Brightness automatic adjusting method for projector, projector and storage medium

Abstract

The application discloses a brightness automatic adjusting method for a projector, the projector and a storage medium. The brightness automatic adjusting method comprises the following steps: acquiring a shooting image containing a projection picture; obtaining brightness data for representing a current projection environment according to the brightness values of the middle region and the surrounding region of the shooting image, wherein the brightness data comprises a projection representative brightness and an environment representative brightness; comparing the brightness data with a plurality of sets of calibration brightness data in a calibration model to determine at least one set of calibration brightness data similar to the brightness data, wherein the calibration brightness data comprises a calibration projection representative brightness and a calibration environment representative brightness; determining the brightness level of the current projection environment according to the corresponding brightness level of the calibration model of the at least one set of calibration brightness data similar to the brightness data; and adjusting the picture brightness of the projector according to the brightness level of the current projection environment. The application can match the brightness of the projection picture with the environment brightness without increasing the cost of the projector.

Description

Technical Field

[0001] This invention relates to the field of projector technology, and more particularly to an automatic brightness adjustment method for a projector, a projector, and a storage medium. Background Technology

[0002] Currently, high-end projectors typically have a dedicated brightness sensor that identifies ambient light to automatically adjust the brightness of the projected image, increasing the projector's cost. However, due to cost constraints, some projectors lack a dedicated ambient light sensor, making it impossible to match the projected image brightness with the ambient light, resulting in a poor user experience.

[0003] The above background information is provided only to aid in understanding the concept and technical solution of this invention. It does not necessarily belong to the prior art of this patent application. In the absence of clear evidence that the above information was disclosed on the filing date of this patent application, the above background information should not be used to evaluate the novelty and inventiveness of this application. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes an automatic brightness adjustment method for projectors, a projector, and a storage medium. This method enables the brightness of the projected image to match the ambient brightness without increasing the projector's cost, thereby improving the user experience.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention discloses an automatic brightness adjustment method for a projector, comprising:

[0007] Acquire a captured image containing the projected image;

[0008] Based on the brightness values ​​of the central and surrounding areas of the captured image, brightness data is obtained to characterize the current projection environment. The brightness data includes the projection-represented brightness and the environment-represented brightness.

[0009] The brightness data is compared with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is close to the brightness data. The calibration brightness data includes the calibration projection representative brightness and the calibration environment representative brightness.

[0010] The brightness level of the current projection environment is determined based on the brightness level corresponding to the calibration model of at least one set of calibration brightness data that are similar to the brightness data.

[0011] Adjust the projector's screen brightness according to the current projection environment's brightness level.

[0012] Preferably, the step of obtaining brightness data representing the current projection environment based on the brightness values ​​of the central region and the surrounding regions of the captured image, wherein the brightness data includes projection-representative brightness and environment-representative brightness, specifically includes: taking the maximum or average value of the brightness values ​​at multiple locations in the central region of the captured image as the projection-representative brightness for representing the current projection environment; and taking the minimum or average value of the brightness values ​​at multiple locations in the surrounding regions of the captured image as the environment-representative brightness for representing the current projection environment.

[0013] Preferably, the projector's processor acquires a captured image containing the projected image, and obtains brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image; or, the camera module acquires a captured image containing the projected image, obtains brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image, and then sends the brightness data to the projector's processor.

[0014] Preferably, the step of comparing the brightness data with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is close to the brightness data specifically includes: calculating the Euclidean distance between the brightness data and each set of calibration brightness data in the calibration model, and taking the K sets of calibration brightness data with the smallest Euclidean distance from the brightness data as the K sets of calibration brightness data that are close to the brightness data, where K is a positive integer.

[0015] Preferably, the Euclidean distance D between the luminance data and the p-th group of calibration luminance data in the calibration model is... p The formula is: D p =[((center-x)-(center-max)] p )) 2 +(around-x)-(around-min) p )) 2 ] 1 / 2 In the formula, center-x represents the projected representative brightness used to characterize the current projection environment, around-x represents the ambient representative brightness used to characterize the current projection environment, and center-max represents the ambient representative brightness. p This indicates that the calibration projection in the p-th group of calibration luminance data in the calibration model represents luminance, around-min. p This indicates the calibration environment representing the luminance in the p-th group of calibration luminance data in the calibration model.

