Method and device for selecting x-ray exposure parameters for individual trees of different species

Abstract

The application discloses a different tree species single tree X-ray exposure parameter selection method and device, and belongs to the technical field of forestry detection. The method comprises the following steps: acquiring a plurality of frames of X-ray images of a target tree collected by an image sensor under a plurality of different parameter combinations at different punching depths; determining a target parameter combination corresponding to the target tree at the same punching depth based on the imaging effect of the plurality of frames of X-ray images collected by the image sensor under the plurality of different parameter combinations at the same punching depth; constructing a correlation between the target parameter combination corresponding to each different target tree and the target thickness; and determining the X-ray exposure parameter of the image sensor based on the correlation, the initial trunk diameter of the single tree to be measured and the tree species category of the single tree to be measured. The method of the application can accurately, clearly and efficiently collect the internal structure information of the tree under the premise of maximizing the retention of the complete trunk area.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of forestry detection, and particularly relates to a method and device for selecting X-ray exposure parameters of single trees of different tree species. BACKGROUND

[0002] With the deepening of researches on forestry resource monitoring, tree growth evaluation and wood quality prediction, obtaining internal structure information of trees has become a key requirement in forestry scientific research and actual production management. Traditional detection methods mostly rely on destructive sampling, which not only affects the normal growth of trees, but also has problems such as complicated operation, low efficiency and insufficient data representativeness. In recent years, X-ray nondestructive imaging technology has gradually been applied in internal detection of wood and trees due to its advantages of rapidity, intuitiveness and high resolution.

[0003] However, when the X-ray imaging method is applied to tree detection, in the related art, different trees under the same tree species category need to be photographed multiple times, and then the best image with the best imaging effect is selected by subjective comparison by human eyes, which consumes a lot of effort and time, and the accuracy of the finally determined exposure parameters is low. Especially in the practicality of field nondestructive detection and large-scale forest survey, there is still room for improvement, and it is urgent to develop a tree internal imaging solution with adaptability, high resolution and high efficiency to meet the needs of modern forestry informatization and fine management. SUMMARY

[0004] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides a method and device for selecting X-ray exposure parameters of single trees of different tree species, which can accurately, clearly and efficiently collect internal structure information of trees while maximizing the preservation of the complete area of the trunk in the process of tree research, and has a wide range of application scenarios, high universality and stability.

[0005] In a first aspect, the present application provides a method for selecting X-ray exposure parameters of single trees of different tree species, which comprises:

[0006] obtaining multiple frames of X-ray images of a target tree corresponding to multiple different drilling depths, which are collected by an image sensor under multiple sets of different parameter combinations; the lens center of the image sensor and a marked point of the target tree are on the same horizontal line, and the drilling depth is obtained by drilling the target tree along the diameter direction of the marked point;

[0007] determining a target parameter combination corresponding to the same drilling depth of the target tree based on the imaging effects of multiple frames of X-ray images collected by the image sensor under multiple sets of different parameter combinations corresponding to the same drilling depth;

[0008] constructing a correlation between a target parameter combination corresponding to each different target tree and a target thickness, the target thickness being a difference between an initial stem diameter of each of the target trees and the drilling depth;

[0009] Based on the correlation, the initial stem diameter of the to-be-tested single tree, and the species category of the to-be-tested single tree, an X-ray exposure parameter of the image sensor is determined to collect an X-ray image of the to-be-tested single tree.

[0010] According to the different tree species single tree X-ray exposure parameter selection method of the present application, a target tree is drilled to obtain multiple frames of X-ray images of the target tree corresponding to multiple different drilling depths, which are collected by an image sensor under multiple different parameter combinations. Based on the imaging effect of the X-ray images, critical exposure parameters corresponding to each drilling depth are determined, and then the drilling depth is converted into a stem thickness under the same species category to obtain critical exposure parameters corresponding to each stem thickness. The method is simple to operate and easy to implement, and has low cost. Without affecting the tree body, the sampling error can be effectively reduced, and the accuracy and precision of the determined target parameter combination can be improved, so that the imaging quality is maintained while effectively avoiding the problems caused by underexposure or overexposure. In the process of tree research, the internal structure of the tree can be accurately, clearly, and efficiently collected under the premise of maximizing the preservation of the complete area of the stem, and the method has a wide range of application scenarios, high universality, and stability.

[0011] According to an embodiment of the present application, the multiple frames of X-ray images of the target tree corresponding to multiple different drilling depths, which are collected by the image sensor under multiple different parameter combinations, include:

[0012] The X-ray image of the target tree corresponding to the same drilling depth, which is collected by the image sensor under the initial parameter combination;

[0013] Adjusting the parameters of the target category in the initial parameter combination along a target adjustment direction and a target adjustment step, and keeping the parameters of other categories unchanged, reacquiring the X-ray image of the target tree corresponding to the same drilling depth, which is collected by the image sensor under the adjusted initial parameter combination.

[0014] The multiple frames of X-ray images of the target tree corresponding to the initial drilling depth, which are collected by the image sensor under multiple different parameter combinations;

[0015] Adjust the initial drilling depth, and obtain multiple frames of X-ray images of the target tree corresponding to the adjusted initial drilling depth, which are captured by the image sensor under multiple sets of different parameter combinations.

[0016] According to an embodiment of the present application, the imaging effect of the multiple frames of X-ray images corresponding to the same drilling depth and captured by the image sensor under multiple sets of different parameter combinations is used to determine the target parameter combination corresponding to the same drilling depth of the target tree, including:

[0017] Image recognition is performed on the multiple frames of X-ray images corresponding to the same drilling depth based on an adjustment sequence, which is the sequence for adjusting the parameters of the target category in the parameter combination during image acquisition.

[0018] When the marker point is not displayed in the X-ray image for the first time, the parameter combination corresponding to the previous frame of X-ray image of the X-ray image is determined as the target parameter combination corresponding to the same drilling depth.

[0019] According to an embodiment of the present application, the imaging effect of the multiple frames of X-ray images corresponding to the same drilling depth and captured by the image sensor under multiple sets of different parameter combinations is used to determine the target parameter combination corresponding to the same drilling depth of the target tree, including:

[0020] Obtain multiple frames of X-ray images of other trees of the same tree species as the target tree under multiple drilling depths and multiple sets of different parameter combinations.

[0021] Based on the imaging effect of the multiple frames of X-ray images corresponding to the same target thickness of each tree, the target parameter combination corresponding to the same target thickness of each tree is determined.

[0022] Based on the average value of the target parameter combination corresponding to the same target thickness of each tree, the target parameter combination corresponding to the same target thickness of the target tree is determined.

[0023] According to an embodiment of the present application, the imaging effect of the multiple frames of X-ray images corresponding to the same drilling depth and captured by the image sensor under multiple sets of different parameter combinations is used to determine the target parameter combination corresponding to the same drilling depth of the target tree, including:

[0024] adjusting the parameter of the target category in the initial parameter combination along the target adjustment direction and the target adjustment step, keeping the parameters of other categories unchanged at the first values, determining, based on the imaging effect of the collected multiple X-ray images, the optimal value of the parameter of the target category corresponding to the parameters of the other categories being the first values, and determining the first values of the parameters of the other categories and the optimal value of the parameter of the target category as a set of target parameter combinations;

[0025] adjusting the value of the parameter of the first category in the parameters of the other categories to a second value, keeping the values of the parameters of the remaining categories in the parameters of the other categories unchanged at the first values, adjusting the parameter of the target category along the target adjustment direction and the target adjustment step, and determining, based on the imaging effect of the collected multiple X-ray images, the optimal value of the parameter of the target category corresponding to the parameter of the first category being the second value and the values of the parameters of the remaining categories being the first values, and determining the parameter of the first category being the second value, the values of the parameters of the remaining categories being the first values, and the optimal value of the parameter of the target category as a set of target parameter combinations.

