CN108875625B - Identification method and electronic equipment - Google Patents
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Abstract
According to the identification method, the first image collected by the image collection module is analyzed, whether the first image meets the preset condition or not is judged, and when the first image does not meet the preset condition, the parameter value of the image collection module is adjusted, so that the image meeting the preset condition can be collected until the first image meets the preset condition, and when the first image meets the preset condition, the content in the image is analyzed to obtain the operation gesture information, so that the gesture of a user is identified. In the process, the parameter value of the image acquisition module is adjusted in real time by combining the image acquired by the image acquisition module, so that the content in the acquired image can be correctly identified, and the problem that the equipment cannot correctly identify the gesture of the user when the light condition is poor is solved.
Description
Technical Field
The present application relates to the field of electronic devices, and more particularly, to an identification method and an electronic device.
Background
With the development of electronic technology, many devices currently support gesture interaction.
However, in the prior art, the gesture interaction device can be normally used in a room with moderate light, and the gesture interaction of the user cannot be correctly recognized in an environment with poor light conditions (such as weak light or strong, especially strong sunlight irradiation), which results in failure to implement gesture interaction.
Disclosure of Invention
In view of this, the present application provides an identification method, which solves the problem in the prior art that when the light condition is poor, the device cannot correctly identify the gesture of the user.
In order to achieve the above purpose, the present application provides the following technical solutions:
an identification method, the method being applied to an electronic device, the method comprising:
receiving a first image acquired by an image acquisition module;
judging whether the first image meets a preset condition or not;
analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information;
and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
Preferably, in the method, the determining whether the first image meets a preset condition includes:
converting the first image into a gray-scale image;
acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image;
judging whether the average gray value meets a preset threshold condition or not;
determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition;
and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
Preferably, in the method, the adjusting the parameter value of the image capturing module includes:
and adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule.
Preferably, in the above method, before receiving the image collected by the image collecting module, the method further includes:
receiving a second image acquired by the image acquisition module in a preset environment;
identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result;
and calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition.
Preferably, the method further comprises:
and adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition.
An electronic device, comprising:
a body;
the image acquisition module is arranged in the body and is used for acquiring a first image;
the processor is used for receiving a first image acquired by the image acquisition module; judging whether the first image meets a preset condition or not; analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information; and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
Preferably, the electronic device, the processor is configured to,
converting the first image into a gray-scale image;
acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image;
judging whether the average gray value meets a preset threshold condition or not;
determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition;
and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
Preferably, in the electronic device as described above, the processor is specifically configured to,
and adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule.
Preferably, in the electronic device as described above, the processor is specifically configured to,
receiving a second image acquired by the image acquisition module in a preset environment;
identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result;
and calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition.
Preferably, in the electronic device, the processor is further configured to,
and adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition.
As can be seen from the above technical solutions, compared with the prior art, the present application provides an identification method, including: receiving a first image acquired by an image acquisition module; judging whether the first image meets a preset condition or not; analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information; and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition. By adopting the method, the first image collected by the image collection module is analyzed to judge whether the first image meets the preset condition, and when the first image does not meet the preset condition, the parameter value of the image collection module is adjusted to collect the image meeting the preset condition, and when the first image meets the preset condition, the content in the image is analyzed to obtain the operation gesture information, so that the gesture of the user is recognized. In the process, the parameter value of the image acquisition module is adjusted in real time by combining the image acquired by the image acquisition module, so that the content in the acquired image can be correctly identified, and the problem that the equipment cannot correctly identify the gesture of the user when the light condition is poor is solved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of an embodiment 1 of an identification method provided in the present application;
fig. 2 is a flowchart of an identification method according to embodiment 2 of the present application;
fig. 3 is a schematic diagram of an overexposed and adjusted image in embodiment 2 of an identification method provided in the present application;
fig. 4 is a flowchart of an identification method according to embodiment 3 of the present application;
fig. 5 is a flowchart of an identification method embodiment 4 provided in the present application;
fig. 6 is a schematic structural diagram of an embodiment of an electronic device provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
As shown in fig. 1, a flowchart of an embodiment 1 of an identification method provided by the present application is applied to an electronic device having an image capturing function, and the method includes the following steps:
step S101: receiving a first image acquired by an image acquisition module;
the electronic equipment is provided with an image acquisition module, and the image acquisition module acquires images of an image acquisition area of the electronic equipment to obtain a first image.