[0016] Preferably, the step of determining at least one set of calibration brightness data that is similar to the brightness data specifically involves: determining multiple sets of calibration brightness data that are similar to the brightness data;

[0017] The step of determining the brightness level of the current projection environment based on the brightness level corresponding to the calibration model of at least one set of calibration brightness data that is similar to the brightness data specifically includes: determining the brightness level with the highest proportion as the brightness level of the current projection environment based on the brightness level corresponding to the calibration model of multiple sets of calibration brightness data that are similar to the brightness data.

[0018] Preferably, the step of acquiring the captured image containing the projected image specifically includes: acquiring multiple frames of captured images containing the projected image in a time sequence;

[0019] The step of obtaining brightness data to characterize the current projection environment based on the brightness values ​​of the middle and surrounding areas of the captured image specifically includes: obtaining multiple sets of brightness data to characterize the current projection environment based on the brightness values ​​of the middle and surrounding areas of multiple frames of the captured image.

[0020] The step of comparing the brightness data with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is similar to the brightness data specifically includes: comparing the multiple sets of brightness data with multiple sets of calibration brightness data in the calibration model respectively, and determining at least one set of calibration brightness data that is similar to each set of brightness data.

[0021] The step of determining the brightness level of the current projection environment based on the brightness level corresponding to the calibration model of at least one set of calibration brightness data that is similar to the brightness data specifically includes: determining the brightness level with the highest proportion as the brightness level of the current projection environment based on the brightness level corresponding to the calibration model of at least one set of calibration brightness data that is similar to each set of brightness data.

[0022] Preferably, the calibration model includes multiple brightness levels and multiple sets of calibration brightness data, wherein the values ​​of each set of calibration brightness data are different, and each brightness level has a mapping relationship with at least one set of calibration brightness data.

[0023] In a second aspect, the present invention discloses a projector, including a processor and a memory, wherein the memory stores a computer program that can be read by the processor to execute in order to implement the automatic brightness adjustment method as described in the first aspect.

[0024] Thirdly, the present invention discloses a storage medium storing a computer program, wherein the computer program is configured to be run by a processor to perform the automatic brightness adjustment method described in the first aspect.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: The automatic brightness adjustment method, projector, and storage medium disclosed in the present invention are based on a captured image containing the projected image, and further identify the brightness values ​​of the central and surrounding areas of the captured image and compare them with a calibration model to obtain the ambient brightness level. The brightness of the projector image is then adjusted according to the ambient brightness level, thereby achieving matching of the brightness of the projected image with the ambient brightness without increasing the cost of the projector, thus improving the user experience. Attached Figure Description

[0026] Figure 1 This is a flowchart of an automatic brightness adjustment method for a projector according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a schematic diagram illustrating the acquisition of brightness data from a captured image in one embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram illustrating the acquisition of brightness data from a captured image in another embodiment of the present invention. Detailed Implementation

[0029] The embodiments of the present invention will be described in detail below. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope and application of the present invention.

[0030] It should be noted that when a component is referred to as "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as "connected to" another component, it can be directly connected to or indirectly connected to that other component. Furthermore, a connection can be used for both fixing and circuit / signal connectivity.

[0031] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0032] like Figure 1 As shown, Embodiment 1 of the present invention discloses an automatic brightness adjustment method for a projector, comprising the following steps:

[0033] S1: Acquire a captured image containing the projected image;

[0034] The images captured in this step can be taken by the projector's own camera module or by a mobile device such as a smartphone. The projected image can be referenced. Figure 3 The P region in the text.

[0035] S2: Based on the brightness values ​​of the central and surrounding areas of the captured image, obtain brightness data to characterize the current projection environment. The brightness data includes the projection-represented brightness and the environment-represented brightness.