[0026] According to an embodiment of the present application, the construction of the association between the target parameter combination corresponding to each different target tree and the target thickness includes:

[0027] Taking the target thickness and the species categories corresponding to multiple target trees as samples and taking the target parameter combination as a sample label, a training sample is constructed.

[0028] The multiple training samples are input into a network model, the network model outputs a predicted parameter combination, the network model is trained to predict the parameter combination, and the association is learned.

[0029] According to an embodiment of the present application, the parameter combination includes a tube voltage parameter, a tube current parameter, and an exposure time parameter, and the parameters of each category are independent of each other.

[0030] According to an embodiment of the present application, the determination of the X-ray exposure parameter of the image sensor to collect the X-ray image of the to-be-measured single tree based on the association, the initial trunk diameter of the to-be-measured single tree, and the species category of the to-be-measured single tree includes:

[0031] Based on the bark thickness of the to-be-measured single tree, a first width is determined.

[0032] Based on the first width, the species category of the to-be-measured single tree, and the association between the target parameter combination and the target thickness, a predicted parameter combination corresponding to the to-be-measured single tree is determined.

[0033] adjust X-ray exposure parameters of the image sensor based on the predicted parameter combination to capture the X-ray image of the single tree to be measured.

[0034] In a second aspect, the present application provides a device for selecting X-ray exposure parameters of single trees of different species, comprising:

[0035] A first processing module is configured to acquire a plurality of X-ray images of a target tree corresponding to a plurality of different drilling depths, which are captured by an image sensor under a plurality of different parameter combinations; the lens center of the image sensor and a marker point of the target tree are on the same horizontal line, and the drilling depth is obtained by drilling the target tree along the diameter direction of the marker point;

[0036] A second processing module is configured to determine a target parameter combination corresponding to the same drilling depth based on the imaging effect of a plurality of X-ray images captured by the image sensor under a plurality of different parameter combinations corresponding to the same drilling depth;

[0037] A third processing module is configured to construct a correlation between the target parameter combination corresponding to each different target tree and a target thickness, wherein the target thickness is the difference between the initial trunk diameter of each target tree and the drilling depth;

[0038] A fourth processing module is configured to determine X-ray exposure parameters of the image sensor based on the correlation, the initial trunk diameter of the single tree to be measured, and the species category of the single tree to be measured, to capture the X-ray image of the single tree to be measured.

[0039] According to the device for selecting X-ray exposure parameters of single trees of different species, the target tree is drilled to acquire a plurality of X-ray images of the target tree corresponding to a plurality of different drilling depths, which are captured by an image sensor under a plurality of different parameter combinations, the critical exposure parameters corresponding to each drilling depth are determined based on the imaging effect of the X-ray images, and then the drilling depth is converted into the trunk thickness under the same species category to obtain the critical exposure parameters corresponding to each trunk thickness, which is simple to operate, easy to implement, and low in cost. Without affecting the tree body, the sampling error can be effectively reduced, the accuracy and precision of the determined target parameter combination can be improved, the problems caused by underexposure or overexposure can be effectively avoided while maintaining the imaging quality, the internal structure of the tree can be accurately, clearly, and efficiently captured on the premise of maximizing the preservation of the complete area of the trunk, and the device has a wide application scenario, high universality, and stability.

[0040] In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for selecting X-ray exposure parameters of a single tree of different tree species according to the first aspect.

[0041] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the method for selecting X-ray exposure parameters of a single tree of different tree species according to the first aspect.

[0042] In a fifth aspect, the present application provides a computer program product comprising a computer program, wherein the computer program is executable by a processor to implement the method for selecting X-ray exposure parameters of a single tree of different tree species according to the first aspect.

[0043] The one or more technical solutions described above in the embodiments of the present application have at least one of the following technical effects:

[0044] By punching the target tree, multiple frames of X-ray images of the target tree corresponding to multiple different punching depths are acquired under multiple different parameter combinations, the critical exposure parameters corresponding to each punching depth are determined based on the imaging effect of the X-ray images, and then the punching depth is converted into the trunk thickness under the same tree species category, so as to obtain the critical exposure parameters corresponding to each trunk thickness. The operation is simple and easy to implement, and the cost is low. Without affecting the tree body, the sampling error can be effectively reduced, and the accuracy and accuracy of the determined target parameter combination are improved, so that the problems caused by underexposure or overexposure can be effectively avoided while maintaining the imaging quality, so that the internal structure of the tree can be accurately, clearly and efficiently acquired under the premise of maximizing the preservation of the complete area of the trunk in the tree research process. It has a wide application scenario, high universality and stability.

[0045] Further, by setting each exposure parameter as a parameter that can be adjusted independently, the data dimension is higher and the relationship between variables is more complex in the case of simultaneous change of three variables including tube voltage, tube current and exposure time, which can further improve the accuracy and accuracy of the subsequently determined critical exposure parameters.

[0046] Further, the deep learning algorithm is used to learn the correlation between the target parameter combination and the target thickness, which can learn the relationship between more complex multiple different dimensions of exposure parameters and tree features, thereby improving the accuracy and accuracy of the exposure parameters calculated according to the tree species category and the trunk thickness, further improving the imaging effect, and the operation is simple and convenient, and the calculation efficiency is high.

[0047] Further, by replacing the stem thickness with the first width of the bark thickness removal area to calculate the prediction parameter combination, the influence of the bark thickness on the imaging result can be considered, so that the prediction parameter combination can lose the bark area features in the image and only keep the wood area features, further improving the imaging effect

[0048] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and / or by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0049] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings, in which:

[0050] Figure 1 is a flowchart of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0051] Figure 2 is one of the principle diagrams of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0052] Figure 3 is another of the principle diagrams of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0053] Figure 4 is a third of the principle diagrams of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0054] Figure 5 is a fourth of the principle diagrams of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0055] Figure 6 is a result diagram of the method for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application

[0056] Figure 7 is a structural diagram of the device for selecting X-ray exposure parameters of single trees of different tree species provided by the embodiments of the present application;

[0057] Figure 8 is a structural diagram of the electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0058] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0059] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0060] Below, in combination with the accompanying drawings, the method for selecting X-ray exposure parameters for single trees of different tree species, the device for selecting X-ray exposure parameters for single trees of different tree species, the electronic device and the readable storage medium provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

[0061] The method for selecting X-ray exposure parameters for individual trees of different tree species can be applied to a terminal, and can be specifically executed by hardware or software in the terminal.

[0062] The embodiment of the present application provides a method for selecting X-ray exposure parameters for single trees of different tree species. The execution subject of the method for selecting X-ray exposure parameters for single trees of different tree species can be an electronic device or a functional module or functional entity in the electronic device that can implement the method for selecting X-ray exposure parameters for single trees of different tree species. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras and wearable devices, etc. The method for selecting X-ray exposure parameters for single trees of different tree species provided in the embodiment of the present application is explained below using electronic devices as the execution subject as an example.

[0063] like Figure 1 As shown, the method for selecting X-ray exposure parameters for single trees of different tree species includes: step 110, step 120, step 130 and step 140.

