A method and system for measuring biological parameters of flying insects

Abstract

The present invention provides a method and system for measuring biological parameters of flying insects. The method comprises the following steps: 1: suspending the measured insect at a designated position within a measurement box via an insect fixing assembly; 2: synchronously capturing flight images of the measured insect using cameras I and II; and 3: calculating parameters of the measured insect based on the flight images using an industrial computer. The present invention relates to the field of insect parameter measurement technology and is capable of simultaneously measuring multiple parameters, including insect wingbeat frequency, body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective flight wing area. The system can meet the needs of various insect measurements and is suitable for large-scale data measurement. The system also features a simple measurement process, short measurement time, minimal human error, low requirements for the measurement environment, high measurement efficiency, and high measurement accuracy. The measurement device has a simple structure and is easy to maintain, resulting in the beneficial effect of improving the quality of insect parameter databases.

Description

Technical Field

[0001] The present invention relates to the technical field of insect parameter measurement, and in particular to a method and system for measuring biological parameters of flying insects. Background Art

[0002] Insect parameters such as wingbeat frequency, body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective wing area are key parameters for assessing insect flight ability, ecological adaptability, and behavioral habits. Accurately measuring these parameters is crucial for insect biology research, ecological monitoring, and biomimetics applications. It is also crucial for building a high-quality insect parameter database required for insect radar identification technology.

[0003] At present, some methods for measuring insect parameters need to rely on manual measurement. The measurement results of these parameters are easily affected by human errors, making it difficult to provide high-precision and high-repeatability measurement results. At the same time, there are some measuring devices in the prior art for measuring insect physical signs and flight parameters, such as high-speed cameras, stroboscopes, infrared speed meters, etc. that can measure the frequency of insect wingbeats, and high-precision digital vernier calipers that can measure the body length, body width, forewing length, forewing width, hindwing length, and hindwing width of insects. However, these devices usually focus on one or several insect parameters and it is difficult to measure more parameters at the same time. In addition, there is currently no better method for measuring the effective flight wing area of ​​insects; and either they have high requirements for the measurement environment and the species of insects being measured, making them unsuitable for large-scale data measurement; or the measurement process is cumbersome and complicated, with large human errors.

[0004] Chinese utility model application number 202221476261.7 discloses a device for measuring the size of lepidopteran insects, comprising a base and a sliding module. The base is a transparent module that is narrow at the top and wide at the bottom, and the transparent module is made of PVC. A millimeter ruler is engraved on the front and side of the transparent module. The sliding module is two independent transparent modules, and the transparent modules are made of PVC. A slidable embedded base pulley is provided between the two independent transparent modules. The base and the sliding module are connected by an embedded base pulley. The utility model has the advantages of simple structure, convenient operation, accurate measurement, and applicability to a wide variety of insect species. However, the utility model can only measure the length, width, and height of the insect body, and cannot meet the scenario of measuring multiple insect parameters at the same time. It can only measure the size of lepidopteran insects and is not suitable for large-scale data measurement.

[0005] The Chinese invention patent application number 202211158588.4 discloses a device for measuring the frequency of insect wingbeats, which includes a test box, an insect fixing component, and a wingbeat frequency measurement component. The insect fixing component is arranged in the test box, and is used to fix the insect at a fixed position in the test box without affecting the normal wingbeat behavior of the insect; the wingbeat frequency measurement component includes a photoelectric sensor, which is arranged on the upper wall of the test box, and the light beam emitted by the photoelectric sensor is projected onto the insect's forewings when the insect's wings are spread, and is projected onto the lower wall of the test box when the insect's wings are raised. The invention has the advantages of a simple device structure, easy maintenance, and low cost; accurate test results; simple and convenient operation, short test time, and high efficiency. However, the device can only measure the frequency of insect wingbeats, and cannot meet the scenario of measuring multiple insect parameters at the same time. Summary of the Invention

[0006] To solve at least one of the above technical problems, the present invention provides a method and system for measuring biological parameters of flying insects.

[0007] A first aspect of the present invention provides a method for measuring biological parameters of flying insects, comprising:

[0008] Step 1: Use the insect fixing component to suspend the measured insect at the designated position in the measurement box;

[0009] Step 2: Camera I and Camera II synchronously capture flight images of the measured insect;

[0010] Step 3: The industrial computer calculates the biological parameters of the measured insect based on the flight image of the measured insect.

[0011] Preferably, before cameras I and II capture flight images of the measured insects, cameras I and II are calibrated to obtain the intrinsic parameter matrices K and distortion parameters D of cameras I and II, respectively, as well as the rotation matrix R and translation vector t between cameras I and II.

[0012] Preferably, in any of the above schemes, in step 3, the industrial computer performs distortion correction on the flight images of the measured insect captured synchronously by camera I and camera II to eliminate radial and tangential distortion caused by the camera lenses; and performs stereo correction to align the flight images of the measured insect captured by camera I and camera II at the same time, thereby obtaining a sequence of flight images of the measured insect arranged frame by frame in chronological order.