[0036] In a specific embodiment, the maximum or average brightness value among multiple locations in the central region of the captured image is used as the representative projection brightness to characterize the current projection environment. By comparing the brightness values ​​at multiple locations in the central region and using the maximum or average value as the representative projection brightness to characterize the current projection environment, even if some locations are outside the projection screen due to changes in projection distance, it can be ensured that other locations in the captured image are within the projection screen. The brightness acquisition locations in the central region can be symmetrically spaced, and the more locations there are, the better to avoid the aforementioned problems. In addition, the center of the central region can coincide with the center of the captured image, and the length and width of the central region are half the length and width of the captured image, or they can be adaptively adjusted according to the FOV of the actual camera and optical engine. The minimum or average brightness value among multiple locations in the surrounding area of ​​the captured image is used as the representative ambient brightness to characterize the current projection environment. The brightness value of any location includes point brightness or average brightness of a small area, and multiple locations are spaced apart, preferably symmetrically arranged in the captured image. The brightness value of a certain location in the captured image can be determined based on the grayscale value of that location.

[0037] In some embodiments, the projector's processor acquires a captured image containing the projected image and obtains brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image. In other embodiments, a camera module acquires a captured image containing the projected image and obtains brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image, and then sends the brightness data to the projector's processor. The camera module can be part of the projector or a mobile terminal. Obtaining brightness data through a camera module and then sending it to the projector reduces the computational burden on the projector's processor.

[0038] S3: Compare the brightness data with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is close to the brightness data. The calibration brightness data includes the representative brightness of the calibration projection and the representative brightness of the calibration environment.

[0039] The calibration model contains multiple brightness levels and multiple sets of calibration brightness data, with each set of calibration brightness data having different values, and each brightness level having a mapping relationship with at least one set of calibration brightness data.

[0040] In a specific embodiment, the Euclidean distance between the luminance data and each group of calibration luminance data in the calibration model is calculated. The K groups of calibration luminance data with the smallest Euclidean distance to the luminance data are taken as the K groups of calibration luminance data that are close to the luminance data, where K is a positive integer; wherein, the Euclidean distance D between the luminance data and the p-th group of calibration luminance data in the calibration model is... p The formula is:

[0041] D p =[((center-x)-(center-max)] p )) 2 +(around-x)-(around-min) p )) 2 ] 1 / 2

[0042] In the formula, center-x represents the projected representative brightness used to characterize the current projection environment, around-x represents the ambient representative brightness used to characterize the current projection environment, and center-max represents the ambient representative brightness. p This indicates that the calibration projection in the p-th group of calibration luminance data in the calibration model represents luminance, around-min. p This indicates the calibration environment representing the luminance in the p-th group of calibration luminance data in the calibration model.

[0043] S4: Determine the brightness level of the current projection environment based on at least one set of calibration brightness data that are similar to the brightness data at the brightness level corresponding to the calibration model;

[0044] In some embodiments, multiple sets of calibrated brightness data that are similar to the brightness data are determined in step S3. In this step, the brightness level with the highest proportion is determined as the brightness level of the current projection environment based on the brightness level of the multiple sets of calibrated brightness data that are similar to the brightness data in the calibration model.

[0045] S5: Adjust the brightness of the projector screen according to the brightness level of the current projection environment.

[0046] Based on the brightness level of the current projection environment obtained in step S4, the brightness of the projected image is adjusted accordingly. When the ambient light is bright, the brightness of the projected image is increased to obtain a better viewing experience; when the ambient light is dim, the brightness of the projected image is reduced to reduce eye strain and save energy.

[0047] In some preferred embodiments, step S1 involves acquiring multiple frames of images containing the projected image in a time sequence; step S2 involves obtaining multiple sets of brightness data to characterize the current projection environment based on the brightness values ​​of the central and surrounding areas of the multiple frames, specifically, the maximum value among multiple positions in the central area of ​​each frame is taken as the corresponding representative projection brightness to characterize the current projection environment; the minimum value among multiple positions in the surrounding area of ​​each frame is taken as the corresponding representative environment brightness to characterize the current projection environment, thus obtaining multiple sets of brightness data to characterize the current projection environment; step S3 involves comparing the multiple sets of brightness data with multiple sets of calibration brightness data in the calibration model, and determining at least one set of calibration brightness data that is similar to each set of brightness data; step S4 involves determining the brightness level with the highest proportion in the calibration model based on the brightness level corresponding to the at least one set of calibration brightness data that is similar to each set of brightness data, and then adjusting the brightness of the projector screen according to the brightness level of the current projection environment; step S5 involves adjusting the brightness of the projector screen according to the brightness level of the current projection environment. In this preferred embodiment, by determining the brightest brightness value in the central area and the darkest brightness value in the surrounding area of ​​each frame of captured images from multiple frames as multiple sets of brightness data to characterize the current projection environment, the accuracy of identifying the ambient brightness level can be further improved and errors reduced. For example, the camera acquires one frame of image every 0.5 seconds, and three frames are acquired consecutively. The ambient brightness level calculated based on these three frames is determined as the final ambient brightness level.

