Image acquisition method, device, computer equipment, storage medium and program product

Abstract

The present application relates to an image acquisition method, device, computer equipment, storage medium and program product. The method comprises: color correction of an initial inspection camera to obtain a candidate inspection camera; based on the environmental parameters of the inspection area to be inspected corresponding to the candidate inspection camera, exposure parameter adjustment of the candidate inspection camera is performed to obtain a target inspection camera; image acquisition of the inspection area is performed according to the target inspection camera to obtain a target image of the inspection area. The method can obtain high-quality images.

Description

Technical Field

[0001] The present application relates to the field of imaging technology, and in particular to an image acquisition method, apparatus, computer equipment, storage medium and program product. Background Art

[0002] With the continuous development of drone technology, drones are being used more and more widely. For example, they can be used for power inspection, bridge inspection, oil and gas pipeline inspection, etc.

[0003] At present, the inspection method based on the UAV platform and equipped with UV cameras has become more and more popular. However, UV cameras are very sensitive to lighting conditions. Therefore, when the UAV is equipped with UV cameras, it is easy to cause low image quality, thus affecting the inspection effect. Summary of the invention

[0004] Based on this, it is necessary to provide an image acquisition method, device, computer equipment, storage medium and program product to obtain high-quality images in response to the above technical problems.

[0005] In a first aspect, the present application provides an image acquisition method, the method comprising:

[0006] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0007] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0008] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0009] In one embodiment, color correction is performed on an initial inspection camera to obtain a candidate inspection camera, including:

[0010] The initial inspection camera is calibrated with an ultraviolet light source to obtain an initial inspection camera calibrated with an ultraviolet light source; and the initial inspection camera calibrated with an ultraviolet light source is calibrated with a white balance to obtain a candidate inspection camera.

[0011] In one embodiment, ultraviolet light source calibration is performed on an initial inspection camera to obtain an initial inspection camera after ultraviolet light source calibration, including:

[0012] A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and the initial inspection camera is calibrated with an ultraviolet light source according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, so as to obtain an initial inspection camera after the ultraviolet light source calibration.

[0013] In one embodiment, white balance calibration is performed on an initial inspection camera after ultraviolet light source calibration to obtain a candidate inspection camera, including:

[0014] A white balance reference object is selected; at least two second standard images corresponding to the white balance reference object are obtained based on the initial inspection camera calibrated with the ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions; according to the reference object color of the white balance reference object in each second standard image, the initial inspection camera calibrated with the ultraviolet light source is calibrated with white balance to obtain a candidate inspection camera.

[0015] In one embodiment, based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection camera, exposure parameters of the candidate inspection camera are adjusted to obtain the target inspection camera, including:

[0016] Predict the environmental parameters of the area to be inspected at the current moment; adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters to obtain the target inspection camera.

[0017] In one embodiment, predicting the environmental parameters of the area to be inspected at the current moment includes:

[0018] Obtain the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment based on the regional location coordinates and the real-time meteorological data.

[0019] In a second aspect, the present application further provides an image acquisition device, the device comprising:

[0020] A correction module, used to perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0021] An adjustment module is used to adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters of the inspection area to be inspected corresponding to the candidate inspection cameras to obtain the target inspection camera;

[0022] The acquisition module is used to acquire images of the area to be inspected according to the target inspection camera to obtain the target image of the area to be inspected.