[0013] Preferably, in any of the above solutions, in step 3, after the flight image of the measured insect is stereo-rectified, the industrial computer calculates the parameters of the measured insect.

[0014] Preferably, in any of the above solutions, in step 3, calculating the wing beat frequency of the measured insect includes:

[0015] Step 311: For each frame of the flight image sequence of the measured insect, the insect region is separated by a threshold comparison method to obtain a binary image sequence;

[0016] Step 312: Calculate the number of pixels in the insect region of each frame of the binary image of the measured insect according to the binary image sequence to obtain a pixel number sequence of the insect region;

[0017] Step 313: performing discrete Fourier transform on the insect area pixel number sequence to obtain a frequency spectrum;

[0018] Step 314: Calculate the actual frequency according to the frequency spectrum, and calculate the average frequency according to the actual frequency as the wingbeat frequency of the measured insect.

[0019] In any of the above solutions, preferably, in step 311, for each frame of the flight image sequence of the measured insect, according to the formula

[0020] ,

[0021] Separate the insect area, where I(x,y) is the grayscale value of the pixel at position (x,y) in the flight image, T is the set threshold, and I binary (x, y) is the pixel value at position (x, y) in the binary image. A value of 1 indicates an insect area, and a value of 0 indicates a non-insect area.

[0022] Any of the above solutions is preferably that in step 312, according to the formula

[0023] ,

[0024] Calculate the number of pixels in the insect area of ​​each frame of the binary image of the measured insect, where n insect is the number of pixels in the insect area, W and H are the width and height of the binary image, respectively, and I binary (x,y) is the pixel value at position (x,y) in the binary image.

[0025] Any of the above solutions is preferably that in step 313, according to the formula

[0026] ,

[0027] Perform discrete Fourier transform, where N insect (k) is the complex spectrum in the frequency domain, which represents the amplitude of the frequency component corresponding to the frequency index k. The value range of k is [0, N-1]; ninsect (n) represents the number of pixels at position n in the insect region pixel number sequence, and the value range of n is [0, N-1], where N represents the length of the insect region pixel number sequence; is a complex exponential function, representing the basis function in the frequency domain, j is an imaginary unit, is the phase of the frequency component.

[0028] Any of the above solutions is preferably that, in step 314, first according to the formula

[0029] ,

[0030] Calculate the actual frequency f k , where the actual frequency f k The unit is Hz, k is the frequency index, f s represents the sampling frequency in Hz, which is the frame rate of camera I and camera II. N represents the length of the sequence of the number of pixels in the insect area, that is, the number of flight images of the measured insect captured by camera I and camera II.

[0031] Any of the above solutions is preferably that in step 314, according to the calculated actual frequency f k , according to the formula

[0032] ,

[0033] Calculate the average frequency as the wingbeat frequency of the measured insect, where f avg Indicates the average frequency, that is, the wingbeat frequency of the measured insect, and its unit is Hz, N insect (k) represents the amplitude corresponding to the frequency index k, f k Indicates the actual frequency corresponding to frequency index k.

[0034] Preferably, in any of the above schemes, in step 3, the body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area of ​​the measured insect are calculated, including:

[0035] Step 321: Selecting the binary image of the insect being measured corresponding to the maximum pixel number in the insect region pixel number sequence as the image of the insect being measured in the flight state with wings spread, and the binary image of the insect being measured corresponding to the minimum pixel number as the image of the insect being measured in the flight state with wings folded, and calculating the disparity value based on the flight images corresponding to the image of the insect being measured in the flight state with wings spread and the image of the insect being measured in the flight state with wings folded, respectively;

[0036] Step 322: Calculate the plane depth of the body and the plane depth of the wings of the measured insect for the flight images of the measured insect in the wings-out and wings-folded flight states;

[0037] Step 323: Calculate the real distance corresponding to each pixel in the image of the measured insect in the state of flying with wings spread out at the plane depths where the body and wings of the measured insect are located respectively;

[0038] Step 324: Calculate the body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective flight wing area of ​​the measured insect based on the true distance.

[0039] Any of the above solutions is preferably that in step 322, according to the formula

[0040] ,

[0041] Calculate the depth of the plane where the body and wings of the measured insect are located respectively, where depth represents the depth of the plane where the body / wings of the measured insect are located, that is, the distance between the body / wings of the measured insect and the camera; f represents the focal length of camera I and camera II, in pixels; B represents the baseline distance between camera I and camera II, in millimeters; disparity represents the disparity value of a point on the measured insect in the flight images collected by camera I and camera II, in pixels.

[0042] Preferably, in any of the above schemes, in step 323, the depth of the plane where the body of the measured insect is located and the depth of the plane where the wings of the measured insect are located are calculated according to the formula

[0043] ,

[0044] Calculate the true distance d corresponding to each pixel point pixel , where depth represents the object distance (i.e., the distance from the camera to the object), f represents the focal length of camera I and camera II in pixels, and s pixel Represents the physical size of each pixel on the imaging sensor of Camera I and Camera II.