In specific implementation, a user executes gesture operation in the image acquisition area, and correspondingly, the image acquired by the image acquisition module comprises gesture information of the user.
In a specific implementation, the gesture recognition operation is performed, generally, the gesture recognition operation is performed through Infrared information, the image acquisition module may adopt an IR camera (Infrared camera) to acquire the content in the image acquisition area, and the obtained image is an Infrared image.
Step S102: judging whether the first image meets a preset condition or not;
the electronic equipment is provided with a preset condition, and whether the first image meets the condition or not is judged based on the preset condition.
In a specific implementation, the preset condition may specifically include that the exposure satisfies a condition, that is, the brightness of the image is appropriate, and based on the brightness, the content in the image can be identified.
If the first image meets the condition, the operation gesture information contained in the first image can be identified; otherwise, the operation gesture information contained in the first image cannot be recognized.
In the following embodiments, how to determine whether the first image satisfies the predetermined condition is explained, and details are not described in this embodiment.
Step S103: analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information;
the first image meets preset conditions, correspondingly, the content in the first image can be recognized, correspondingly, the content of the first image is recognized respectively, operation gesture information of a user is obtained, and therefore the electronic equipment can respond to the operation gesture information and complete gesture operation of the user.
Wherein the content in the image can be identified according to an image identification technology.
Step S104: and adjusting the parameter value of the image acquisition module based on the condition that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
When the first image does not meet the preset condition, the acquired image is changed by adjusting the parameter value of the image acquisition module, whether the acquired new first image meets the preset condition is judged again, and when the preset condition is not met, the parameter value of the image acquisition module is adjusted again, and the process is executed in a circulating manner until the acquired new first image meets the preset condition.
In summary, an identification method provided in this embodiment includes: receiving a first image acquired by an image acquisition module; judging whether the first image meets a preset condition or not; analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information; and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition. By adopting the method, the first image collected by the image collection module is analyzed to judge whether the first image meets the preset condition, and when the first image does not meet the preset condition, the parameter value of the image collection module is adjusted to collect the image meeting the preset condition, and when the first image meets the preset condition, the content in the image is analyzed to obtain the operation gesture information, so that the gesture of the user is recognized. In the process, the parameter value of the image acquisition module is adjusted in real time by combining the image acquired by the image acquisition module, so that the content in the acquired image can be correctly identified, and the problem that the equipment cannot correctly identify the gesture of the user when the light condition is poor is solved.
As shown in fig. 2, a flow chart of embodiment 2 of an identification method provided by the present application includes the following steps:
step S201: receiving a first image acquired by an image acquisition module;
step S201 is the same as step S101 in embodiment 1, and details are not described in this embodiment.
Step S202: converting the first image into a gray-scale image;
in a specific implementation, the first image collected by the image collecting module is an infrared image, and a gray value can be used to represent the brightness of the first image.
Firstly, each detail part in the gray-scale image can be processed to meet a preset condition only by converting the whole first image into the gray-scale image.
In specific implementation, an averaging method, a maximum-minimum averaging method and a weighted averaging method can be adopted to calculate the gray value of each pixel point, and the image is converted based on the gray value to obtain a gray-scale image.
Wherein, the averaging method is to average the values of 3 channels RGB (red green blue) at the same pixel position; in the average method, the maximum and minimum average method is to average the maximum and minimum brightness in RGB of the same pixel position; the weighted average method, I (x, y) ═ 0.3 × I _ R (x, y) +0.59 × I _ G (x, y) +0.11 × I _ B (x, y), and several weighting coefficients 0.3,0.59, and 0.11 are parameters adjusted according to the human luminance perception system, and are widely used standardized parameters.
When the first image is an infrared image, the infrared camera captures Y-channel data representing brightness (Luminance/Luma) in a YUV (pixel format in which a Luminance parameter and a chrominance parameter are separately represented) channel, and directly takes the Y-channel data as a gray value. And respectively taking the Y channel data of each pixel point as the gray value of the pixel point, and obtaining the integral gray-scale image according to the gray value of each pixel point.