[0023] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0024] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0025] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0026] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0027] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0028] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0029] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0030] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0031] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0032] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0033] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0034] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0035] The above-mentioned image acquisition method, device, computer equipment, storage medium and program product perform color correction on the initial inspection camera and obtain a corrected candidate inspection camera to eliminate the color deviation of the captured image; further, based on the environmental parameters of the area to be inspected, the exposure parameters of the candidate inspection camera are adjusted to obtain a target inspection camera to adapt to the environment of the area to be inspected; then, the area to be inspected is inspected by the target inspection camera, and an image of the area to be inspected is captured to obtain a target image of the area to be inspected. The above-mentioned scheme, by performing color correction and exposure parameter adjustment to adapt the target inspection camera to the area to be inspected, can perfectly reproduce the actual situation of the area to be inspected to the greatest extent, and ensure that the captured target image is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] FIG1 is a diagram of an application environment of an image acquisition method provided in an embodiment of the present application;

[0038] FIG2 is a schematic diagram of a flow chart of an image acquisition method provided in an embodiment of the present application;

[0039] FIG3 is a schematic diagram of a color correction process provided in an embodiment of the present application;

[0040] FIG4 is a schematic diagram of a flow chart of exposure parameter adjustment provided in an embodiment of the present application;

[0041] FIG5 is a schematic diagram of a flow chart of another image acquisition method provided in an embodiment of the present application;

[0042] FIG6 is a structural block diagram of an image acquisition device provided in an embodiment of the present application;

[0043] FIG7 is a structural block diagram of another image acquisition device provided in an embodiment of the present application;

[0044] FIG8 is a structural block diagram of another image acquisition device provided in an embodiment of the present application;

[0045] FIG. 9 is an internal structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] The image acquisition method provided in the embodiment of the present application can be applied in the application environment as shown in Figure 1. Among them, the drone end 102 (equipped with a target inspection camera (adjusted initial inspection camera)) communicates with the server end 104 through the network. The data storage system can store the data that the server end 104 needs to process. The data storage system can be integrated on the server end 104, or it can be placed on the cloud or other network servers. The server end 104 can send control instructions to enable the drone end 102 to control the initial inspection camera to complete operations such as color correction and exposure parameter adjustment, so that the adjusted target inspection camera matches the area to be inspected. Among them, the server end 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0048] In an exemplary embodiment, as shown in FIG. 2 , a method for acquiring an image is provided. The method is described by taking the application of the method to the server 104 in FIG. 1 as an example, and the method may include the following steps:

[0049] S201, performing color correction on an initial inspection camera to obtain a candidate inspection camera.

[0050] Among them, the initial inspection camera can be an ultraviolet camera with high dynamic range (HDR) and automatic exposure control characteristics; the candidate inspection camera can be an ultraviolet camera that has been color-corrected and can cope with shooting requirements under different lighting conditions.

[0051] It should be noted that the sensor of the initial inspection camera may have different responses under different lighting conditions, resulting in color deviation in the captured image. Therefore, the sensor of the initial inspection camera needs to be calibrated to ensure the accuracy of the image.

[0052] For example, the initial inspection camera is calibrated by a preset standard ultraviolet light source, and the gain control parameters of the initial inspection camera are adjusted according to the calibration data; further, the initial inspection camera can be calibrated for white balance by a marker to obtain a candidate inspection camera. The marker can be selected as needed and can be a single color that meets the white balance standard, for example, the marker can be a white card or other white marker.

[0053] Optionally, the drone can be used as a platform, equipped with a candidate inspection camera (the target inspection camera before parameter adjustment), which can control the shooting path and collect images taken by the candidate inspection camera, and transmit the collected images to the server side 104, which processes and analyzes the captured images, and extracts the data of the found problems and feeds them back to the staff.

[0054] S202, adjusting exposure parameters of candidate inspection cameras based on environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras to obtain a target inspection camera.

[0055] Among them, the area to be inspected can be any area that the target inspection camera inspects by image capture; environmental parameters can refer to parameters related to the environment in the area to be inspected, which may include but are not limited to solar altitude, solar azimuth, light radiation intensity, rainfall, atmospheric transparency, temperature, humidity, air pressure, wind direction, wind speed, sky brightness, sky color, inspection height (the height of the candidate inspection camera perpendicular to the ground) and inspection pitch angle and other parameters; the target inspection camera can be a camera that inspects by image capture in the environment of the area to be inspected.