[0045] Preferably, in any of the above schemes, in step 324, the number of pixels occupied by the body length and body width of the measured insect in the image of the flight state with wings spread out is converted into real length based on the real distance corresponding to each pixel point calculated at the plane depth where the body of the measured insect is located, thereby obtaining the body length and body width parameters of the measured insect.

[0046] Preferably, in any of the above schemes, in step 324, the number of pixels occupied by the forewing length, forewing width, hindwing length and hindwing width of the measured insect in the image of the flight state with wings spread out is converted into real length based on the real distance corresponding to each pixel point calculated at the plane depth where the wings of the measured insect are located, thereby obtaining the parameters of the forewing length, forewing width, hindwing length and hindwing width of the measured insect.

[0047] Preferably, in any of the above schemes, in step 324, the number of pixels occupied by the measured insect in the image of the flight state with wings spread out is converted into a real area based on the real distance corresponding to each pixel point calculated at the depth of the plane where the wings of the measured insect are located, thereby obtaining the maximum flight projection area of ​​the measured insect, and the number of pixels occupied by the measured insect in the image of the flight state with wings folded is converted into a real area, thereby obtaining the minimum flight projection area of ​​the measured insect, and the effective flight wing area of ​​the measured insect is obtained by subtracting the two.

[0048] Preferably, in any of the above schemes, in step 2, during the process of collecting the flight image of the measured insect, the wind speed of the measurement environment is adjusted by fans arranged on the front wall and / or rear wall of the measurement box, and / or the stopped measured insect is prompted to flap its wings and fly.

[0049] Preferably, in any of the above solutions, in step 1, when the insect fixing assembly suspends the measured insect, it does not affect the normal wing flapping behavior of the measured insect.

[0050] A second aspect of the present invention provides a system for measuring biological parameters of flying insects, for executing the method for measuring biological parameters of flying insects, comprising: a measuring box, an insect fixing assembly, and a measuring assembly;

[0051] The measurement box is configured to provide an image acquisition environment required for measuring insect parameters;

[0052] The insect fixing assembly is disposed in the measuring box and is configured to suspend the measured insect at a designated position in the measuring box without affecting the normal wing flapping behavior of the measured insect;

[0053] The measuring component is configured to collect flight images of the measured insect and calculate multiple parameters of the measured insect based on the flight images.

[0054] Preferably, the inner top plate of the measuring box is set to white, the inner bottom plate is provided with a fill light board, and fans are provided on the front and rear side walls respectively; the insect fixing assembly is connected to the inner top plate of the measuring box.

[0055] Preferably, any of the above schemes is that the measuring component includes a camera I, a camera II and an industrial computer, and the camera I and camera II are arranged on the inner bottom plate of the measuring box and are configured to collect flight images of the measured insect; and the camera I and the camera II are arranged side by side directly below the insect fixing component, and the camera II is arranged on the left or right side of the camera I; the industrial computer is arranged on the outside of the measuring box and is connected to the camera I and camera II through a dual acquisition card, and is configured to obtain flight images of the measured insect and calculate multiple parameters of the measured insect based on the flight images.

[0056] Preferably, in any of the above solutions, the camera I and the camera II have the same model and parameters, and are both equipped with a fixed-focus macro lens.

[0057] Preferably, in any of the above solutions, the industrial computer is further configured to control the flight image acquisition of camera I and camera II.

[0058] The method and system for measuring biological parameters of flying insects of the present invention have the following beneficial effects:

[0059] 1. It can simultaneously measure multiple parameters such as insect wing beat frequency, body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area;

[0060] 2. Able to meet the needs of various insect measurements and suitable for large-scale data measurement;

[0061] 3. The measurement process is simple, the measurement time is short, the human error is small, the requirements for the measurement environment are low, and the measurement efficiency is high and the results are accurate;

[0062] 4. The measuring device has a simple structure and is easy to maintain;

[0063] 5. It can be used to improve the quality of insect parameter databases, thereby providing more reliable data support for insect radar identification technology and promoting the development of related research and applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 1 is a flow chart of a preferred embodiment of a method for measuring biological parameters of flying insects according to the present invention.

[0065] Figure 2 It is a schematic structural diagram of a preferred embodiment of the system for measuring biological parameters of flying insects according to the present invention.

[0066] Figure 3 This is a schematic diagram of an insect with its wings spread out.

[0067] Figure 4 Schematic diagram of an insect spreading its wings diagonally upward / downward.

[0068] Figure 5 For the method of measuring biological parameters of flying insects according to the present invention Figure 1 A schematic diagram of a flow chart for calculating the wingbeat frequency of a measured insect in the illustrated embodiment.

[0069] Figure 6 Schematic diagram of insect body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area.

[0070] Figure 7 For the method of measuring biological parameters of flying insects according to the present invention Figure 1 Schematic diagram of the process of calculating the body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area of ​​the measured insect in the embodiment shown. DETAILED DESCRIPTION

[0071] In order to better understand the present invention, the present invention is described in detail below with reference to specific embodiments.