[0048] The calibration model involved in step S3 of the above embodiments can be preset in the projector, and its preset process steps can be performed before the device leaves the factory, specifically including the following steps:

[0049] A1: Acquire images to obtain calibration brightness data that characterizes the current projection environment;

[0050] The field of view (FOV) of the camera is greater than that of the optical engine, meaning that the image captured by the camera includes not only the projected image but also the surrounding environment. The camera can be the camera module of the projector itself or the camera module of a mobile device such as a mobile phone.

[0051] After capturing the image, it is converted into a grayscale image. Each pixel value in the grayscale image represents the brightness value at that location within the captured image. The camera captures the brightness values ​​of n points in the surrounding area and m points in the center area. The brightness values ​​of the n points in the surrounding area are denoted as around1, around2, ..., around1. n The minimum value among them is denoted as around-min, which serves as the "representative brightness" of the surrounding area, i.e., the ambient representative brightness; the brightness values ​​of the m points in the middle area are denoted as center1, center2, ..., center2. m The maximum value is denoted as center-max, which serves as the "representative brightness" of the central region, i.e., the projected representative brightness. The calibration brightness data used to characterize the current projection environment includes both the calibrated projected representative brightness and the calibrated environment representative brightness. In this embodiment, the surrounding area refers to the area outside the corresponding projected image, while the central area is the area corresponding to the projected image.

[0052] like Figure 2 As shown, in one example, the brightness values ​​of n points in the surrounding area represent the four corners of the captured image 100, including around1, around2, around3, and around4. The brightness values ​​of m points in the center area represent nine interval positions in the center area of ​​the captured image 100, including center1, center2, center3, ..., center9. Figure 3 As shown, in another example, the brightness values ​​of n points in the surrounding area include the four corners and the midpoints of the four sides of the captured image 100, namely around1, around2, around3, around4, around5, around6, around7, and around8. The brightness values ​​of m points in the central area are the nine interval positions in the central area of ​​the captured image 100 and the midpoints of the four sides of the central rectangular area, namely center1, center2, center3, ..., center9, center1. 10 center 11 center 12 center 13 However, the location and number of brightness values ​​for multiple points in the surrounding and central areas are not limited to... Figure 2 and Figure 3 The situation is shown.

[0053] By collecting the brightness values ​​of various points in the surrounding area, the ambient brightness outside the projection area can be identified. In this embodiment, the minimum value (around-min) among the n brightness values ​​of the surrounding area is used as the calibrated ambient brightness (representing the ambient brightness value of the surrounding area in the currently captured image), which can further eliminate interference areas with high brightness in the captured image. By using the maximum value (center-max) among the m brightness values ​​of the central area as the calibrated projection brightness (representing the brightness value of the projected image in the currently captured image), interference areas with low brightness in the projected image can be eliminated. Step A2 below uses this value selection method as an example. However, in other embodiments, depending on the accuracy and scene requirements, some examples may also use the average of the n brightness values ​​of the surrounding area to obtain the calibrated ambient brightness representing the current projection environment; and the average of the m brightness values ​​of the central area to obtain the calibrated projection brightness representing the current projection environment.