[0056] It should be noted that the temperature, humidity, air pressure and wind direction in the environmental parameters will affect the normal operation of the drone, and thus affect the candidate inspection cameras. For example, the temperature in the environmental parameters can affect the battery life of the drone. When the temperature is at the optimal value, the battery life of the drone can reach the maximum; the atmospheric transparency and humidity can affect the vision of the drone and the working state of some hardware circuits; the wind speed and wind direction can affect the range of the drone, etc.

[0057] Exemplarily, the server end 104 can obtain the location parameters of the candidate inspection camera and the environmental parameters of the area to be inspected; further, the state of the drone can be determined by the obtained location parameters and environmental parameters; by combining the location parameters, environmental parameters and the state of the drone, the current optimal exposure parameters of the candidate inspection camera can be determined, and the exposure parameters of the candidate inspection camera can be adjusted accordingly; at this time, a target inspection camera that adapts to the environment of the area to be inspected is obtained.

[0058] S203, acquiring an image of the area to be inspected according to the target inspection camera to obtain a target image of the area to be inspected.

[0059] The target image may be an inspection image corresponding to the area to be inspected, may be a group of images, or may be a single image.

[0060] Exemplarily, the server end 104 can send an inspection instruction to the target inspection camera; then, the target inspection camera inspects the inspection area according to the received inspection instruction, and takes images to obtain the target image of the inspection area; further, the server end 104 can obtain the target image, and process and analyze the target image. If an abnormality is found in the target image, the staff can be reminded.

[0061] Optionally, during the inspection of the area to be inspected, the target image and the lighting conditions of the area to be inspected are continuously monitored; if the lighting conditions of the area to be inspected change, the exposure parameters of the target inspection camera are readjusted to ensure the high quality of the target image.

[0062] The above-mentioned image acquisition method performs color correction on the initial inspection camera and obtains the corrected candidate inspection camera to eliminate the color deviation of the captured image; further, based on the environmental parameters of the area to be inspected, the exposure parameters of the candidate inspection camera are adjusted to obtain the target inspection camera to adapt to the environment of the area to be inspected; then, the target inspection camera is used to inspect the area to be inspected, and an image of the area to be inspected is captured to obtain the target image of the area to be inspected. The above-mentioned scheme, by performing color correction and exposure parameter adjustment to adapt the target inspection camera to the area to be inspected, can perfectly reproduce the actual situation of the area to be inspected to the greatest extent, and ensure that the captured target image is more accurate.

[0063] Based on the above embodiment, the embodiment of the present application explains the above embodiment S201 in detail. Specifically, the embodiment of the present application involves a process of color correction for an initial inspection camera, as shown in FIG3 , which specifically includes the following steps:

[0064] S301, calibrate the initial inspection camera with an ultraviolet light source to obtain the initial inspection camera calibrated with the ultraviolet light source.

[0065] A feasible method comprises the following steps: selecting a standard ultraviolet light source; obtaining a first standard image corresponding to the standard ultraviolet light source based on an initial inspection camera; and calibrating the initial inspection camera with an ultraviolet light source according to the spectral difference between the image spectrum of the first standard image and the standard spectrum, thereby obtaining an initial inspection camera with the ultraviolet light source calibrated.

[0066] Exemplarily, a standard ultraviolet light source with known wavelength and light intensity is selected; wherein the standard ultraviolet light source can be a special ultraviolet lamp or light source, and the spectral characteristics of the quasi-ultraviolet light source have been measured and recorded in detail. Further, the initial inspection camera is set to ensure that the exposure time and aperture are set appropriately, the initial inspection camera is aimed at the standard ultraviolet light source, and an image is taken to obtain a first standard image. Then, the first standard image and the standard spectrum corresponding to the standard ultraviolet light source are spectrally compared, and based on the result of the spectral comparison, the response of the sensor of the initial inspection camera and the like can be determined, and the sensor in the initial inspection camera and the like can be adjusted to complete the calibration of the ultraviolet light source of the initial inspection camera, and finally the initial inspection camera after the ultraviolet light source calibration is obtained.