[0072] Example 1

[0073] like Figure 1 As shown, a method for measuring biological parameters of flying insects comprises:

[0074] Step 1: Use the insect fixing component to suspend the measured insect at the designated position in the measurement box;

[0075] Step 2: Camera I and Camera II synchronously capture flight images of the measured insect;

[0076] Step 3: The industrial computer calculates the parameters of the measured insect based on the flight image of the measured insect.

[0077] like Figure 2 As shown, a system for measuring biological parameters of flying insects, used for executing the method for measuring biological parameters of flying insects, comprises: a measuring box 1, an insect fixing component and a measuring component;

[0078] The measuring box 1 is configured to provide an image acquisition environment required for measuring insect parameters;

[0079] The insect fixing assembly is disposed in the measuring box 1 and is configured to suspend the measured insect at a designated position in the measuring box 1 without affecting the normal wing flapping behavior of the measured insect;

[0080] The measuring component is configured to collect flight images of the measured insect and calculate multiple parameters of the measured insect based on the flight images.

[0081] Specifically, if Figure 2As shown, the interior top plate of the measuring box 1 is set to white. A fill light board 11 is set on the interior bottom plate. The fill light board 11 is used to project light vertically to the top of the measuring box 1, thereby ensuring that the entire measuring box 1 is bright. Fans 12 ( Figure 2 (The figure shows the internal structure of the measurement box 1, omitting the front side wall of the measurement box 1 and the fans thereon). Both fans 12 can be remotely turned on and off, and their wind speeds are adjustable. Their parameters can be set to the same or different. On the one hand, the fans 12 are used to provide different wind speeds, thereby enabling the measurement of the insect's wingbeat frequency at different wind speeds. On the other hand, during the flight image acquisition process, if the measured insect stops flying, turning on the fans 12 can prompt the measured insect to flap its wings, thereby ensuring that the flight image of the measured insect can be successfully captured. To facilitate the replacement of the measured insect, openable windows 13 are also provided on the left and right side walls of the measurement box 1. Preferably, the windows 13 are outward-opening.

[0082] The insect fixing assembly is connected to the inner top plate of the measuring box 1. Specifically, Figure 2 As shown, the insect fixing assembly includes a base plate 21 and an insect pin 22. The base plate 21 is fixedly arranged on the inner top plate of the measuring box 1. The insect pin 22 is detachably connected to the base plate 21, and a hanging ring is provided at the lower end of the insect pin 22, and the measured insect is clamped on the hanging ring.

[0083] like Figure 2 The measurement assembly shown includes camera I31, camera II32, and an industrial computer. Cameras I31 and II32 are mounted on the interior floor of the measurement box 1 and are configured to capture flight images of the insect being measured. Cameras I31 and II32 are positioned side by side directly below the insect mounting assembly (cameras I31 and II32 are positioned adjacent to each other, directly below the insect mounting assembly), with camera II32 positioned to the left or right of camera I31. The industrial computer is mounted outside the measurement box 1 and connected to cameras I31 and II32 via a dual acquisition card. It is configured to capture flight images of the insect being measured and calculate multiple parameters of the insect based on the flight images. In this embodiment, preferably, cameras I31 and II32 are of the same model and specifications, and both are equipped with fixed-focus macro lenses. The industrial computer is also configured to control cameras I31 and II32 to synchronously capture flight images. In this embodiment, preferably, cameras I31 and II32 are high-speed cameras.

[0084] The following is a detailed description of the method for measuring biological parameters of flying insects.

[0085] In step 1, healthy, vigorous insects are selected as the measured insects. Outside measurement chamber 1, the measured insects are attached to the lower ring of insect pin 22. Then, window 13 of measurement chamber 1 is opened, and insect pin 22, with the attached insects, is placed on base plate 21. During placement, the measured insects should be positioned as directly above the parallel cameras I 31 and II 32 as possible.

[0086] Before step 2, that is, before cameras I31 and II32 capture flight images of the insect being measured, cameras I31 and II32 are calibrated to obtain the intrinsic parameter matrices K and distortion parameters D of cameras I31 and II32, respectively, as well as the rotation matrix R and translation vector t between cameras I31 and II32. In this embodiment, preferably, a chessboard image is captured for cameras I31 and II32, and single-target calibration is first performed based on OpenCV-Python, followed by dual-target calibration, to obtain the intrinsic parameter matrices K and distortion parameters D of cameras I31 and II32, respectively, as well as the rotation matrix R and translation vector t between cameras I31 and II32. The specific calibration method is not specifically limited in this application, and methods disclosed in the prior art can be used.

