide ghosting dynamic correction method based on brightness optimization, and the method comprises the following steps: 1, enabling an optical machine to project a detection image to a left lens and a right lens, and enabling cameras disposed on the left lens and the right lens to shoot the detection image; step 2, defining a selected area for the edge position of the detection image, detecting the maximum brightness value and the average brightness value of the selected area, if the maximum brightness value of the selected area is greater than a set threshold value and the number of repeated detection times does not reach the maximum set number of times, executing the next step, otherwise, executing step 8; 3, recording the initial angle positions of the left light machine and the right light machine and the maximum brightness value of the corresponding selected area, recording the initial angle position of the left light machine as txLinitial, and recording the initial angle position of the right light machine as txRinitial. According to the invention, the projection position of the ray machine can be accurately adjusted in an automatic and data-driven manner, so that the ghosting is removed, and misjudgment caused by the ghosting during subsequent ghosting detection is prevented.

Description

Technical Field

[0001] This invention relates to augmented reality (AR) display technology, and more specifically to a dynamic correction method for waveguide ghosting in AR glasses based on brightness optimization. Background Technology

[0002] AR glasses project images into the user's eyes through optical waveguides, achieving a fusion of virtual information and the real world. However, in actual use, due to optical system errors or lens reflections, the displayed image may exhibit a "ghosting" phenomenon, affecting the user experience.

[0003] In fact, the above-mentioned phenomenon of "ghosting" may be a double image or a ghost image. The difference between the two is that a double image is caused by external refraction and can be removed from the visible area by adjustment, while a ghost image is caused by a problem inside the optical engine and cannot be removed by adjustment. It can only trigger an alarm after being detected.

[0004] Since ghosting and image distortion appear similar in a camera, they can both cause a similar "ghosting" phenomenon, easily leading to misjudgment by inspectors and resulting in ineffective corrections, wasting time. Furthermore, adjusting for ghosting relies heavily on manual skill, resulting in low accuracy and efficiency. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic correction method for waveguide ghosting in AR glasses based on brightness optimization. This method can accurately adjust the optical engine projection position in an automated and data-driven manner to remove ghosting and prevent it from causing misjudgment during subsequent ghost detection.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A dynamic correction method for waveguide ghosting in AR glasses based on brightness optimization includes the following steps: Step 1: The optical engine projects the detection image onto the left and right lenses, and the cameras set on the left and right lenses capture the detection image; Step 2: Define the selected area by the edge position of the detected image, and detect the maximum brightness value and average brightness value of the selected area. If the maximum brightness value of the selected area is greater than the set threshold and the number of repeated detections has not reached the maximum set number, proceed to the next step; otherwise, proceed to step 8. Step 3: Record the initial angle positions of the left and right optical engines and the corresponding maximum brightness values ​​of the selected areas. The initial angle position of the left optical engine is recorded as tx_L_initial, and the initial angle position of the right optical engine is recorded as tx_R_initial. Step 4: The left and right optical engines are fine-tuned in multiple steps. After each step of fine-tuning, the camera re-detects the maximum brightness value of the selected area and records the corresponding angle position. Step 5: Find the smallest maximum brightness value among the multiple photos of the selected area taken by the left and right cameras respectively, and record it as the relatively low brightness value. Find the angle position corresponding to the relatively low brightness value. The angle position corresponding to the relatively low brightness value of the left lens is recorded as tx_L_min, and the angle position corresponding to the relatively low brightness value of the right lens is recorded as tx_R_min. Step Six: Calculate the relative offset angle between the left and right lenses at their relatively lower brightness values, where: The relative offset angle of the position where the left lens has a relatively lower brightness value: △L=∣tx_L_min-tx_L_initial∣ The relative offset angle of the position where the brightness of the right lens is relatively low: △R=∣tx_R_min-tx_R_initial∣ Choose the larger value between △L and △R as the offset reference amount △_max; Step 7: Add the offset reference amount △_max to the current initial angle positions of the left and right optical engines to obtain the adjusted initial angle positions of the left and right optical engines; tx_L_initial=tx_L_initial+Δ_max; tx_R_initial=tx_R_initial+Δ_max The left side of the equal sign represents the adjusted initial angle positions of the left and right optical engines, tx_L_initial and tx_R_initial. Then, step one is executed again. Step 8: Detect ghosting.