[0064] Step 110: Acquire multiple frames of X-ray images corresponding to the target tree at multiple different drilling depths, collected by the image sensor under multiple sets of different parameter combinations;

[0065] In this step, the target tree may be any tree of any tree species. In some embodiments, a tree with a larger trunk diameter may be selected from any tree species.

[0066] The marking point is a point used for indicating the position of the hole, which can be marked on the diameter direction of the trunk with a marker.

[0067] The lens center of the image sensor is on the same horizontal line as the marking point of the target tree, and the hole depth is obtained by drilling the target tree along the diameter direction of the marking point.

[0068] The hole depth can be between 0 and the diameter of the target tree, and the hole depth of 0 means no drilling, which can be used as an initial state for image acquisition, as shown in Figure 5 .

[0069] With reference to Figure 5 , in some embodiments, the image sensor can be a digital radiography (DR) device, which includes an X-ray generator and a detector. During shooting, the X-ray generator, the diameter direction of the trunk, and the detector should be on the same straight line. The X-ray generator is arranged in front of the trunk of the target tree, and the detector is close to the other side of the trunk.

[0070] The shooting distance is the distance between the X-ray generator and the detector, which can be customized by the user, as long as the shooting distance corresponding to the same target tree is kept the same.

[0071] In some embodiments, the shooting distance can be set to 1.5 m or 2 m, etc.

[0072] The parameter combination includes a plurality of exposure parameters.

[0073] In actual execution, with reference to Figure 5 , the target tree can be first limited, and the diameter of the trunk at a certain height, such as the initial trunk diameter D at a distance of 1.3 m from the ground, is measured, and a marking point is marked at this height. Then, the portable DR device is placed at a distance of 1.3 m from the ground, and the lens center point is directly opposite the diameter direction, i.e., the subsequent drilling direction. The target tree is shot under a certain parameter combination to obtain an X-ray image. Then, the parameter values in the parameter combination are adjusted, and the target tree is shot again to obtain an X-ray image. In this way, all parameter combinations are traversed to obtain a plurality of X-ray images corresponding to the current hole depth.

[0074] Then, the hole depth is changed, and the above steps are repeated to obtain a plurality of X-ray images corresponding to the next hole depth. In this way, a plurality of X-ray images corresponding to a plurality of different hole depths are obtained.

[0075] The imaging effect of the X-ray image is affected by the exposure parameters of the image sensor, and the obtained X-ray image can or can not include the texture features of the trunk, and the width of the included texture features can also be different. The obtained X-ray images under different exposure parameters are as shown in Figure 4

[0076] It can be understood that, in the case of underexposure, although the image area is complete, it can cause image blur and loss of details, thereby affecting the clarity of the X-ray image and failing to meet the image differentiation requirement; and in the case of overexposure, although it has high clarity, it can cause the loss of the edge part of the tree with a thin thickness in the image, that is, it can cause the loss of part of the target area, thereby affecting the completeness of the X-ray image.

[0077] In the case of optimal exposure, the obtained X-ray image has high clarity and high detail completeness, and can be approximately considered to meet the image differentiation requirement.

[0078] In some embodiments, the X-ray image can also include features corresponding to the marker points.

[0079] In some embodiments, the parameter combination can include a tube voltage parameter (unit: kilovolt), a tube current parameter (unit: milliampere), and an exposure time parameter (unit: second), and the parameters of each category are independent of each other and can be adjusted independently.

[0080] According to the different tree species single tree X-ray exposure parameter selection method provided in the embodiments of the present application, by setting each exposure parameter as a parameter that can be adjusted independently, the case of simultaneous change of three variables, i.e., tube voltage, tube current, and exposure time, is involved, the data dimension is higher, and the relationship between the variables is more complex, which can further improve the precision and accuracy of the subsequently determined critical exposure parameter.

[0081] In step 120, based on the imaging effects of the multiple frames of X-ray images acquired by the image sensor under multiple sets of different parameter combinations corresponding to the same drilling depth, a target parameter combination corresponding to the target tree at the same drilling depth is determined.

[0082] In this step, the imaging effect can be judged according to the completeness of the target tree in the X-ray image and whether the marker points can be identified or not. It can be understood that, in the case of underexposure or overexposure, the marker points cannot be displayed in the X-ray image.

[0083] In the actual execution process, the X-ray image can be identified based on an image recognition algorithm to judge the imaging effect.

[0084] ​The target parameter combination is a critical exposure parameter. When the image sensor performs image acquisition based on the target parameter combination, the area of exposure loss can be reduced as much as possible under the premise of meeting the image definition, and the integrity of the X-ray image is improved. When the target parameter combination is exceeded, it is considered that overexposure has occurred. The target parameter combination is one or more sets of exposure parameter combinations that can maintain a balance between image definition and image integrity.

[0085] In some embodiments, the target parameters corresponding to the same target number at the same drilling depth can be one or more.

[0086] For the determination of the critical exposure parameter corresponding to each drilling depth, the method of steps 110 to 120 can be used, which will not be repeated here.

[0087] Step 130, constructing the association relationship between the target parameter combination corresponding to each different target tree and the target thickness, the target thickness being the difference between the initial trunk diameter of each target tree and the drilling depth;

[0088] In this step, the target thickness is the length of the remaining part of the hole diameter after the trunk is drilled, that is, the target thickness is the difference between the initial trunk diameter and the drilling depth, as shown in the following formula: Figure 2

[0089] It can be understood that when the target tree and the initial trunk thickness of the target tree remain unchanged, the drilling depth changes, and the target thickness changes accordingly. The deeper the drilling depth, the thinner the corresponding target thickness. In actual execution, the target thickness can be approximately considered as the trunk thickness corresponding to the acquired X-ray image. The X-ray images corresponding to different drilling depths can be approximately considered as X-ray images of different trunk thicknesses of the same tree species category as the target tree.

[0090] The association relationship is used to represent the association relationship between the tree species category (i.e., the tree category), the trunk diameter, and the critical exposure parameter combination of the image sensor, Figure 6 An example of an association relationship is shown.

[0091] The association relationship is used for the image sensor to acquire X-ray images of trees of the same category as the target tree and having a target thickness.

[0092] In actual execution, for any tree species category, a single tree of the tree species category is selected as the target tree, and the method of steps 110 to 120 is executed, so that the critical exposure parameter of the image sensor corresponding to the target tree at different drilling depths can be obtained.

[0093] ​The difference between the initial trunk diameter of the target tree and each drilling depth is approximated as the trunk thickness of different trees in the same tree species category, so as to obtain the critical exposure parameters of the image sensor corresponding to the different trees with different trunk thicknesses in the same tree species category.

[0094] The above method is performed for each tree species category, so as to obtain the critical exposure parameters of the image sensor corresponding to the different trees with different trunk thicknesses in each tree species category.

[0095] In some embodiments, a linear fitting algorithm can be used to fit the obtained tree species categories, different trunk thicknesses, and critical exposure parameters corresponding to the tree species categories and trunk thicknesses, so as to obtain the correlation therebetween.

[0096] In step 140, the X-ray exposure parameters of the image sensor are determined based on the correlation, the initial trunk diameter of the to-be-measured tree, and the tree species category of the to-be-measured tree, so as to collect the X-ray image of the to-be-measured tree.

[0097] In this step, the to-be-measured tree can be any tree that needs to be subjected to X-ray image collection in research or application processes.