[0087] Perform single target timing on camera I31 and camera II32 respectively to obtain the focal length (f x , f y ), main point (c x , c y ), radial distortion parameters (k1, k2, k3) and tangential distortion parameters (p1, p2), and then respectively according to the formula:

[0088] The intrinsic parameter matrices KI and KII and distortion parameters DI and DII of cameras I31 and II32 are calculated using D = [k1, k2, p1, p2, k3], respectively. Then, binocular positioning is performed on cameras I31 and II32, and the rotation matrix R and translation vector t between them are calculated. It should be noted that binocular positioning of cameras I31 and II32 can be performed using existing techniques, such as the existing binocular positioning function in OpenCV, or other methods, which are not specifically limited in this application.

[0089] In step 2, after calibrating cameras I31 and II32, the height at which the insect is suspended by the insect mounting assembly is adjusted (for example, by using insect pins 22 of varying lengths or adjusting the connection length between the pins 22 and the base plate 21) to ensure that the insect is in focus. Specifically, when the industrial computer display clearly displays the images of the insect captured by cameras I31 and II32, this indicates that the plane of the insect is within the focal plane of cameras I31 and II32. The industrial computer then controls cameras I31 and II32 to synchronously capture flight images of the insect. The acquisition time is set as needed; in this embodiment, the acquisition time is preferably set within a range of 10-30 seconds. It should be noted that during the image acquisition process, if the measured insect stops flying, the image acquisition is stopped, the fan 12 is turned on, and the measured insect is prompted to fly normally before restarting the image acquisition; if it is necessary to capture flight images of the measured insect under different wind speed conditions, the speed of the fan 12 is first set according to the wind speed requirements, and then the image acquisition is started after the measured insect flies normally at the set wind speed.

[0090] In step 3, the industrial computer performs distortion correction on the flight images of the measured insect captured by cameras I31 and II32 to eliminate radial and tangential distortion caused by the camera lenses. Stereo correction is then performed to align the flight images of the measured insect captured by cameras I and II at the same time, resulting in a chronological, frame-by-frame sequence of flight images of the measured insect. It should be noted that distortion correction is performed using the intrinsic parameter matrix K and distortion parameter D obtained during camera calibration. Specifically, each frame of the flight image of the measured insect captured by camera I31 is corrected using the intrinsic parameter matrix K and distortion parameter D obtained during camera I31 calibration, while each frame of the flight image of the measured insect captured by camera II32 is corrected using the intrinsic parameter matrix K and distortion parameter D obtained during camera II32 calibration.

[0091] Specifically, the distortion correction includes the following steps:

[0092] According to the formula: , convert each pixel coordinate (x',y') in the flight image to normalized camera coordinate (u',v');

[0093] According to the distortion model:

[0094] , remove the radial and tangential distortion caused by the camera lens, and obtain the normalized camera coordinates (u, v) after dedistortion, where , (k1, k2, k3) are radial distortion parameters, (p1, p2) are tangential distortion parameters;

[0095] According to the formula: , mapping the dedistorted normalized camera coordinates (u, v) to the distortion-corrected image pixel coordinates (x, y).

[0096] More specifically, during stereo calibration, the insect images captured by cameras I31 and II32 are transformed into a common image plane so that the points of the same name on the image are on the same row (the epipolar lines are parallel), and the flight images of the measured insect captured by cameras I31 and II32 at the same time are aligned, thereby obtaining a sequence of flight images of the measured insect arranged in chronological order and frame by frame.

[0097] In step 3, after stereo correction of the flight image of the measured insect, the industrial computer calculates the parameters of the measured insect, which include the wing beat frequency, body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area of ​​the measured insect.

[0098] The flight behavior of insects can be regarded as a process of periodically spreading wings flatly, spreading wings diagonally upward, spreading wings flatly, spreading wings diagonally downward, and then spreading wings flatly. Therefore, during the process of insect wing flapping, the number of pixels in the insect area in the flight image of the measured insect changes periodically. Figure 3 The figure shows a schematic diagram of an insect with its wings spread out. At this time, the number of pixels in the insect area is the largest in the flight image of the measured insect. Figure 4 The figure shows a schematic diagram of an insect spreading its wings obliquely upward / downward. At this time, in the flight image of the measured insect, the number of pixels in the insect area decreases. Therefore, in the sequence of flight images of the measured insect arranged frame by frame in chronological order, the number of pixels in the insect area shows a periodic change of increase-decrease-increase-decrease.

[0099] like Figure 5 As shown, in step 3, calculating the wing beat frequency of the measured insect includes:

[0100] Step 311: For each frame of the flight image sequence of the measured insect, the insect region is separated by a threshold comparison method to obtain a binary image sequence;

[0101] Step 312: Calculate the number of pixels in the insect region of each frame of the binary image of the measured insect according to the binary image sequence to obtain a pixel number sequence of the insect region;

[0102] Step 313: performing discrete Fourier transform on the insect area pixel number sequence to obtain a frequency spectrum;

[0103] Step 314: Calculate the actual frequency according to the frequency spectrum, and calculate the average frequency according to the actual frequency as the wingbeat frequency of the measured insect.