[0054] A2: Map the calibration brightness data to the ambient brightness level to obtain the calibration model;

[0055] Under different ambient brightness conditions, different ambient brightness levels L1, L2, ..., L were determined. j Each level of ambient brightness corresponds to a range of ambient brightness when the projector is off. With the projector on, the ambient light is adjusted. In this embodiment, the range from no ambient light to the brightest ambient light is divided into the following levels: L1, L2, ..., L... j Then, at each ambient brightness level, turn on the projector and repeat step A1 to capture images at each ambient brightness level, obtaining corresponding calibration brightness data representing the current projection environment. This results in j sets of calibration brightness model data, where each set contains several sets of calibration brightness data (because the projected image changes, the data fluctuates; therefore, in this example, several sets of calibration brightness data are collected under the same ambient light level). Each set of calibration brightness data within the same set of calibration brightness model data (including the calibrated projection representative brightness and the calibrated ambient representative brightness) is measured separately by projecting a slightly varying brightness image within the same ambient brightness level. The calibration brightness data can be measured using a camera.

[0056] The obtained j sets of calibration brightness model data were labeled and saved. Each set was labeled with the corresponding ambient brightness level of the test environment. That is, the projected representative brightness and ambient representative brightness of each set of calibration brightness data in the first set of calibration brightness model data correspond to ambient brightness level L1, the projected representative brightness and ambient representative brightness of each set of calibration brightness data in the second set of calibration brightness model data correspond to ambient brightness level L2, and so on, resulting in the calibration model shown in Table 1. Each set of calibration brightness model data corresponds to one ambient brightness level, and each set of calibration brightness model data includes 3 sets of calibration brightness data (center-max). ab around-min ab ), where center-max ab This refers to the ambient light level L corresponding to the a-th ambient light level. a The calibration projection in group b of the calibration brightness data represents brightness, around min. ab This refers to the ambient light level L corresponding to the a-th ambient light level. a In the b-th group of calibration brightness data, the calibration environment represents the brightness, where a takes the value 1, 2, ..., or j, and b takes the value 1, 2, or 3. That is, in the table below, center-max and around-min with the same subscript are obtained from the same captured image, while center-max and around-min with different subscripts are obtained from different ambient brightness levels and different captured images.

[0057] Table 1. Mapping Relationship Between Calibration Brightness Data and Ambient Brightness Level

[0058]

[0059] It should be noted that the calibration projection brightness and calibration environment brightness in a large set of calibration brightness model data are not limited to the three in Table 1. There can be more data, that is, b can also take the value of 4, 5 or even larger values.

[0060] The following section provides a more detailed explanation of how the KNN algorithm (minimum nearest neighbor algorithm) is used to determine the brightness level of the current projection environment in the automatic brightness adjustment method for projectors according to Embodiment 1 of the present invention, in conjunction with the calibration model described above.

[0061] In step S1, under the current environment, the projector projects an image and takes a picture to obtain a captured image, which includes the projected image. Then, in step S2, based on the captured image obtained in step S1, the brightness values ​​of m points in the central region and n points in the surrounding region are obtained from the captured image. Based on the brightness values ​​of the m points in the central region, a representative projection brightness center-x (i.e., the maximum value of the m points in the central region, center-max) is obtained. Based on the brightness values ​​of the n points in the surrounding region, an environmental representative brightness around-x (i.e., the minimum value of the n points in the surrounding region, around-min) is obtained. The positions of the captured images corresponding to the brightness values ​​of the m points in the central region and the n points in the surrounding region obtained in this step can be the same as the corresponding positions in step A1.

[0062] In step S3, the Euclidean distances are calculated between the brightness data obtained in step S2 and all the calibration brightness data in Table 1, so that each obtained Euclidean distance is mapped to the ambient brightness level in the calibration model, as shown in Table 2.

[0063] Table 2. Mapping Relationship between Euclidean Distance and Ambient Brightness Level between Brightness Data and Calibrated Brightness Data

[0064]

[0065] Among them, the brightness data is related to the a-th ambient brightness level L a The Euclidean distance D between the b group of calibrated luminance data ab The following formula can be used for calculation:

[0066] D ab =[((center-x)-(center-max)] ab )) 2 +(around-x)-(around-min) ab )) 2 ] 1 / 2

[0067] In the formula, center-x represents the projected representative brightness used to characterize the current projection environment, around-x represents the ambient representative brightness used to characterize the current projection environment, and center-max represents the ambient representative brightness. ab This represents the ambient light level L corresponding to the a-th level. a The projection in the b-th group of calibration luminance data represents luminance, around-min ab This represents the ambient light level L corresponding to the a-th level. a The ambient representative brightness in the b group of calibration brightness data.