[0098] It can be understood that, in actual application processes, for example, Figure 6 As shown, a plurality of target trees of different categories can be preselected, and the target parameter combinations corresponding to each target tree at different drilling depths are obtained according to the method of steps 110 to 130, so as to obtain the correlation between the tree species, target thickness, and target parameter combinations that can obtain clear and complete X-ray images under the tree species and target thickness; in subsequent application processes, only the initial trunk diameter of the to-be-measured tree and the tree species category of the to-be-measured tree need to be substituted into the obtained correlation, so as to obtain the target parameter combination required for collecting a complete and clear X-ray image of the to-be-measured tree, and then the parameters of the image sensor are adjusted to the determined target parameter combination, and the to-be-measured tree is subjected to image collection to obtain an X-ray image, which can more completely retain the contour features of the to-be-measured tree and clearly present structural details, and has a higher imaging effect.

[0099] In some embodiments, a plurality of target parameter combinations can be obtained according to the correlation, the initial trunk diameter of the to-be-measured tree, and the tree species category of the to-be-measured tree.

[0100] In some embodiments, one target parameter combination can be selected as the X-ray exposure parameters of the image sensor from the plurality of target parameter combinations according to the first input of the user.

[0101] In some embodiments, the target parameter combination that matches the performance parameter of the image sensor can also be screened as the X-ray exposure parameter of the image sensor based on the performance parameter of the image sensor. The actual needs can be flexibly selected.

[0102] The inventors found in the development process that in the related art, there is also a method for determining the critical parameter by continuously shooting X-ray images with different exposure parameter combinations at the same angle, combining the conversion relationship between the pixel width of the exposure loss area and the physical width of the tree, and measuring the corresponding trunk width Wr at the Lr position of the deep trunk using a vernier caliper, to obtain the critical overexposure depth under the exposure parameter. However, this method needs to convert between pixel values and physical values, and needs to measure the thickness of the trunk multiple times, which has a large measurement error, thereby affecting the accuracy of the finally determined exposure parameter, and the steps are more complicated and the measurement efficiency is lower.

[0103] In the present application, the target tree is punched to obtain multiple frames of X-ray images of the target tree corresponding to multiple different punching depths under multiple different parameter combinations collected by the image sensor, the critical exposure parameter corresponding to each punching depth is determined based on the imaging effect of the X-ray image, and then the punching depth is converted into the trunk thickness under the same tree species category to obtain the critical exposure parameter corresponding to each trunk thickness, without the need for calibration and conversion of pixel coordinates and three-dimensional space coordinates. The accurate target parameter combination can be obtained, the operation steps are simplified, the operation is simple and easy to implement, and the processing efficiency is higher.

[0104] In addition, for each tree species category, only one tree needs to be selected to measure the initial trunk diameter of the trunk, and multiple thicknesses of different trunks do not need to be collected, which effectively reduces the sampling error and further improves the accuracy and accuracy of the determined target parameter combination. It is suitable for data collection and exposure parameter determination in a wide range of multiple tree species categories, reduces labor and time costs, improves processing efficiency and detection efficiency, is suitable for field nondestructive testing and large-scale forest surveying, and has high practicality.

[0105] The hole diameter is small when the hole is punched by the electric drill, and the impact on the tree body can be ignored. After the punching and shooting of the target tree are completed, the hole can be filled to protect the tree body, so that the target parameter combination can be determined efficiently, conveniently and at low cost without affecting the tree body, and the determined target parameter combination has high precision and accuracy.

[0106] On this basis, according to the constructed correlation, in the subsequent application process, the exposure parameters can be automatically obtained and adjusted based on the correlation according to different tree species and their trunk diameter characteristics, efficient, clear and accurate image acquisition of the internal structure of the trunk is realized, the best X-ray image for the single tree to be measured is intelligently obtained, different tree species are considered comprehensively, the wood structure density and water content of different tree species are different, and the absorption capacity of X-rays is significantly different; and the diameter of the trunk changes in a large range, which directly affects the imaging penetration depth and image quality and other factors affecting the imaging effect, has high precision, helps to improve the imaging effect, has self-adaptability and imaging stability on the premise of retaining the complete and clear image area of the trunk as much as possible, provides reliable nondestructive testing means and data support for forestry resource investigation, tree health monitoring and related scientific research, and can meet the needs of modern forestry informatization and fine management.

[0107] According to the different tree species single tree X-ray exposure parameter selection method provided in the embodiment of the application, the target tree is punched to obtain a plurality of frames of X-ray images of the target tree corresponding to a plurality of different punching depths collected by the image sensor under a plurality of different parameter combinations, the critical exposure parameters corresponding to each punching depth are determined based on the imaging effect of the X-ray images, and then the punching depth is converted into the trunk thickness under the same tree species category, to obtain the critical exposure parameters corresponding to each trunk thickness. The operation is simple and easy to implement, and the cost is low; without affecting the tree body, the sampling error can be effectively reduced, the accuracy and accuracy of the determined target parameter combination can be improved, so that the imaging quality is maintained while effectively avoiding the problems caused by underexposure or overexposure, the internal structure of the tree can be accurately, clearly and efficiently collected on the premise of maximizing the retention of the complete area of the trunk, and the method has a wide application scenario, high universality, stability and practicality, and is suitable for field nondestructive testing and large-scale forest survey.

[0108] In some embodiments, step 110 can include:

[0109] Obtaining an X-ray image of the target tree corresponding to the same punching depth collected by the image sensor under the initial parameter combination;

[0110] Adjusting the parameters of the target category in the initial parameter combination along the target adjustment direction and the target adjustment step, and keeping the parameters of other categories unchanged, reobtaining the X-ray image of the target tree corresponding to the same punching depth collected by the image sensor under the adjusted initial parameter combination.

[0111] In this embodiment, the target adjustment direction is the adjustment direction corresponding to the size of the parameter, such as sequentially increasing or sequentially decreasing.

[0112] In some embodiments, the target adjustment direction can be determined according to the initial trunk diameter of the target tree, and in a case where the initial trunk diameter is greater than a preset diameter, the target adjustment direction is set to gradually decrease; and in a case where the initial trunk diameter is less than or equal to the preset diameter, the target adjustment direction is set to gradually increase.

[0113] The target adjustment step is a difference between a numerical value of a parameter of the target category and a numerical value of the parameter before adjustment, which can be customized by a user, and the target adjustment step can be a fixed step or a variable step, which is not limited in the present application.

[0114] The initial parameter combination includes initial values of multiple categories of parameters, and the initial values are set according to the target adjustment direction, for example, the initial values are set to larger values when the target adjustment direction is gradually decreasing, and the initial values are set to smaller values when the target adjustment direction is gradually increasing.

[0115] The target category can be any category of the included parameter categories.

[0116] Taking an example in which the initial parameter combination includes a tube voltage parameter, a tube current parameter and an exposure time parameter, first, two categories of parameters are fixed, the third category of parameter is changed to gradually increase, and at each numerical value corresponding to the third category of parameter, an X-ray image is collected by the image sensor until a preset condition is reached, and the collection is stopped.

[0117] The preset condition can be customized by a user, for example, a maximum adjustment number is set, and when the adjustment number reaches the maximum adjustment number, the preset condition is considered to be reached; or a target range corresponding to each category of parameter can be set, and when the numerical value of the adjusted parameter exceeds the target range, the preset condition is considered to be reached.

[0118] In some embodiments, step 110 can include:

[0119] The multiple frames of X-ray images of the target tree corresponding to the initial drilling depth under the multiple sets of different parameter combinations are collected by the image sensor.

[0120] The initial drilling depth is adjusted, and the multiple frames of X-ray images of the target tree corresponding to the adjusted initial drilling depth under the multiple sets of different parameter combinations are collected by the image sensor.