[0104] Specifically, in step 311, for each frame of the flight image sequence of the measured insect, according to the formula

[0105] ,

[0106] Separate the insect area, where I(x,y) is the grayscale value of the pixel at position (x,y) in the flight image, T is the set threshold, and I binary (x, y) is the pixel value at position (x, y) in the binary image. A value of 1 indicates an insect area, and a value of 0 indicates a non-insect area.

[0107] In step 312, according to the formula

[0108] ,

[0109] Calculate the number of pixels in the insect area of ​​each frame of the binary image of the measured insect, where n insect is the number of pixels in the insect area, W and H are the width and height of the binary image, respectively, and I binary (x,y) is the pixel value at position (x,y) in the binary image.

[0110] In step 313, according to the formula

[0111] ,

[0112] Perform discrete Fourier transform, where N insect (k) is the complex spectrum in the frequency domain, which represents the amplitude of the frequency component corresponding to the frequency index k. The value range of k is [0, N-1]; n insect (n) represents the number of pixels at position n in the insect region pixel number sequence, and the value range of n is [0, N-1], where N represents the length of the insect region pixel number sequence; is a complex exponential function, representing the basis function in the frequency domain, j is an imaginary unit, is the phase of the frequency component.

[0113] In step 314, first, according to the formula

[0114]

[0115] Calculate the actual frequency f k , where the actual frequency f k The unit is Hz, k is the frequency index, f s represents the sampling frequency in Hz, which is the frame rate of camera I and camera II. N represents the length of the sequence of the number of pixels in the insect area, that is, the number of flight images of the measured insect captured by camera I and camera II.

[0116] Then according to the calculated actual frequency f k , according to the formula

[0117] ,

[0118] Calculate the average frequency as the wingbeat frequency of the measured insect, where f avg Indicates the average frequency, that is, the wingbeat frequency of the measured insect, and its unit is Hz, N insect (k) represents the amplitude corresponding to the frequency index k, f k Indicates the actual frequency corresponding to frequency index k.

[0119] like Figure 6 As shown in the figure, when the insect is in the flight state with its wings spread out, the solid line BL (Body Length) represents the body length of the insect being measured, which is the length from the front end of the head to the end of the abdomen of the insect being measured. When measuring, it is measured along the center line of the insect body; the solid line BW (Body Width) represents the body width of the insect being measured, which is the lateral width of the insect body at the widest part. When measuring, the widest part of the insect body is selected in the trunk (such as the chest) area; the solid line FWL (Forewing Length) represents the forewing length of the insect being measured, which is the maximum length of the insect forewing from the root (the part connecting to the body) to the end of the forewing. When measuring, it is measured from the wing root to the wing tip; the solid line FWW (Forewing Width) represents the forewing width of the insect being measured, which represents the lateral width of the forewing at the widest part. When measuring, the widest part of the wing is selected perpendicular to the direction of the forewing length; the hindwing length HWL (Hindwing Length) and hindwing width HWW (Hindwing Width) of the insect being measured Refer to the definition of forewing forewing. The effective flight wing area is the total projected area of ​​the measured insect with its wings extended minus the total projected area of ​​the measured insect with its wings folded.

[0120] like Figure 7 As shown, in step 3, the body length, body width, forewing length, forewing width, hindwing length, hindwing width and effective flight wing area of ​​the measured insect are calculated, including:

[0121] Step 321: Selecting the binary image of the insect being measured corresponding to the maximum pixel number in the insect region pixel number sequence as the image of the insect being measured in the flight state with wings spread, and the binary image of the insect being measured corresponding to the minimum pixel number as the image of the insect being measured in the flight state with wings folded, and calculating the disparity value based on the flight images corresponding to the image of the insect being measured in the flight state with wings spread and the image of the insect being measured in the flight state with wings folded, respectively;

[0122] Step 322: Calculate the plane depth of the body and the plane depth of the wings of the measured insect for the flight images of the measured insect in the wings-out and wings-folded flight states;

[0123] Step 323: Calculate the real distance corresponding to each pixel in the image of the measured insect in the state of flying with wings spread out at the plane depths where the body and wings of the measured insect are located respectively;

[0124] Step 324: Calculate the body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective flight wing area of ​​the measured insect based on the true distance.

[0125] Specifically, in step 321, according to the formula:

[0126] , calculate the disparity value, that is, the difference in horizontal pixel coordinates of the same 3D scene point in the left and right images after stereo correction, where x left Indicates the horizontal pixel coordinate of the 3D scene point in the left eye (Left) corrected image, x right Indicates the horizontal pixel coordinates of the same 3D scene point in the right eye (Right) rectified image.

[0127] In step 322, according to the formula

[0128] ,

[0129] Calculate the depth of the plane where the body and wings of the measured insect are located respectively, where depth represents the depth of the plane where the body / wings of the measured insect are located, that is, the distance between the body / wings of the measured insect and the camera; f represents the focal length of camera I and camera II, in pixels; B represents the baseline distance between camera I and camera II, in millimeters; disparity represents the disparity value of a point on the measured insect in the flight images collected by camera I and camera II, in pixels.