[0007] Specifically, in step one, the detection image projected by the optomechanical system is a rectangular frame; In step two, the selected area is defined by the edge position of the rectangular frame.

[0008] Specifically, in step four, the left and right optical engines swing three times in sequence, with each swing being 0.5°.

[0009] Specifically, in step eight, the specific steps are as follows: S1. Optical-mechanical switching of the projected detection image, switching to five rectangularly distributed points; S2. Locate unnatural low-contrast areas in the detection image, i.e., light spots; S3. Calculate the size, brightness difference, and position of the light spot; S4. Based on the location of the light spot and the specifications of its field of view, the contrast and area are controlled. If the specifications are exceeded, it is determined that there is a ghosting. S5. If a ghost image is present, trigger an alarm; if no ghost image is present, complete the calibration.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Automation and accuracy: Steps one to seven of this calibration method automatically adjust the optical engine position through data-driven means, replacing the traditional manual experience adjustment, thus improving the accuracy and efficiency of the adjustment.

[0011] (2) Effectively eliminate ghosting: Steps one to seven of this correction method can effectively remove ghosting by finding and correcting the optical-mechanical angle position corresponding to the relatively low brightness value, thus preventing ghosting from causing misjudgment in subsequent ghost detection.

[0012] (3) Improve user experience: After eliminating ghosting, users can have a clearer and more comfortable AR visual experience.

[0013] (4) Wide applicability: This algorithm can be applied to various AR glasses devices that use optical waveguides, and has good versatility. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart of the present invention; Figure 2 This is a flowchart for brightness detection; Figure 3 The flowchart for ghost detection; Figure 4 To adjust the rectangular frame-shaped detection image used in the optomechanical process; Figure 5 The five-point detection image used in the ghost detection process after the optical engine is adjusted; Figure 6 Example image of the selected area; Figure 7 Example image of a detected ghost image; Figure 8 This is an example diagram illustrating the detection of image changes during the adjustment of the optical mechanism. Detailed Implementation

[0016] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0017] A dynamic correction method for waveguide ghosting in AR glasses based on brightness optimization, characterized by the following steps: Step 1: The optical engine projects the detection image onto the left and right lenses. The detection image projected by the optical engine is a rectangular frame (see...). Figure 4 The cameras on the left and right lenses capture the detection images; Step 2: Define the selected area by marking the edges of the rectangular frame (see...) Figure 6 ), detect the maximum brightness value and average brightness value of the selected area. If the maximum brightness value of the selected area is greater than the set threshold and the number of repeated detections has not reached the maximum set number, proceed to the next step; otherwise, proceed to step eight. Step 3: Record the initial angle positions of the left and right optical engines and the corresponding maximum brightness values ​​of the selected areas. The initial angle position of the left optical engine is recorded as tx_L_initial, and the initial angle position of the right optical engine is recorded as tx_R_initial. Step 4: The left and right optical engines swing three steps in sequence, each step swinging 0.5°. After each swing angle, the camera re-detects the maximum brightness value of the selected area and records the corresponding angle position. Step 5: Find the smallest maximum brightness value among the multiple photos of the selected area taken by the left and right cameras respectively, and record it as the relatively low brightness value. Find the angle position corresponding to the relatively low brightness value. The angle position corresponding to the relatively low brightness value of the left lens is recorded as tx_L_min, and the angle position corresponding to the relatively low brightness value of the right lens is recorded as tx_R_min. Step Six: Calculate the relative offset angle between the left and right lenses at their relatively lower brightness values, where: The relative offset angle of the position where the left lens has a relatively lower brightness value: △L=∣tx_L_min-tx_L_initial∣ The relative offset angle of the position where the brightness of the right lens is relatively low: △R=∣tx_R_min-tx_R_initial∣ Choose the larger value between △L and △R as the offset reference amount △_max; Step 7: Add the offset reference amount △_max to the current initial angle positions of the left and right optical engines to obtain the adjusted initial angle positions of the left and right optical engines; tx_L_initial=tx_L_initial+Δ_max; tx_R_initial=tx_R_initial+Δ_max The left side of the equal sign represents the adjusted initial angle positions of the left and right optical engines, tx_L_initial and tx_R_initial. Then, step one is executed again. Step 8: Detect ghosting. The specific steps are as follows: S1. Optomechanical switching of the projected detection image, switching to five rectangularly distributed points (see...) Figure 5 ); S2. Locate unnatural low-contrast areas in the detection image, i.e., light spots; S3. Calculate the size, brightness difference, and position of the light spot; S4. Based on the location of the light spot and the specifications of its field of view, the contrast and area are controlled. If the specifications are exceeded, it is determined that there is a ghosting. S5. If ghost images exist (e.g.) Figure 7 If no ghosting is detected, the calibration is complete.