[0121] In this embodiment, the initial drilling depth can be customized by a user, for example, the initial drilling depth is set to 0, that is, without drilling, the exposure parameters of the image sensor are adjusted, and the multiple frames of X-ray images under the multiple sets of different parameter combinations are collected, and the specific adjustment parameter combination has been described in the above embodiments, and is not repeated here.

[0122] After all the X-ray images under the initial drilling depth are collected, the initial drilling depth is adjusted, for example, the initial drilling depth is adjusted along the diameter direction of the target tree trunk where the marker point is located, and the image sensor is kept fixed. Then, the target tree trunk is photographed under the current drilling depth according to the parameter combinations under the initial drilling depth, and a plurality of X-ray images corresponding to the plurality of different parameter combinations under the current drilling depth are obtained.

[0123] In some embodiments, adjusting the initial drilling depth can include drilling the target tree along the diameter direction of the target tree trunk where the marker point is located based on a first step length.

[0124] In this embodiment, the drilling direction should be kept the same each time.

[0125] The first step length is the distance by which the current drilling depth is advanced relative to the last drilling depth, which can be customized by the user and can be set to a small length, such as 0.1 times or 0.2 times the initial trunk diameter of the target tree, which is not limited in the present application.

[0126] In some embodiments, step 120 can include:

[0127] The plurality of X-ray images corresponding to the same drilling depth are identified based on an adjustment sequence, and the adjustment sequence is the sequence in which the parameters of the target category in the parameter combination are adjusted during image collection.

[0128] In the first identification of the case where the marker point is not displayed in the X-ray image, the parameter combination corresponding to the previous X-ray image of the X-ray image is determined as the target parameter combination corresponding to the same drilling depth.

[0129] In this embodiment, the adjustment sequence is the sequence in which the parameters of the target category in the parameter combination are adjusted, for example, the parameters are sequentially increased.

[0130] Taking the parameter combination including the tube voltage parameter, the tube current parameter, and the exposure time parameter as an example, in actual execution, first, two exposure parameters are fixed, for example, the values of the tube current and the exposure time are kept constant, the third exposure parameter is changed, the tube voltage is gradually increased from 0 by a target adjustment step, the X-ray image collected by the image sensor under each tube voltage is obtained, the marker point in the X-ray image is identified according to the image recognition algorithm, and if the marker point in the X-ray image is detected to have just disappeared, the previous parameter combination can be determined as the target parameter combination corresponding to the drilling depth, that is, the critical exposure parameter combination under the target thickness corresponding to the drilling depth.

[0131] The hole depth is deepened step by step according to the depth gradient of the first step length, and the above steps are repeated, so that the target parameter combination corresponding to each punching depth is obtained, and the critical exposure parameters corresponding to different trunk thicknesses are obtained.

[0132] In some embodiments, step 120 can include:

[0133] In the case of adjusting the parameters of the target category in the initial parameter combination along the target adjustment direction and the target adjustment step length, and keeping the parameters of other categories unchanged, based on the imaging effect of the collected multiple X-ray images, the optimal value of the parameters of the target category corresponding to the first values of the parameters of other categories is determined, and the first values of the parameters of other categories and the optimal value of the parameters of the target category are determined as a set of target parameter combinations.

[0134] The value of the parameters of the first category in the other categories is adjusted to the second value, the values of the parameters of the remaining categories in the other categories are kept unchanged, the parameters of the target category are adjusted along the target adjustment direction and the target adjustment step length, and based on the imaging effect of the collected multiple X-ray images, the optimal value of the parameters of the target category corresponding to the second value of the parameters of the first category and the first value of the parameters of the remaining categories is determined, and the second value of the parameters of the first category and the first value of the parameters of the remaining categories and the optimal value of the parameters of the target category are determined as a set of target parameter combinations.

[0135] In this embodiment, taking the initial parameter combination including the tube voltage parameter, the tube current parameter and the exposure time parameter as an example, the exposure time parameter can be determined as the target category parameter, and the tube voltage parameter and the tube current parameter can be determined as the other category parameters. In the adjustment process, the tube voltage parameter and the tube current parameter are set to fixed values, such as setting the tube voltage parameter to a1 and the tube current parameter to b1, and then the exposure time parameter is adjusted along the target adjustment direction and the target adjustment step length to obtain multiple parameter combinations: (a1, b1, c1), (a1, b1, c2), …, (a1, b1, cn), where c1, c2, …, cn are the values of the exposure time parameter, and n is a positive integer corresponding to the number of adjustments.

[0136] The X-ray images collected by the image sensor under the above various parameter combinations are obtained, and a set of target parameter combinations is selected according to the imaging effect, such as (a1, b1, c1). The target parameter combination is the critical exposure parameter corresponding to the exposure time parameter when the tube voltage parameter is a1 and the tube current parameter is b1.

[0137] Keeping the drilling depth unchanged, the tube voltage parameter is determined as the first type of parameter, and the tube current parameter is the remaining type of parameter. The value of the first type of parameter is adjusted and fixed on the basis of the previous round, such as adjusting the tube voltage parameter from a1 to a2, keeping the value of the tube current parameter unchanged as in the previous round, and then adjusting the exposure time parameter along the target adjustment direction and the target adjustment step to obtain a plurality of parameter combinations: (a2, b1, c1), (a2, b1, c2), …, (a2, b1, cn).

[0138] The X-ray images collected by the image sensor under each of the above parameter combinations are obtained, and a target parameter combination is selected according to the imaging effect, such as (a2, b1, c3). The target parameter combination is the critical exposure parameter corresponding to the exposure time parameter under the condition that the tube voltage parameter is a2 and the tube current parameter is b1.

[0139] The tube voltage parameter is continuously adjusted, and the above process is repeated until the tube voltage parameter cannot be continuously adjusted, so as to obtain a plurality of target parameter combinations corresponding to the tube current parameter b1.

[0140] Then the value of the remaining type of parameter is adjusted and fixed, such as adjusting the tube current parameter from b1 to b2, repeating the above steps, and obtaining a plurality of target parameter combinations corresponding to the tube current parameter b2.

[0141] By analogy, a plurality of target parameter combinations corresponding to the same target tree under the same drilling depth can be listed.

[0142] Then the drilling depth is changed, and the above steps are continuously repeated, so as to list a plurality of target parameter combinations corresponding to the same target tree under a plurality of drilling depths, wherein each drilling depth corresponds to at least one target parameter combination. In some embodiments, step 120 can include:

[0143] Obtaining a plurality of X-ray images of other trees of the same tree species as the target tree under a plurality of drilling depths and a plurality of different parameter combinations;

[0144] Based on the imaging effect of the plurality of X-ray images corresponding to each tree under the same target thickness, the target parameter combination corresponding to each tree under the same target thickness is determined;

[0145] Based on the average value of the target parameter combinations corresponding to each tree under the same target thickness, the target parameter combination corresponding to the target tree under the same target thickness is determined.

[0146] In this embodiment, in each tree species category, multiple trees can be selected for testing to obtain critical exposure parameters under different tree thickness (i.e. target thickness) conditions, so that the interval of tree thickness can cover the whole forest of the same tree species category.

[0147] At the same time, the critical exposure parameters obtained under the same tree species category and the same tree thickness are added and averaged, and the average value is taken as the critical overexposure parameter corresponding to each tree species category under the corresponding tree thickness. The exposure dose characteristics of the tree species category and different part thicknesses are provided.

[0148] According to the single-tree X-ray exposure parameter selection method for different tree species provided in the embodiments of the present application, the target parameter combination is calculated by multiple sampling and averaging, which further improves the accuracy of the determined critical exposure parameter.