[0130] In step 323, the depth of the plane where the body of the measured insect is located and the depth of the plane where the wings of the measured insect are located are calculated according to the formula

[0131] ,

[0132] Calculate the true distance d corresponding to each pixel point pixel , where depth represents the object distance (i.e., the distance from the camera to the object), f represents the focal length of camera I and camera II in pixels, and s pixel Represents the physical size of each pixel on the imaging sensor of Camera I and Camera II.

[0133] In step 324, based on the actual distance corresponding to each pixel point calculated at the plane depth of the body of the measured insect, the number of pixels occupied by the body length and body width of the measured insect in the image of the flat-winged flight state is converted into the actual length, thereby obtaining the body length and body width parameters of the measured insect.

[0134] In step 324, the number of pixels occupied by the forewing length, forewing width, hindwing length and hindwing width of the measured insect in the image of the wings-out flight state is converted into real length based on the real distance corresponding to each pixel point calculated at the depth of the plane where the wings of the measured insect are located, thereby obtaining the parameters of the forewing length, forewing width, hindwing length and hindwing width of the measured insect. It should be noted that the number of pixels occupied by the forewing length, forewing width, hindwing length and hindwing width in the image of the wings-out flight state can be calculated according to Figure 6 As shown, it is obtained by drawing a line with a mouse on an industrial computer, or by adopting other known methods.

[0135] In step 324, the number of pixels in the image of the insect in flight with wings spread is converted to a real area based on the actual distance corresponding to each pixel calculated at the depth of the plane where the insect's wings are located. This is used to obtain the maximum flight projection area of ​​the insect. The number of pixels in the image of the insect in flight with wings folded is converted to a real area to obtain the minimum flight projection area of ​​the insect. The two are then subtracted to obtain the effective flight wing area of ​​the insect. It should be noted that the flight projection area of ​​the insect is the number of pixels occupied by the insect area.

[0136] Example 2

[0137] This embodiment is similar to the previous embodiment, except that, in this embodiment, preferably, a first magnet is provided on the substrate 21, and a groove is provided on the first magnet. A second magnet is provided on the upper end of the insect pin 22, and the shape of the second magnet matches the shape of the groove. Through the first magnet and the second magnet, the substrate 21 and the insect pin 22 are detachably connected.

[0138] It is further preferred in this embodiment that the size of the measurement box 1 is 50 cm×50 cm×50 cm.

[0139] Example 3

[0140] This embodiment is similar to the above embodiment, except that, in this embodiment, preferably, the insect fixing assembly refers to the insect fixing assembly disclosed in Chinese invention patent CN 115362990 A, and the measured insect is clamped to the hanging ring at the lower end of the insect fixing assembly according to the method disclosed in the invention patent.

[0141] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the above embodiments describe the present invention in detail, those skilled in the art should understand that they can modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein, and these replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present invention.

Claims

1. A method for measuring biological parameters of flying insects, comprising: Step 1: Use the insect fixing component to suspend the measured insect at the designated position in the measurement box; Step 2: Camera I and Camera II synchronously capture flight images of the measured insect; Step 3: The industrial computer calculates the biological parameters of the measured insect based on the flight image of the measured insect; Its characteristics are: In step 3, calculating the wing beat frequency of the measured insect includes: Step 311: For each frame of the flight image sequence of the measured insect, the insect region is separated by a threshold comparison method to obtain a binary image sequence; Step 312: Calculate the number of pixels in the insect region of each frame of the binary image of the measured insect according to the binary image sequence to obtain a pixel number sequence of the insect region; Step 313: performing discrete Fourier transform on the insect area pixel number sequence to obtain a frequency spectrum; Step 314: Calculate the actual frequency according to the frequency spectrum, and calculate the average frequency according to the actual frequency as the wingbeat frequency of the measured insect; Among them, in step 313, according to the formula ， Perform discrete Fourier transform, where N insect (k) is the complex spectrum in the frequency domain, which represents the amplitude of the frequency component corresponding to the frequency index k. The value range of k is [0, N-1]; n insect (n) represents the number of pixels at position n in the insect region pixel number sequence, and the value range of n is [0, N-1], where N represents the length of the insect region pixel number sequence; is a complex exponential function, representing the basis function in the frequency domain, j is an imaginary unit, is the phase of the frequency component; In step 314, first, according to the formula ， Calculate the actual frequency f k , where the actual frequency f k The unit is Hz, k is the frequency index, f s represents the sampling frequency in Hz, which is the frame rate of camera I and camera II. N represents the length of the sequence of the number of pixels in the insect area, that is, the number of flight images of the measured insect captured by camera I and camera II. Then according to the calculated actual frequency f k , according to the formula ， Calculate the average frequency as the wingbeat frequency of the measured insect, where f avg Indicates the average frequency, that is, the wingbeat frequency of the measured insect, and its unit is Hz, N insect (k) represents the amplitude corresponding to the frequency index k, f k Indicates the actual frequency corresponding to frequency index k.