[0068] In step S3, the K smallest Euclidean distances are selected from all the Euclidean distances calculated in Table 2 (K is generally small, for example, K is 5).

[0069] In step S4, the brightness level with the largest Euclidean distance among the K smallest Euclidean distances is determined as the current ambient light level (similar to a vote, the one with the most votes is the output). Taking Table 2 as an example, assuming K is 5, and assuming the five smallest Euclidean distances are D... 22 D 23 D 31 D 32 D 33 If the ambient brightness level of the current projection is L3, then each ambient brightness level corresponds to a preset projection screen brightness.

[0070] In step S4, after determining the current ambient brightness level, the projector projects the image at the corresponding screen brightness. Several adjacent ambient brightness levels can correspond to a single screen brightness, or they can each correspond to a different screen brightness.

[0071] It should be noted that, besides mapping the ambient brightness level to the luminance level by calculating the Euclidean distance between the luminance data and the calibrated luminance data, other calculation methods can also be used. This simply requires obtaining the calibrated luminance data from the closest calibration model based on the representative projection luminance (center-x) and the representative ambient luminance (around-x) used to characterize the current projection environment. For example, this can be achieved by first determining the center-max among several sets of calibrated luminance data closest to the representative projection luminance (center-x). ab Then, from these sets of calibrated brightness data, determine the around-min value that is closest to the ambient representative brightness around-x. ab This allows us to obtain calibrated brightness data that is close to the actual brightness data, and then further determine the brightness level of the current projection environment; alternatively, we can first determine the around-min value among several sets of calibrated brightness data that are closest to the representative ambient brightness around-x. ab Then, from these sets of calibrated brightness data, the center-max that is closest to the center-x of the projected brightness is determined. ab This is used to obtain calibrated brightness data that is similar to the brightness data, and then to further determine the brightness level of the current projection environment.

[0072] Embodiment 2 of the present invention also discloses a projector, including a processor and a memory. The memory stores a computer program, which can be read and executed by the processor to implement the automatic brightness adjustment method as described in Embodiment 1 above.

[0073] Embodiment 3 of the present invention discloses a storage medium storing a computer program, wherein the computer program is configured to be run by a processor to perform the steps of the automatic brightness adjustment method in Embodiment 1 above.

[0074] Optionally, the aforementioned storage media may include, but are not limited to, USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks, and other media capable of storing computer programs.

[0075] The present invention discloses an automatic brightness adjustment method for a projector, a projector, and a storage medium. The method is based on a captured image containing the projected image, and further identifies and weights the brightness values ​​of the central and surrounding areas of the captured image to obtain the ambient brightness level. The method automatically adjusts the brightness of the projector screen under different ambient light conditions, thereby improving the user experience.

[0076] The background section of this invention may include background information about the problems or circumstances surrounding the invention, rather than a description of prior art by others. Therefore, the content included in the background section is not an admission of prior art by the applicant.

[0077] The above description provides a further detailed explanation of the present invention in conjunction with specific / preferred embodiments, and it should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various substitutions or modifications can be made to these described embodiments without departing from the concept of the present invention, and all such substitutions or modifications should be considered within the scope of protection of the present invention. In the description of this specification, the reference to terms such as "an embodiment," "some embodiments," "preferred embodiment," "example," "specific example," or "some examples," etc., indicates that the specific features, structures, materials, or characteristics described in connection with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Furthermore, those skilled in the art can combine and integrate different embodiments or examples and features of different embodiments or examples described in this specification without contradiction. Although the embodiments of the present invention and their advantages have been described in detail, it should be understood that various changes, substitutions, and modifications can be made herein without departing from the scope defined by the appended claims.