[0067] Another possible implementation method is to calibrate the UV light source of the initial inspection camera through the UV light source calibration model. The UV light source calibration model can analyze the video stream captured by the initial inspection camera through the AI ​​(Artificial Intelligence) target detection algorithm, and determine the parameters to be adjusted for the initial inspection camera, and finally achieve UV light source calibration for the initial inspection camera.

[0068] S302, performing white balance calibration on the initial inspection camera after the ultraviolet light source is calibrated to obtain a candidate inspection camera.

[0069] A feasible method comprises the following steps: selecting a white balance reference object; obtaining at least two second standard images corresponding to the white balance reference object based on an initial inspection camera calibrated with an ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with an ultraviolet light source under different lighting conditions; and performing white balance calibration on the initial inspection camera calibrated with an ultraviolet light source according to the reference object color of the white balance reference object in each second standard image to obtain a candidate inspection camera.

[0070] Exemplarily, a standard white balance reference is selected; wherein the white balance reference may be a white reference card or an object, to ensure that the white balance reference can maintain a relatively stable color under ultraviolet light. Further, under different lighting conditions, an initial inspection camera calibrated with an ultraviolet light source is used to capture images to obtain a second standard image; wherein the second standard image must include the white balance reference; in addition, images are captured under at least two different lighting conditions, i.e., at least two second standard images are obtained.

[0071] Then, each second standard image is analyzed, and the initial inspection camera calibrated with the ultraviolet light source is white-balanced according to the analysis result to obtain a candidate inspection camera. Optionally, the reference color of the white balance reference object in each second standard image is analyzed and compared to determine the white balance offset of the initial inspection camera under different lighting conditions, and the parameters of the initial inspection camera are set according to the white balance offset of the initial inspection camera to obtain a candidate inspection camera.

[0072] Another possible implementation method is to complete the white balance calibration of the initial inspection camera through a white balance calibration model. The white balance calibration model can analyze the video stream captured by the initial inspection camera through a white balance algorithm, and determine the white balance offset of the initial inspection camera under different lighting conditions, and finally set the parameters of the initial inspection camera according to the white balance offset to make the image captured by the initial inspection camera more accurate.

[0073] In the embodiment of the present application, the ultraviolet light source calibration and white balance calibration of the initial inspection camera are performed to lay the foundation for the accuracy of the image.

[0074] Based on the above embodiment, the embodiment of the present application explains the above embodiment S202 in detail. Specifically, the embodiment of the present application involves a process of adjusting the exposure parameters of the candidate inspection camera, as shown in FIG4 , which specifically includes the following steps:

[0075] S401, predicting the environmental parameters of the area to be inspected at the current moment.

[0076] A feasible method is to obtain the regional position coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment according to the regional position coordinates and the real-time meteorological data.

[0077] Exemplarily, based on the positioning module installed on the drone end 102, the regional position coordinates of the area to be inspected where the drone end 102 is currently located can be determined; further, based on the regional position coordinates of the area to be inspected, the real-time meteorological data of the area to be inspected can be determined from a meteorological station or other meteorological data source; further, the regional position coordinates and the real-time meteorological data can be input into a sky prediction model, which analyzes the regional position coordinates and the real-time meteorological data and predicts the environmental parameters of the area to be inspected at the current moment, for example, predicting the sky brightness and sky color in the environmental parameters.

[0078] The sky prediction model can be trained by a large amount of historical meteorological data, regional location coordinate data and historical environmental parameter data; the historical meteorological data and regional location coordinate data can constitute training samples, and the historical environmental parameter data can be used as training labels corresponding to the training samples. The sky prediction model can be regularly updated according to the supplemented historical data.

[0079] Optionally, the initial sky prediction model can determine the solar zenith angle parameters based on historical meteorological data and regional location coordinate data ; Furthermore, based on the solar zenith angle parameter , the sky brightness and sky color in the historical environmental parameters can be predicted; the prediction process can be expressed as:

[0080] (1)

[0081] (2)

[0082] Where I is the sky brightness, T is the sky color, and A, B, C, F1, F2, F3, and D are model parameters.