[0149] In some embodiments, step 130 can include:

[0150] Taking the tree species category and the target thickness corresponding to the multiple target trees as samples, and taking the target parameter combination as a sample label, a training sample is constructed;

[0151] The multiple training samples are input into the network model, and the network model outputs a predicted parameter combination as a target training network model to learn the correlation.

[0152] In this embodiment, the network model can be a deep learning model or a neural network model, such as a CNN model or a Transformer model, which is not limited in the present application.

[0153] In the training process, with reference to Figure 6 , the input data of the network model includes the tree species category (S), the target thickness (T), the tube voltage (TV), the tube current (TC), and the exposure time (ET), and the output data is the critical exposure parameter combination corresponding to the predicted tree species category and the target thickness.

[0154] By training the network model, the complex relationship between different exposure parameters and tree features is learned, and then the most suitable exposure parameter combination (TV, TC, ET) under the conditions of tree species and target thickness (T) is provided. In the subsequent application process, only the tree species category of the tree to be tested and the tree trunk thickness (such as the trunk diameter) corresponding to the tree to be tested need to be input, and the critical exposure parameter combination predicted by the network model can be obtained.

[0155] In actual execution, the target parameter combinations corresponding to the trees of different tree species categories at different target thicknesses can be obtained through steps 110-120, and these data are paired to obtain a plurality of training samples. The training samples are divided into a training set, a validation set and a test set according to a ratio of 7:1:2 or 8:1:1. The network model is trained by the training set, and verified and tested by the validation set and the test set, until the difference between the predicted parameter combination obtained by the network model and the input target parameter combination is not less than a target threshold, such as not less than 85% or 90%.

[0156] According to the different tree species single tree X-ray exposure parameter selection method provided in the embodiments of the present application, the deep learning algorithm is used to learn the correlation between the target parameter combination and the target thickness, which can learn the relationship between the exposure parameters and the tree features of more complex dimensions, thereby improving the accuracy and precision of the exposure parameters calculated according to the tree species category and the trunk thickness, further improving the imaging effect, and being simple and convenient to operate and high in calculation efficiency.

[0157] In some embodiments, step 140 can include:

[0158] determining a first width based on the bark thickness of the single tree to be measured;

[0159] determining a predicted parameter combination corresponding to the single tree to be measured based on the first width, the tree species category of the single tree to be measured, and the correlation between the target parameter combination and the target thickness;

[0160] adjusting the X-ray exposure parameters of the image sensor based on the predicted parameter combination to acquire an X-ray image of the single tree to be measured.

[0161] In this embodiment, as shown in Figure 3 the trunk includes a bark region and a wood region. In actual shooting, the X-ray image of the wood region is mainly shot.

[0162] The first width is the distance between the intersection of the tangent of the outer periphery of the wood region after removing the bark thickness L of the bark region of the trunk diameter and the outer periphery of the trunk, as shown in Figure 3 WL, which can be approximately considered as the thickness of the wood region.

[0163] The predicted parameter combination calculated by the first width, the tree species category of the single tree to be measured, and the correlation between the target parameter combination and the target thickness can be approximately considered as the best exposure parameter combination under the tree species category and the trunk thickness.

[0164] The predicted parameter combination can be one or more combinations, and any one of them can be selected as the optimal exposure parameter according to the actual situation.

[0165] Taking the network model as an example, after the network model is trained, the first width (WL) corresponding to the tree species category (S) and the bark thickness is taken as input and is transmitted to the network model M, and the network model M outputs the corresponding optimal exposure parameter combination (TV, TC, ET).

[0166] It can be understood that the thicker the tree is, the thicker the bark is relatively, but the bark part is not the detection target and can be lost. Generally, after the exposure dose is adjusted to be sufficient to lose the bark area, a clear image can be captured. By replacing the stem thickness with the first width to calculate the predicted parameter combination, the influence of the bark thickness on the X-ray imaging quality can be considered, the bark area is lost in the image, irrelevant features in the image are reduced, and the inventors have verified through multiple experiments that the X-ray image captured after the exposure dose is adjusted to be sufficient to lose the bark area is clear and complete, thereby further improving the imaging quality of the collected X-ray image.

[0167] The inventors have found in the research and development process that in the related art, there is also a method of taking the tree width at the depth of 5% and 1% of the stem diameter as the upper limit and lower limit of the X-ray optimal exposure depth, and the upper limit and lower limit of the X-ray exposure dose, respectively, but this method does not have universality and affects the accuracy.

[0168] In the present application, by losing the bark area in the image (since there can be a certain density difference between the phloem and the xylem, the lost area can be slightly larger than the bark area, but this loss is acceptable), the decline in imaging quality can be effectively avoided; in addition, by predicting the critical parameter combination through the tree species category and the width of the xylem area, the optimal exposure parameter value under the condition of reducing the influence of the bark area can be adaptively predicted according to the bark thickness corresponding to different trees, the accuracy of the obtained parameter combination is further improved, thereby improving the imaging effect and having universality.

[0169] According to the different tree species single tree X-ray exposure parameter selection method provided in the embodiments of the present application, the first width of the removed bark area thickness is used to replace the stem thickness to calculate the predicted parameter combination, the influence of the bark thickness on the imaging result can be considered, so that the predicted parameter combination can lose the bark area feature in the image and only retain the xylem area feature, thereby further improving the imaging effect.

[0170] The different tree species single tree X-ray exposure parameter selection method provided in the embodiments of the present application can be executed by a different tree species single tree X-ray exposure parameter selection device. In the embodiments of the present application, the different tree species single tree X-ray exposure parameter selection method is executed by a different tree species single tree X-ray exposure parameter selection device as an example to illustrate the different tree species single tree X-ray exposure parameter selection device provided in the embodiments of the present application.

[0171] The embodiment of the present application also provides a device for selecting X-ray exposure parameters for single trees of different tree species.

[0172] like Figure 7 As shown, the device for selecting X-ray exposure parameters for single trees of different tree species includes: a first processing module 710 , a second processing module 720 , a third processing module 730 and a fourth processing module 740 .

[0173] The first processing module 710 is configured to obtain multiple frames of X-ray images corresponding to a target tree at multiple different drilling depths, acquired by an image sensor under multiple different parameter combinations; the center of the image sensor lens and the target tree's marking point are co-level, and the drilling depth is obtained by drilling the target tree along the diameter of the marking point;

[0174] The second processing module 720 is configured to determine a target parameter combination corresponding to the same drilling depth of the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple sets of different parameter combinations corresponding to the same drilling depth;

[0175] The third processing module 730 is used to establish a correlation between the target parameter combination corresponding to each target tree and the target thickness, where the target thickness is the difference between the initial trunk diameter of each target tree and the drilling depth;

[0176] The fourth processing module 740 is configured to determine X-ray exposure parameters of the image sensor to acquire an X-ray image of the tree to be measured based on the association relationship, the initial trunk diameter of the tree to be measured, and the tree species of the tree to be measured.

[0177] According to the device for selecting X-ray exposure parameters for single trees of different tree species provided in the embodiment of the present application, a target tree is drilled to obtain multiple frames of X-ray images corresponding to the target tree at multiple different drilling depths, which are collected by the image sensor under multiple groups of different parameter combinations. The critical exposure parameters corresponding to each drilling depth are determined based on the imaging effect of the X-ray image, and then the drilling depth is converted into the trunk thickness under the same tree species category to obtain the critical exposure parameters corresponding to each trunk thickness. The operation is simple, easy to implement and low in cost. Without affecting the tree body, the sampling error can be effectively reduced, and the precision and accuracy of the determined target parameter combination can be improved, thereby effectively avoiding the problems caused by underexposure or overexposure while maintaining the imaging quality, so that in the process of tree research, the internal structure of the tree can be accurately, clearly and efficiently collected while maximizing the retention of the intact area of ​​the trunk. It has a wide range of application scenarios, high universality and stability.