Step S203: acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image;
the gray-scale image is composed of a plurality of pixel points, and each pixel point corresponds to a gray value.
Specifically, the average gray value of each pixel point in the gray-scale image is calculated, and specifically, the sum of the gray values of each pixel point is divided by the number of the pixel points, so that the obtained numerical value is the average gray value of the gray-scale image.
In practical application, when the ambient brightness around the electronic equipment is higher, the average gray value of the image acquired by the electronic equipment converted into the gray-scale image is also higher; correspondingly, when the ambient brightness around the electronic equipment is low, the average gray value of the image acquired by the electronic equipment converted into the gray-scale image is also low; or the electronic equipment is in fault, so that the brightness of the acquired image is lower or higher, and correspondingly, the average gray value of the gray-scale image obtained by converting the acquired image is lower or higher.
Step S204: judging whether the average gray value meets a preset threshold condition or not;
determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition; and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
When the exposure of the first image is too low or too exposed, the average gray value of the first image does not meet the threshold condition, accordingly, the content of the first image cannot be identified, while the exposure of the first image is proper, and the average gray value of the first image is within the threshold condition, wherein the content of the first image can be identified.
It should be noted that, when the image acquisition module of the electronic device adopts an infrared camera, the acquired image is an infrared image, and correspondingly, the wavelength range of the acquired light is about 900nm (nanometers). In the infrared image acquisition process, the light wavelength range corresponding to the human body is in the content of the infrared imaging range, but in stronger sunlight, the content of the wavelength range is partially the environment due to higher ambient temperature, and the imaging interference to the user is more.
Therefore, the process of the infrared image collected by the image collecting module needs to be processed so as to reduce the influence of the environment on the infrared imaging.
FIG. 3 is a schematic diagram of an overexposed and adjusted image, where (a) is an overexposed grayscale image and (b) is an adjusted grayscale image.
In the graph (a), the white area is an area with strong brightness, and has a large area with strong brightness, and the operation gesture of the user cannot be recognized in the area. On the other hand, the region with strong brightness in the graph (b) is reduced, and the gesture operation of the user can be recognized.
Step S205: analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information;
step S206: and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
Steps S205 to 206 are the same as steps S103 to 104 in embodiment 1, and are not described in detail in this embodiment.
In summary, in an identification method provided in this embodiment, the determining whether the first image meets a preset condition includes: converting the first image into a gray-scale image; acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image; judging whether the average gray value meets a preset threshold condition or not; determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition; and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition. In the scheme, whether the first image is overexposed or underexposed is determined by calculating the average gray value in the gray-scale image corresponding to the first image, and the adjustment is simple and easy.
As shown in fig. 4, a flow chart of embodiment 3 of an identification method provided by the present application includes the following steps:
step S401: receiving a first image acquired by an image acquisition module;
step S402: judging whether the first image meets a preset condition or not;
step S403: analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information;
steps S401 to 403 are the same as steps S101 to 103 in embodiment 1, and are not described in detail in this embodiment.
Step S404: and based on the fact that the first image does not meet the preset condition, adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
Wherein, the parameter of this image acquisition module includes: gain values and exposure times.
In specific implementation, adjusting the parameters of the image acquisition module can be realized by adjusting the gain value and/or the exposure time.
In specific implementation, the gain value and the exposure time are adjusted in a linear mode.
Wherein the linear manner may include: one parameter is used as a fixed value, and the value of the other parameter is adjusted in an arithmetic progression mode.
For example, in the adjustment process, the exposure time is first set as a constant value, the magnitude of the gain value is adjusted, when the gain value is adjusted to be maximum or minimum and a gray value satisfying the condition cannot be obtained, the value of the exposure time is adjusted, and the magnitude of the gain value is adjusted again by the adjusted exposure time.