[0083] Furthermore, the predicted environmental parameters (I and T) can be compared with the corresponding historical environmental parameters, and the model parameters in the initial sky prediction model can be adjusted according to the comparison results. After the model parameters are adjusted, the above parameter prediction and the process of comparing the predicted environmental parameters with the corresponding historical environmental parameters are repeated until the comparison result meets the preset comparison result. At this time, the sky prediction model is obtained. The preset comparison result can be that the variance is less than the preset variance. The preset comparison result is not specifically limited in the present embodiment of the application.

[0084] Another feasible method is to obtain historical meteorological data, historical regional location coordinate data and historical environmental parameter data of the area to be inspected; wherein, a set of historical meteorological data and historical regional location coordinate data corresponds to one historical environmental parameter data; further, at least one data similar to the real-time meteorological data and regional location coordinate data of the area to be inspected at the current moment can be selected from the historical meteorological data and historical regional location coordinate data as class data, and the historical environmental parameter data corresponding to the class data can be directly used as the predicted environmental parameters of the area to be inspected at the current moment.

[0085] S402: adjusting exposure parameters of candidate inspection cameras based on environmental parameters to obtain a target inspection camera.

[0086] Exemplarily, the actual illumination value of the area to be inspected at the current moment is determined based on the sky brightness and sky color in the environmental parameters; wherein the actual illumination value can represent the actual illumination conditions; further, the actual illumination value is compared with the target illumination value to determine the difference between the actual illumination value and the target illumination value; wherein the target illumination value can represent the optimal illumination conditions required for image capture; and then, based on the difference, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera.

[0087] For example, the exposure time in the exposure parameters is adjusted, and the adjustment process can be expressed as:

[0088] (3)

[0089] Among them, Exposure new is the adjusted exposure time, Exposure current is the exposure time before adjustment, Illuminance target is the target illumination value, Illuminance estimated is the actual lighting value.

[0090] Optionally, the filter and lens of the target inspection camera may be determined according to the predicted environmental parameters of the area to be inspected at the current moment, so as to better improve the image quality.

[0091] Furthermore, during the inspection process of the target inspection camera, the target image captured by the target inspection camera is monitored in real time to detect changes in lighting conditions and adjust the exposure parameters of the target inspection camera in real time.

[0092] For example, during the inspection process of the target inspection camera, the real-time sensor data of the target inspection camera is continuously obtained, which may include but is not limited to the brightness, light intensity and spectral data of the current target image; then, based on the real-time meteorological data and real-time sensor data, the relevant parameters in the sky prediction model are regularly updated to accurately reflect the current lighting conditions (actual lighting values); further, the updated sky prediction model is used to calculate the target exposure parameters under the current lighting conditions, for example, the target exposure time Exposure target ; Then, based on the target exposure time Exposure target and the current exposure time Exposure current , determine the exposure time adjustment amount ΔExposure; Optionally, the calculation process of the adjustment amount ΔExposure can be expressed as ΔExposure=k·(Exposure target -Exposure current ); where k is an adjustable gain parameter used to control the speed of exposure adjustment; according to the adjustment amount ΔExposure, the current exposure time Exposure current Make adjustments; optionally, the adjustment process can be expressed as Exposure new =Exposure current +ΔExposure.

[0093] In the embodiment of the present application, by predicting the environmental parameters of the area to be inspected at the current moment and adjusting the exposure parameters of the candidate inspection cameras according to the predicted environmental parameters, a foundation is laid for the accuracy of the captured images.

[0094] Based on the above embodiment, this embodiment provides an optional example of an image acquisition method. As shown in FIG5 , the specific implementation process is as follows:

[0095] S501, select a standard ultraviolet light source.

[0096] S502: Acquire a first standard image corresponding to a standard ultraviolet light source based on an initial inspection camera.