[0178] In some embodiments, the first processing module 710 may also be used to:

[0179] acquire the X-ray image corresponding to the target tree at the same drilling depth under the initial parameter combination;

[0180] adjust the parameters of the target category in the initial parameter combination along the target adjustment direction and the target adjustment step length, keep the parameters of other categories unchanged, and reacquire the X-ray image corresponding to the target tree at the same drilling depth under the adjusted initial parameter combination.

[0181] In some embodiments, the first processing module 710 can be further configured to:

[0182] acquire a plurality of X-ray images corresponding to the target tree at the initial drilling depth under a plurality of different parameter combinations;

[0183] adjust the initial drilling depth, and acquire a plurality of X-ray images corresponding to the target tree at the adjusted initial drilling depth under a plurality of different parameter combinations.

[0184] In some embodiments, the second processing module 720 can be further configured to:

[0185] perform image recognition on the plurality of X-ray images corresponding to the same drilling depth based on an adjustment sequence; the adjustment sequence is the sequence for adjusting the parameters of the target category in the parameter combination during image acquisition;

[0186] In the case where the marker point is not displayed in the X-ray image for the first time, the parameter combination corresponding to the previous X-ray image of the X-ray image is determined as the target parameter combination corresponding to the same drilling depth.

[0187] In some embodiments, the second processing module 720 can be further configured to:

[0188] In the case where the parameters of the target category in the initial parameter combination are adjusted along the target adjustment direction and the target adjustment step length, and the parameters of other categories remain unchanged, the optimal values of the parameters of the target category corresponding to the first values of the parameters of other categories are determined based on the imaging effect of the acquired plurality of X-ray images, and the first values of the parameters of other categories and the optimal values of the parameters of the target category are determined as a set of target parameter combinations;

[0189] adjusting a value of a parameter in a first category of parameters in the other categories of parameters to a second value, keeping values of parameters in remaining categories of parameters in the other categories of parameters unchanged, adjusting the parameter in the target category along the target adjustment direction and the target adjustment step, determining, based on imaging effects of the plurality of frames of X-ray images, a best value of the parameter in the target category corresponding to the first category of parameters being the second value and the remaining categories of parameters being the first value, and determining the first category of parameters being the second value, the remaining categories of parameters being the first value, and the parameter in the target category being the best value corresponding to a target parameter combination.

[0190] In some embodiments, the second processing module 720 can be further configured to:

[0191] obtain a plurality of other trees of a same tree species category as the target tree, corresponding to a plurality of frames of X-ray images at a plurality of drilling depths and a plurality of different parameter combinations;

[0192] determine, based on imaging effects of the plurality of frames of X-ray images corresponding to a same target thickness, a target parameter combination corresponding to each of the plurality of other trees at the same target thickness;

[0193] determine, based on an average of the target parameter combinations corresponding to the plurality of other trees at the same target thickness, a target parameter combination corresponding to the target tree at the same target thickness.

[0194] In some embodiments, the third processing module 730 can be further configured to:

[0195] construct training samples by taking the tree species categories and the target thicknesses corresponding to the plurality of target trees as samples and taking the target parameter combinations as sample labels;

[0196] input the plurality of training samples into a network model, and output, by the network model, a predicted parameter combination as a target training network model to learn a correlation.

[0197] In some embodiments, the fourth processing module can be further configured to:

[0198] determine the first width based on the bark thickness of the to-be-tested single tree;

[0199] determine, based on the first width, the tree species category of the to-be-tested single tree, and a correlation between the target parameter combination and the target thickness, a predicted parameter combination corresponding to the to-be-tested single tree;

[0200] adjust X-ray exposure parameters of the image sensor based on the predicted parameter combination to capture an X-ray image of the to-be-tested single tree.

[0201] The different tree species single tree X-ray exposure parameter selection device in the embodiments of the present applicationapplicationbe an electronic device, or a component in an electronic device, such as an integrated circuit or a chip. The electronic deviceapplicationbe a terminal or another device other than a terminal. For example, the electronic deviceapplicationbe a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted electronic device, a Mobile Internet Device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), andapplicationbe a server, a Network Attached Storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, and the like. The embodiments of the present application do not make a specific limitation.

[0202] The different tree species single tree X-ray exposure parameter selection device in the embodiments of the present applicationapplicationbe a device having an operating system. The operating systemapplicationbe an Android operating system, an IOS operating system, or another possible operating system, and the embodiments of the present application do not make a specific limitation.

[0203] The different tree species single tree X-ray exposure parameter selection device provided in the embodiments of the present applicationapplicationbe capable of implementing the method embodiments Figures 1 to 6 The processes implemented by the method embodimentsapplicationbe described above, and thus are not described herein again to avoid repetition.

[0204] In some embodiments, as shown in Figure 8 The embodiments of the present application also provide an electronic device 800, whichapplicationinclude a processor 801, a memory 802, and a computer program stored in the memory 802 and capable of running on the processor 801. The programapplicationbe executed by the processor 801 to implement the processes of the above different tree species single tree X-ray exposure parameter selection method embodiments, and achieve the same technical effects. The processesapplicationnot be described herein again to avoid repetition.

[0205] It should be noted that the electronic device in the embodiments of the present applicationapplicationinclude the above-mentioned mobile electronic device and non-mobile electronic device.

[0206] The embodiment of the present application further provides a non-transitory computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement each process of the different tree species single tree X-ray exposure parameter selection method embodiment and achieve the same technical effects. To avoid repetition, details are not described herein.

[0207] The processor is the processor in the electronic device in the above embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0208] The embodiment of the present application further provides a computer program product, which includes a computer program. The computer program is executed by a processor to implement the different tree species single tree X-ray exposure parameter selection method.

[0209] The processor is the processor in the electronic device in the above embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0210] The embodiment of the present application further provides a chip, which includes a processor and a communication interface. The communication interface is coupled with the processor. The processor is used to run a program or an instruction to implement each process of the different tree species single tree X-ray exposure parameter selection method embodiment and achieve the same technical effects. To avoid repetition, details are not described herein.

[0211] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system level chip, a system chip, a chip system or a system on chip, etc.

[0212] It should be noted that, in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus including the element. In addition, it should be pointed out that the scope of the method and apparatus in the present application is not limited to the order of functions shown or discussed, but can also include functions performed in a substantially simultaneous manner or in reverse order, for example, the described method can be performed in an order different from that described, and various steps can be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0213] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned example methods can be realized by means of software and necessary general hardware platforms, and of course, they can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer software product in essence or in the form of a part of the prior art that contributes to the present application. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disc, an optical disc), and includes a plurality of instructions for causing a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0214] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative and not restrictive. Those skilled in the art can make many forms under the inspiration of the present application without departing from the scope of the present application and the scope of protection of the claims.