2. The method for measuring biological parameters of flying insects according to claim 1, wherein: In step 3, the industrial computer performs distortion correction on the flight images of the measured insects captured by cameras I and II to eliminate radial and tangential distortion caused by the camera lenses; stereo correction is performed to align the flight images of the measured insects captured by cameras I and II at the same time, thereby obtaining a sequence of flight images of the measured insects arranged in chronological order and frame by frame.

3. The method for measuring biological parameters of flying insects according to claim 1, wherein: In step 311, for each frame of the flight image sequence of the measured insect, according to the formula ， Separate the insect area, where I(x,y) is the grayscale value of the pixel at position (x,y) in the flight image, T is the set threshold, and I binary (x, y) is the pixel value at position (x, y) in the binary image. A value of 1 indicates an insect area, and a value of 0 indicates a non-insect area.

4. The method for measuring biological parameters of flying insects according to claim 3, wherein: In step 312, according to the formula ， Calculate the number of pixels in the insect area of ​​each frame of the binary image of the measured insect, where n insect is the number of pixels in the insect area, W and H are the width and height of the binary image, respectively, and I binary (x,y) is the pixel value at position (x,y) in the binary image.

5. The method for measuring biological parameters of flying insects according to claim 1, wherein: In step 3, the body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective flight wing area of ​​the measured insect are calculated, including: Step 321: Selecting the binary image of the insect being measured corresponding to the maximum pixel number in the insect region pixel number sequence as the image of the insect being measured in the flight state with wings spread, and the binary image of the insect being measured corresponding to the minimum pixel number as the image of the insect being measured in the flight state with wings folded, and calculating the disparity value based on the flight images corresponding to the image of the insect being measured in the flight state with wings spread and the image of the insect being measured in the flight state with wings folded, respectively; Step 322: Calculate the plane depth of the body and the plane depth of the wings of the measured insect for the flight images of the measured insect in the wings-out and wings-folded flight states; Step 323: Calculate the real distance corresponding to each pixel in the image of the measured insect in the state of flying with wings spread out at the plane depths where the body and wings of the measured insect are located respectively; Step 324: Calculate the body length, body width, forewing length, forewing width, hindwing length, hindwing width, and effective flight wing area of ​​the measured insect based on the true distance.

6. The method for measuring biological parameters of flying insects according to claim 5, wherein: In step 322, according to the formula ， Calculate the depth of the plane where the body and wings of the measured insect are located respectively, where depth represents the depth of the plane where the body / wings of the measured insect are located, that is, the distance between the body / wings of the measured insect and the camera; f represents the focal length of camera I and camera II, in pixels; B represents the baseline distance between camera I and camera II, in millimeters; disparity represents the disparity value of a point on the measured insect in the flight images collected by camera I and camera II, in pixels; In step 323, the depth of the plane where the body of the measured insect is located and the depth of the plane where the wings of the measured insect are located are calculated according to the formula ， Calculate the true distance d corresponding to each pixel point pixel , where depth represents the object distance, that is, the distance from the camera to the object, f represents the focal length of camera I and camera II, in pixels, and s pixel Represents the physical size of each pixel on the imaging sensor of Camera I and Camera II.

7. The method for measuring biological parameters of flying insects according to claim 6, wherein: In step 324, the number of pixels occupied by the length and width of the insect in the image of the wingspan flight state is converted into real length based on the real distance corresponding to each pixel point calculated at the depth of the plane where the insect's body is located, thereby obtaining the body length and width parameters of the insect. According to the real distance corresponding to each pixel point calculated at the depth of the plane where the wings of the measured insect are located, the number of pixels occupied by the forewing length, forewing width, hindwing length and hindwing width of the measured insect in the image of the flat-winged flight state is converted into real length, and then the parameters of the forewing length, forewing width, hindwing length and hindwing width of the measured insect are obtained; According to the real distance corresponding to each pixel point calculated at the depth of the plane where the wings of the measured insect are located, the number of pixels occupied by the image of the measured insect in the flight state with wings spread out is converted into the real area, and then the maximum flight projection area of ​​the measured insect is obtained. The number of pixels occupied by the image of the measured insect in the flight state with wings folded is converted into the real area, and then the minimum flight projection area of ​​the measured insect is obtained. The effective flight wing area of ​​the measured insect is obtained by subtracting the two.

8. A system for measuring biological parameters of flying insects, characterized by: A method for measuring biological parameters of flying insects according to any one of claims 1 to 7, comprising: a measuring box, an insect fixing assembly, and a measuring assembly; The measurement box is configured to provide an image acquisition environment required for measuring insect parameters; The insect fixing assembly is disposed in the measuring box and is configured to suspend the measured insect at a designated position in the measuring box without affecting the normal wing flapping behavior of the measured insect; The measuring component is configured to collect flight images of the measured insect and calculate multiple parameters of the measured insect based on the flight images.

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