As a specific example, the first image is an overexposed image, and the adjusting the parameter of the image capturing module includes: the exposure time is not changed, the gain value is reduced, if the range value of the gain value is (10,20), the gain value can be reduced from 20 to 18, 16 … … in sequence until the gain value reaches 10, if the gain value is 10, the average gray value of the gray-scale image converted from the first image collected by the image collecting module is still larger than the threshold value, the exposure time is reduced, and then the reduced exposure time is taken as a fixed value, and the gain value is reduced from the maximum value.
In specific implementation, if the average gray value is larger, the values of the two gain values and the exposure time are respectively adjusted to be smaller; if the average gray value is smaller, the values of the two gain values and the exposure time are respectively adjusted to be larger.
It should be noted that the linear adjustment proposed in the present embodiment is not limited to this, and other adjustment methods may be used.
In summary, in the identification method provided in this embodiment, the adjusting the parameter value of the image capturing module includes: and adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule. By adopting the method, the gray scale of the image is adjusted by adjusting the gain value and/or the exposure time of the image acquisition module, and the adjustment mode is simple and easy.
As shown in fig. 5, a flow chart of embodiment 4 of an identification method provided by the present application includes the following steps:
step S501: receiving a second image acquired by the image acquisition module in a preset environment;
the threshold is detected and set in the preset environment, and the preset environment can be an outdoor environment or an indoor environment.
The second image comprises gesture information of a user.
It should be noted that, when the preset environment is an indoor environment, the brightness of the indoor environment is generally a relatively suitable brightness, that is, the operation gesture information in the image acquired in the indoor environment can be identified; when the preset environment is an outdoor environment, the brightness of the outdoor environment is generally high, and the image with the recognized operation gesture information can be acquired after the parameters of the image acquisition module are adjusted.
Step S502: identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result;
the identification rule is an image identification rule, and the content in the image can be identified based on the identification rule.
The recognition result may include content in the image, specifically including a user operation gesture, an environment, and the like.
Step S503: calculating the average gray value of the second image based on whether the identification result meets a preset identification condition, and setting the average gray value of the second image as a threshold condition;
when the recognition result of the second image meets the preset recognition condition, the user operation gesture information contained in the second image can be accurately recognized, at the moment, the image quality is good, the parameter value of the image acquisition module is appropriate, and the average gray value of the image can be set to be the value corresponding to the threshold condition.
In a specific implementation, the threshold condition may be a range value, and a range threshold (an upper limit and a lower limit) may be obtained by adjusting parameter values of the image acquisition module for multiple times, so as to analyze the acquired first image in the subsequent steps.
Step S504: adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition, so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition;
when the recognition result of the second image does not meet the preset recognition condition, the user operation gesture information contained in the second image cannot be accurately recognized, the image quality is poor, the parameter value of the image acquisition module is not appropriate, and the parameter value of the image acquisition module needs to be adjusted.
The adjustment method is similar to that of the image capturing module in embodiment 3, and is not described again in this embodiment.
In specific implementation, the method can be realized by adjusting the gain value and the exposure time of the image acquisition module.
Step S505: receiving a first image acquired by an image acquisition module;
step S506: judging whether the first image meets a preset condition or not;
step S507: analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information;
step S508: and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
Steps S505 to 508 are the same as steps S101 to 104 in embodiment 1, and are not described in detail in this embodiment.
In summary, in the identification method provided in this embodiment, the method further includes: receiving a second image acquired by the image acquisition module in a preset environment; identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result; calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition; and adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition. By adopting the method, the threshold condition of the average gray value is determined by adjusting the parameters of the image recognition mode in the specific environment, and the accuracy of setting the threshold is higher.
Corresponding to the embodiment of the identification method provided by the application, the application also provides an embodiment of the electronic equipment applying the identification method.
Fig. 6 is a schematic structural diagram of an embodiment of an electronic device provided in the present application, where the electronic device has an image capturing function, and the electronic device includes the following structures: a body 601, an image acquisition module 602 and a processor 603;
the image acquisition module 602 is disposed in the body 601 and configured to acquire a first image;
the processor 603 is configured to receive a first image acquired by the image acquisition module 602; judging whether the first image meets a preset condition or not; analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information; and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
In specific implementation, the image acquisition module can adopt an infrared camera, and correspondingly, the acquired image is an infrared image.