[0097] S503, performing ultraviolet light source calibration on the initial inspection camera according to the spectrum difference between the image spectrum of the first standard image and the standard spectrum, to obtain the initial inspection camera after ultraviolet light source calibration.

[0098] S504: Select a white balance reference object.

[0099] S505 , acquiring at least two second standard images corresponding to a white balance reference object based on the initial inspection camera calibrated with the ultraviolet light source.

[0100] Among them, each second standard image is an image acquired by the initial inspection camera under different lighting conditions after being calibrated with an ultraviolet light source.

[0101] S506 , performing white balance calibration on the initial inspection camera calibrated with the ultraviolet light source according to the reference object color of the white balance reference object in each second standard image to obtain a candidate inspection camera.

[0102] S507, obtaining the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected.

[0103] S508, predicting the environmental parameters of the area to be inspected at the current moment according to the area location coordinates and real-time meteorological data.

[0104] S509, adjusting exposure parameters of candidate inspection cameras based on environmental parameters to obtain a target inspection camera.

[0105] S510, acquiring an image of the area to be inspected by a target inspection camera to obtain a target image of the area to be inspected.

[0106] The specific process of S501-S510 can refer to the description of the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0107] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0108] Based on the same inventive concept, the embodiment of the present application also provides an image acquisition device for implementing the above-mentioned image acquisition method. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations in one or more image acquisition device embodiments provided below can refer to the limitations on the image acquisition method above, and will not be repeated here.

[0109] In an exemplary embodiment, as shown in FIG6 , an image acquisition device 1 is provided, comprising: a correction module 10, an adjustment module 20 and an acquisition module 30, wherein:

[0110] The correction module 10 is used to perform color correction on the initial inspection camera to obtain a candidate inspection camera.

[0111] The adjustment module 20 is used to adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras to obtain the target inspection camera.

[0112] The acquisition module 30 is used to acquire an image of the area to be inspected according to the target inspection camera to obtain a target image of the area to be inspected.

[0113] In one embodiment, as shown in FIG7 , the correction module 10 specifically further includes:

[0114] The calibration unit 11 is used to perform ultraviolet light source calibration on the initial inspection camera to obtain the initial inspection camera after the ultraviolet light source calibration.

[0115] The calibration unit 12 is used to perform white balance calibration on the initial inspection camera after the ultraviolet light source is calibrated to obtain a candidate inspection camera.

[0116] In one embodiment, the calibration unit 11 is further configured to:

[0117] A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and the initial inspection camera is calibrated with an ultraviolet light source according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, so as to obtain an initial inspection camera after the ultraviolet light source calibration.

[0118] In one embodiment, the calibration unit 12 is specifically configured to:

[0119] A white balance reference object is selected; at least two second standard images corresponding to the white balance reference object are obtained based on the initial inspection camera calibrated with the ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions; according to the reference object color of the white balance reference object in each second standard image, the initial inspection camera calibrated with the ultraviolet light source is calibrated with white balance to obtain a candidate inspection camera.

[0120] In one embodiment, as shown in FIG8 , the adjustment module 20 specifically further includes:

[0121] The prediction unit 21 is used to predict the environmental parameters of the area to be inspected at the current moment.

[0122] The parameter adjustment unit 22 is used to adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters to obtain the target inspection camera.

[0123] In one embodiment, the prediction unit 21 is specifically used for:

[0124] Obtain the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment based on the regional location coordinates and the real-time meteorological data.

[0125] Each module in the above-mentioned image acquisition device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0126] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG9. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store image data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, an image acquisition method is implemented.

[0127] Those skilled in the art will understand that the structure shown in FIG. 9 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0128] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0129] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0130] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0131] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0132] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0133] The initial inspection camera is calibrated with an ultraviolet light source to obtain an initial inspection camera calibrated with an ultraviolet light source; and the initial inspection camera calibrated with an ultraviolet light source is calibrated with a white balance to obtain a candidate inspection camera.