[0215] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an illustrative embodiment", "an example", "a specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0216] Although the embodiments of the present application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and purposes of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for selecting X-ray exposure parameters for single trees of different tree species, characterized in that: include: Acquire multiple frames of X-ray images corresponding to target trees at multiple different drilling depths, collected by an image sensor under multiple sets of different parameter combinations; The center of the lens of the image sensor and the mark point of the target tree are on the same horizontal line, and the drilling depth is obtained by drilling the target tree along the diameter direction where the mark point is located; Determining a target parameter combination corresponding to the same drilling depth for the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple sets of different parameter combinations at the same drilling depth; Establishing a correlation between target parameter combinations and target thicknesses corresponding to different target trees, wherein the target thickness is the difference between the initial trunk diameter of each target tree and the drilling depth; Determining, based on the association relationship, the initial trunk diameter of the single tree to be measured, and the tree species category of the single tree to be measured, an X-ray exposure parameter of the image sensor to acquire an X-ray image of the single tree to be measured; The determining, based on the association relationship, the initial trunk diameter of the single tree to be measured, and the tree species category of the single tree to be measured, an X-ray exposure parameter of the image sensor to acquire an X-ray image of the single tree to be measured includes: Determining a first width based on the bark thickness of the single tree to be tested; The tree species category and the first width corresponding to the bark thickness are used as inputs and passed to a network model, and the network model outputs a corresponding prediction parameter combination; adjusting X-ray exposure parameters of the image sensor based on the predicted parameter combination to acquire an X-ray image of the single tree to be measured; The first width is the distance between the intersection of the outer tangent line of the xylem area and the outer periphery of the trunk after removing the bark thickness of the bark area from the initial trunk diameter.

2. The method for selecting X-ray exposure parameters for single trees of different tree species according to claim 1, characterized in that: The acquisition of multiple frames of X-ray images corresponding to target trees at multiple different drilling depths, acquired by the image sensor under multiple sets of different parameter combinations, includes: Acquire an X-ray image of the target tree at the same drilling depth, acquired by the image sensor under the initial parameter combination; The parameters of the target category in the initial parameter combination are adjusted along the target adjustment direction and the target adjustment step size, while the parameters of other categories remain unchanged, and the X-ray image corresponding to the target tree at the same drilling depth, which is collected by the image sensor under the adjusted initial parameter combination, is reacquired.

3. The method for selecting X-ray exposure parameters for single trees of different tree species according to claim 1, characterized in that: The acquisition of multiple frames of X-ray images corresponding to target trees at multiple different drilling depths, acquired by the image sensor under multiple sets of different parameter combinations, includes: Acquiring multiple frames of X-ray images corresponding to the target tree at the initial drilling depth, which are collected by the image sensor under multiple sets of different parameter combinations; The initial drilling depth is adjusted, and multiple frames of X-ray images corresponding to the target tree at the adjusted initial drilling depth are acquired by the image sensor under multiple groups of different parameter combinations.

4. The method for selecting X-ray exposure parameters for single trees of different tree species according to any one of claims 1 to 3, characterized in that: The determining of the target parameter combination corresponding to the same drilling depth of the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple groups of different parameter combinations at the same drilling depth includes: Performing image recognition on multiple frames of X-ray images corresponding to the same drilling depth based on an adjustment sequence; the adjustment sequence is the sequence for adjusting the parameters of the target category in the parameter combination during the image acquisition process; When it is recognized for the first time that the marking point is not displayed in the X-ray image, the parameter combination corresponding to the previous frame of the X-ray image is determined as the target parameter combination corresponding to the same drilling depth.

5. The method for selecting X-ray exposure parameters for single trees of different tree species according to any one of claims 1 to 3, characterized in that: The determining of the target parameter combination corresponding to the same drilling depth of the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple groups of different parameter combinations at the same drilling depth includes: Acquire multiple frames of X-ray images corresponding to multiple other trees of the same species as the target tree at multiple drilling depths and multiple sets of different parameter combinations; Determining target parameter combinations corresponding to the trees at the same target thickness based on imaging effects of multiple frames of X-ray images corresponding to the trees at the same target thickness; The target parameter combination corresponding to the target tree at the same target thickness is determined based on an average value of the target parameter combination corresponding to each of the trees at the same target thickness.

6. The method for selecting X-ray exposure parameters for single trees of different tree species according to any one of claims 1 to 3, characterized in that: The determining of the target parameter combination corresponding to the same drilling depth of the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple groups of different parameter combinations at the same drilling depth includes: While adjusting the parameters of the target category in the initial parameter combination along the target adjustment direction and the target adjustment step size, and maintaining the first values ​​of the parameters of the other categories unchanged, determining, based on imaging effects of multiple frames of acquired X-ray images, the optimal values ​​of the parameters of the target category corresponding to the first values ​​of the parameters of the other categories, and determining the first values ​​corresponding to the parameters of the other categories and the optimal values ​​corresponding to the parameters of the target category as a set of target parameter combinations; Adjust the values ​​of the parameters of the first category among the parameters of other categories to the second values, keep the values ​​of the parameters of the remaining categories among the parameters of other categories unchanged at the first values, adjust the parameters of the target category along the target adjustment direction and the target adjustment step, and determine, based on the imaging effect of the collected multiple frames of X-ray images, the optimal values ​​of the parameters of the target category corresponding to the first values ​​when the parameters of the first category are the second values ​​and the values ​​of the parameters of the remaining categories are the first values, and determine the optimal values ​​corresponding to the parameters of the target category when the parameters of the first category are the second values, the values ​​of the parameters of the remaining categories are the first values, and the parameters of the target category as a set of target parameter combinations.

7. The method for selecting X-ray exposure parameters for single trees of different tree species according to any one of claims 1 to 3, characterized in that: The construction of the correlation between the target parameter combinations corresponding to different target trees and the target thickness includes: Taking the tree species categories and the target thickness corresponding to the plurality of target trees as samples and the target parameter combination as sample labels, a training sample is constructed; Input a plurality of the training samples into the network model, train the network model with the output prediction parameter combination of the network model as a target, and learn the association relationship.

8. The method for selecting X-ray exposure parameters for single trees of different tree species according to any one of claims 1 to 3, characterized in that: The parameter combination includes tube voltage parameters, tube current parameters and exposure time parameters, and the parameters of each category are independent of each other.

9. A device for selecting X-ray exposure parameters for single trees of different tree species, characterized in that: include: A first processing module is configured to obtain multiple frames of X-ray images corresponding to a target tree at multiple different drilling depths, acquired by an image sensor under multiple different parameter combinations; the center of the image sensor lens and the marking point of the target tree are co-horizontally aligned, and the drilling depths are obtained by drilling the target tree along the diameter of the marking point; a second processing module configured to determine a target parameter combination corresponding to the same drilling depth of the target tree based on imaging effects of multiple frames of X-ray images acquired by the image sensor under multiple sets of different parameter combinations corresponding to the same drilling depth; A third processing module is configured to establish a correlation between target parameter combinations corresponding to different target trees and target thicknesses, wherein the target thickness is the difference between the initial trunk diameter of each target tree and the drilling depth; a fourth processing module, configured to determine, based on the association relationship, the initial trunk diameter of the single tree to be measured, and the tree species category of the single tree to be measured, an X-ray exposure parameter of the image sensor to acquire an X-ray image of the single tree to be measured; The fourth processing module is configured to: Determining a first width based on the bark thickness of the single tree to be tested; The tree species category and the first width corresponding to the bark thickness are used as inputs and passed to a network model, and the network model outputs a corresponding prediction parameter combination; adjusting X-ray exposure parameters of the image sensor based on the predicted parameter combination to acquire an X-ray image of the single tree to be measured; The first width is the distance between the intersection of the outer tangent line of the xylem area and the outer periphery of the trunk after removing the bark thickness of the bark area from the initial trunk diameter.

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