[0018] The technical effects of this invention are as follows: (1) Automation and accuracy: Steps one to seven of this calibration method automatically adjust the optical engine position through data-driven means, replacing the traditional manual experience adjustment, thus improving the accuracy and efficiency of the adjustment.

[0019] (2) Effectively eliminate ghosting: Steps one to seven of this correction method can effectively remove ghosting by finding and correcting the optical-mechanical angle position corresponding to the relatively low brightness value, thus preventing ghosting from causing misjudgment in subsequent ghost detection.

[0020] (3) Improve user experience: After eliminating ghosting, users can have a clearer and more comfortable AR visual experience.

[0021] (4) Wide applicability: This algorithm can be applied to various AR glasses devices that use optical waveguides, and has good versatility.

[0022] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A dynamic correction method for waveguide ghosting in AR glasses based on brightness optimization, characterized in that: Includes the following steps: Step 1: The optical engine projects the detection image onto the left and right lenses, and the cameras set on the left and right lenses capture the detection image; Step 2: Define the selected area by the edge position of the detected image, and detect the maximum brightness value and average brightness value of the selected area. If the maximum brightness value of the selected area is greater than the set threshold and the number of repeated detections has not reached the maximum set number, proceed to the next step; otherwise, proceed to step 8. Step 3: Record the initial angle positions of the left and right optical engines and the corresponding maximum brightness values ​​of the selected areas. The initial angle position of the left optical engine is recorded as tx_L_initial, and the initial angle position of the right optical engine is recorded as tx_R_initial. Step 4: The left and right optical engines are fine-tuned in multiple steps. After each step of fine-tuning, the camera re-detects the maximum brightness value of the selected area and records the corresponding angle position. Step 5: Find the smallest maximum brightness value among the multiple photos of the selected area taken by the left and right cameras respectively, and record it as the relatively low brightness value. Find the angle position corresponding to the relatively low brightness value. The angle position corresponding to the relatively low brightness value of the left lens is recorded as tx_L_min, and the angle position corresponding to the relatively low brightness value of the right lens is recorded as tx_R_min. Step Six: Calculate the relative offset angle between the left and right lenses at their relatively lower brightness values, where: The relative offset angle of the position where the left lens has a relatively lower brightness value: △L=∣tx_L_min-tx_L_initial∣ The relative offset angle of the position where the brightness of the right lens is relatively low: △R=∣tx_R_min-tx_R_initial∣ Choose the larger value between △L and △R as the offset reference amount △_max; Step 7: Add the offset reference amount △_max to the current initial angle positions of the left and right optical engines to obtain the adjusted initial angle positions of the left and right optical engines; tx_L_initial=tx_L_initial+Δ_max; tx_R_initial=tx_R_initial+Δ_max The left side of the equal sign represents the adjusted initial angle positions of the left and right optical engines, tx_L_initial and tx_R_initial. Then, step one is executed again. Step 8: Detect ghosting.

2. The method for dynamic correction of waveguide ghosting in AR glasses based on brightness optimization according to claim 1, characterized in that: In step one, the detection image projected by the optomechanical system is a rectangular frame; In step two, the selected area is defined by the edge position of the rectangular frame.

3. The method for dynamic correction of waveguide ghosting in AR glasses based on brightness optimization according to claim 1, characterized in that: In step four, the left and right optical engines swing three times in sequence, with each swing being 0.5°.

4. The method for dynamic correction of waveguide ghosting in AR glasses based on brightness optimization according to claim 1, characterized in that: In step eight, the specific steps are as follows: S1. Optical-mechanical switching of the projected detection image, switching to five rectangularly distributed points; S2. Locate unnatural low-contrast areas in the detection image, i.e., light spots; S3. Calculate the size, brightness difference, and position of the light spot; S4. Based on the location of the light spot and the specifications of its field of view, the contrast and area are controlled. If the specifications are exceeded, it is determined that there is a ghosting. S5. If a ghost image is present, trigger an alarm; if no ghost image is present, complete the calibration.

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