[0134] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0135] A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and the initial inspection camera is calibrated with an ultraviolet light source according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, so as to obtain an initial inspection camera after the ultraviolet light source calibration.

[0136] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0137] A white balance reference object is selected; at least two second standard images corresponding to the white balance reference object are obtained based on the initial inspection camera calibrated with the ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions; according to the reference object color of the white balance reference object in each second standard image, the initial inspection camera calibrated with the ultraviolet light source is calibrated with white balance to obtain a candidate inspection camera.

[0138] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0139] Predict the environmental parameters of the area to be inspected at the current moment; adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters to obtain the target inspection camera.

[0140] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0141] Obtain the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment based on the regional location coordinates and the real-time meteorological data.

[0142] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0143] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0144] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0145] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0146] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0147] The initial inspection camera is calibrated with an ultraviolet light source to obtain an initial inspection camera calibrated with an ultraviolet light source; and the initial inspection camera calibrated with an ultraviolet light source is calibrated with a white balance to obtain a candidate inspection camera.

[0148] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0149] A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and the initial inspection camera is calibrated with an ultraviolet light source according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, so as to obtain an initial inspection camera after the ultraviolet light source calibration.

[0150] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0151] A white balance reference object is selected; at least two second standard images corresponding to the white balance reference object are obtained based on the initial inspection camera calibrated with the ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions; according to the reference object color of the white balance reference object in each second standard image, the initial inspection camera calibrated with the ultraviolet light source is calibrated with white balance to obtain a candidate inspection camera.

[0152] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0153] Predict the environmental parameters of the area to be inspected at the current moment; adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters to obtain the target inspection camera.

[0154] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0155] Obtain the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment based on the regional location coordinates and the real-time meteorological data.

[0156] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0157] Perform color correction on the initial inspection camera to obtain a candidate inspection camera;

[0158] Based on the environmental parameters of the to-be-inspected area corresponding to the candidate inspection cameras, the exposure parameters of the candidate inspection cameras are adjusted to obtain the target inspection camera;

[0159] The target inspection camera acquires images of the area to be inspected to obtain a target image of the area to be inspected.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0161] The initial inspection camera is calibrated with an ultraviolet light source to obtain an initial inspection camera calibrated with an ultraviolet light source; and the initial inspection camera calibrated with an ultraviolet light source is calibrated with a white balance to obtain a candidate inspection camera.

[0162] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0163] A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and the initial inspection camera is calibrated with an ultraviolet light source according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, so as to obtain an initial inspection camera after the ultraviolet light source calibration.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0165] A white balance reference object is selected; at least two second standard images corresponding to the white balance reference object are obtained based on the initial inspection camera calibrated with the ultraviolet light source; wherein each second standard image is an image obtained by the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions; according to the reference object color of the white balance reference object in each second standard image, the initial inspection camera calibrated with the ultraviolet light source is calibrated with white balance to obtain a candidate inspection camera.

[0166] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0167] Predict the environmental parameters of the area to be inspected at the current moment; adjust the exposure parameters of the candidate inspection cameras based on the environmental parameters to obtain the target inspection camera.

[0168] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0169] Obtain the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; and predict the environmental parameters of the area to be inspected at the current moment based on the regional location coordinates and the real-time meteorological data.

[0170] It should be noted that the information (including but not limited to camera equipment information, inspection area information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all authorized or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0171] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0172] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0173] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An image acquisition method, characterized in that: The method comprises: Performing ultraviolet light source calibration on the initial inspection camera to obtain the initial inspection camera after ultraviolet light source calibration; Controlling the initial inspection camera after the ultraviolet light source is calibrated to capture images of the white balance reference object to obtain at least two second standard images; Based on the reference object color of the white balance reference object in each second standard image, white balance calibration is performed on the initial inspection camera after the ultraviolet light source is calibrated to obtain a candidate inspection camera; Based on the regional location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected, predict the environmental parameters of the area to be inspected at the current moment; wherein the environmental parameters are parameters related to the environment in the area to be inspected; Based on the environmental parameters, determining the actual light value of the area to be inspected; Based on the difference between the actual illumination value and the target illumination value, the exposure time of the candidate inspection camera is adjusted to obtain the target inspection camera; The target inspection camera acquires an image of the area to be inspected to obtain a target image of the area to be inspected.