Claims

1. A method for automatically adjusting the brightness of a projector, characterized in that, include: Acquire a captured image containing the projected image; Based on the brightness values ​​of the central and surrounding areas of the captured image, brightness data is obtained to characterize the current projection environment. The brightness data includes the projection-represented brightness and the environment-represented brightness. The brightness data is compared with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is close to the brightness data. The calibration brightness data includes the calibration projection representative brightness and the calibration environment representative brightness. The brightness level of the current projection environment is determined based on the brightness level corresponding to the calibration model of at least one set of calibration brightness data that are similar to the brightness data. Adjust the brightness of the projector screen according to the brightness level of the current projection environment; The step of obtaining brightness data representing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image, wherein the brightness data includes the projection-representative brightness and the environment-representative brightness, specifically includes: The maximum or average value of the brightness values ​​at multiple locations in the central region of the captured image is used as the representative brightness of the projection environment; the minimum or average value of the brightness values ​​at multiple locations in the surrounding region of the captured image is used as the representative brightness of the environment.

2. The automatic brightness adjustment method according to claim 1, characterized in that, The processor of the projector acquires a captured image containing the projected image, and obtains brightness data to characterize the current projection environment based on the brightness values ​​of the central area and the surrounding area of ​​the captured image. Alternatively, the camera module acquires a captured image containing the projected image, and obtains brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image, before sending the brightness data to the processor of the projector.

3. The automatic brightness adjustment method according to claim 1, characterized in that, The step of comparing the brightness data with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is similar to the brightness data specifically includes: Calculate the Euclidean distance between the brightness data and each set of calibration brightness data in the calibration model, and take the K sets of calibration brightness data with the smallest Euclidean distance from the brightness data as the K sets of calibration brightness data that are close to the brightness data, where K is a positive integer.

4. The automatic brightness adjustment method according to claim 3, characterized in that, The brightness data and the first in the calibration model p Euclidean distance D between group calibration brightness data p The formula is: D p =[((center-x)-(center-max p )) 2 +((around-x)-(around-min p )) 2 ] 1 / 2 In the formula, center-x represents the projected representative brightness used to characterize the current projection environment, around-x represents the ambient representative brightness used to characterize the current projection environment, and center-max represents the ambient representative brightness. p Indicating the first in the calibration model p The calibration projection in the group calibration brightness data represents brightness, around-min p Indicating the first in the calibration model p The calibration environment in the group calibration brightness data represents the brightness.

5. The automatic brightness adjustment method according to claim 1, characterized in that, The step of determining at least one set of calibration brightness data that is similar to the brightness data specifically includes: Multiple sets of calibrated brightness data that are similar to the brightness data were identified; The step of determining the brightness level of the current projection environment based on at least one set of calibrated brightness data similar to the brightness data at the brightness level corresponding to the calibration model specifically includes: Based on the brightness levels corresponding to multiple sets of calibrated brightness data that are similar to the brightness data in the calibration model, the brightness level with the highest proportion is determined as the brightness level of the current projection environment.

6. The automatic brightness adjustment method according to claim 1, characterized in that, The step of acquiring the captured image containing the projected image specifically includes: Acquire multiple frames of images containing the projected image in a time sequence; The step of obtaining brightness data characterizing the current projection environment based on the brightness values ​​of the central and surrounding areas of the captured image specifically includes: Based on the brightness values ​​of the central and surrounding areas of the captured images in multiple frames, multiple sets of brightness data are obtained to characterize the current projection environment. The step of comparing the brightness data with multiple sets of calibration brightness data in the calibration model to determine at least one set of calibration brightness data that is similar to the brightness data specifically includes: The multiple sets of brightness data are compared with the multiple sets of calibration brightness data in the calibration model, and at least one set of calibration brightness data that is similar to each set of brightness data is determined. The step of determining the brightness level of the current projection environment based on at least one set of calibrated brightness data similar to the brightness data at the brightness level corresponding to the calibration model specifically includes: Based on the brightness level corresponding to at least one set of similar calibration brightness data corresponding to each set of brightness data in the calibration model, the brightness level with the highest proportion is determined as the brightness level of the current projection environment.

7. The automatic brightness adjustment method according to claim 1, characterized in that, The calibration model includes multiple brightness levels and multiple sets of calibration brightness data, wherein the values ​​of each set of calibration brightness data are different, and each brightness level has a mapping relationship with at least one set of calibration brightness data.

8. A projector, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program that can be read by the processor to execute in order to implement the automatic brightness adjustment method as described in any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to be run by a processor to perform the automatic brightness adjustment method as described in any one of claims 1 to 7.

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