In a specific implementation, the processor may be a chip or the like having data processing capability.
Preferably, the processor is configured to convert the first image into a grayscale image; acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image; judging whether the average gray value meets a preset threshold condition or not; determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition; and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
Preferably, the processor is specifically configured to adjust a gain value and/or an exposure time of the image capturing module according to a preset adjustment rule.
Preferably, the processor is specifically configured to receive a second image acquired by the image acquisition module in a preset environment; identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result; and calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition.
Preferably, the processor is further configured to adjust a parameter value of the image acquisition module based on that the identification result does not satisfy a preset identification condition, so that the image acquisition module acquires a new second image according to the adjusted parameter value until the identification result satisfies the preset identification condition.
In summary, the present embodiment provides an electronic device, which includes: a body; the image acquisition module is arranged in the body and is used for acquiring a first image; the processor is used for receiving a first image acquired by the image acquisition module; judging whether the first image meets a preset condition or not; analyzing the content in the first image based on the fact that the first image meets a preset condition to obtain operation gesture information; and adjusting the parameter value of the image acquisition module based on the fact that the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition. This electronic equipment combines the image parameter value of the image acquisition module of image acquisition module collection real-time adjustment for content can be correctly discerned in the image of gathering, when having solved the light condition relatively poor, and equipment can not carry out the problem of correct discernment to user's gesture.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the device provided by the embodiment, the description is relatively simple because the device corresponds to the method provided by the embodiment, and the relevant points can be referred to the method part for description.
The previous description of the provided embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features provided herein.
Claims (8)
1. An identification method, the method being applied to an electronic device, the method comprising:
receiving a second image acquired by the image acquisition module in a preset environment;
identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result;
calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition;
receiving a first image acquired by an image acquisition module;
judging whether the first image meets a preset condition or not;
analyzing the content in the first image to obtain operation gesture information based on the fact that the average gray value of the first image meets the threshold condition and the first image meets a preset condition;
and adjusting the parameter value of the image acquisition module based on that the average gray value of the first image does not meet the threshold condition and the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
2. The method of claim 1, wherein the determining whether the first image satisfies a preset condition comprises:
converting the first image into a gray-scale image;
acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image;
judging whether the average gray value meets a preset threshold condition or not;
determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition;
and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
3. The method of claim 1, wherein said adjusting parameter values of said image acquisition module comprises:
and adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule.
4. The method of claim 1, further comprising:
and adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition.
5. An electronic device, comprising:
a body;
the image acquisition module is arranged in the body and is used for acquiring a first image;
the processor is used for receiving a second image acquired by the image acquisition module in a preset environment; identifying operation gesture information in the second image according to a preset identification rule to obtain an identification result; calculating the average gray value of the second image based on the recognition result meeting a preset recognition condition, and setting the average gray value of the second image as a threshold condition; receiving a first image acquired by an image acquisition module; judging whether the first image meets a preset condition or not; analyzing the content in the first image to obtain operation gesture information based on the fact that the average gray value of the first image meets the threshold condition and the first image meets a preset condition; and adjusting the parameter value of the image acquisition module based on that the average gray value of the first image does not meet the threshold condition and the first image does not meet the preset condition, so that the image acquisition module acquires a new first image according to the adjusted parameter value until the acquired new first image meets the preset condition.
6. The electronic device of claim 5, wherein the processor is to,
converting the first image into a gray-scale image;
acquiring the gray value of each pixel point in the gray-scale image, and calculating the average gray value in the gray-scale image;
judging whether the average gray value meets a preset threshold condition or not;
determining that the first image meets a preset condition based on the average gray value meeting a preset threshold condition;
and determining that the first image does not meet a preset condition based on that the average gray value does not meet a preset threshold condition.
7. The electronic device of claim 5, wherein the processor is specifically configured to,
and adjusting the gain value and/or the exposure time of the image acquisition module according to a preset adjustment rule.
8. The electronic device of claim 5, wherein the processor is further configured to,
and adjusting the parameter value of the image acquisition module based on the recognition result not meeting the preset recognition condition so that the image acquisition module acquires a new second image according to the adjusted parameter value until the recognition result meets the preset recognition condition.
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