2. The method according to claim 1, characterized in that The step of adjusting the exposure time of the candidate inspection camera based on the difference between the actual illumination value and the target illumination value to obtain the target inspection camera includes: Among them, Exposure new is the adjusted exposure time, Exposure current is the exposure time, Illuminance target is the target illumination value, Illuminance estimated is the actual lighting value.

3. The method according to claim 1, characterized in that The ultraviolet light source calibration is performed on the initial inspection camera to obtain the initial inspection camera after the ultraviolet light source calibration, including: Select a standard UV light source; Acquire a first standard image corresponding to the standard ultraviolet light source based on an initial inspection camera; According to the spectral difference between the image spectrum of the first standard image and the standard spectrum, the initial inspection camera is calibrated with an ultraviolet light source to obtain an initial inspection camera calibrated with an ultraviolet light source.

4. The method according to claim 1, characterized in that: The controlling the initial inspection camera after the ultraviolet light source is calibrated to capture images of the white balance reference object to obtain at least two second standard images includes: Select a white balance reference; Acquire at least two second standard images corresponding to the white balance reference object based on the initial inspection camera calibrated by the ultraviolet light source; wherein each second standard image is an image acquired by the initial inspection camera calibrated by the ultraviolet light source under different lighting conditions; According to the reference object color of the white balance reference object in each second standard image, white balance calibration is performed on the initial inspection camera after the ultraviolet light source is calibrated to obtain a candidate inspection camera.

5. The method according to claim 1, characterized in that The step of performing white balance calibration on the initial inspection camera calibrated with the ultraviolet light source based on the reference object color of the white balance reference object in each second standard image to obtain a candidate inspection camera includes: Determining the white balance offset of the initial inspection camera calibrated with the ultraviolet light source under different lighting conditions based on the reference object color of the white balance reference object in each second standard image; Based on the white balance deviation of the initial inspection camera calibrated by the ultraviolet light source under different lighting conditions, the initial inspection camera calibrated by the ultraviolet light source is calibrated to obtain a candidate inspection camera.

6. An image acquisition device, characterized in that: The device comprises: A calibration module is used to calibrate the initial inspection camera with an ultraviolet light source to obtain the initial inspection camera after the ultraviolet light source calibration; A shooting module, used to control the initial inspection camera after the ultraviolet light source is calibrated to shoot images of the white balance reference object to obtain at least two second standard images; A calibration module, configured to perform white balance calibration on the initial inspection camera calibrated by the ultraviolet light source based on the reference object color of the white balance reference object in each second standard image, to obtain a candidate inspection camera; A prediction module, used to predict the environmental parameters of the area to be inspected at the current moment based on the area location coordinates of the area to be inspected and the real-time meteorological data of the area to be inspected; wherein the environmental parameters are parameters related to the environment in the area to be inspected; An illumination determination module, used to determine the actual illumination value of the area to be inspected based on the environmental parameters; An adjustment module, configured to adjust the exposure time of the candidate inspection camera based on the difference between the actual illumination value and the target illumination value, so as to obtain the target inspection camera; The acquisition module is used to acquire an image of the area to be inspected based on the target inspection camera to obtain a target image of the area to be inspected.

7. The device according to claim 6, characterized in that The calibration module also includes: A standard ultraviolet light source is selected; a first standard image corresponding to the standard ultraviolet light source is obtained based on an initial inspection camera; and according to a spectral difference between an image spectrum of the first standard image and a standard spectrum, an ultraviolet light source is calibrated on the initial inspection camera to obtain an initial inspection camera after ultraviolet light source calibration.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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