A plant 3D chlorophyll fluorescence imaging system based on structured light vision

Abstract

This invention discloses a three-dimensional chlorophyll fluorescence imaging system for plants based on structured light vision, comprising: Step S1: constructing a three-dimensional chlorophyll fluorescence imaging system; Step S2: switching between measurement light source, photochemical light source, saturated pulse light source, and far-red light source in red filter mode to acquire chlorophyll fluorescence images of plants under different conditions; Step S3: turning on ordinary white light source, acquiring single-channel images of the plant sequentially in red, green, and blue filter modes, and fusing them to obtain a three-channel color image of the plant; Step S4: turning off all light sources, acquiring a dual-frequency twelve-step phase-shifting fringe image modulated by the plant in neutral filter mode, and reconstructing a three-dimensional point cloud model of the plant; Step S5: using the chlorophyll fluorescence image and the three-channel color image to render the three-dimensional point cloud model of the plant pixel by pixel to achieve three-dimensional chlorophyll fluorescence imaging of the plant.

Description

Technical Field

[0001] This invention belongs to the field of visual measurement technology. Specifically, this invention relates to a three-dimensional chlorophyll fluorescence imaging system for plants based on structured light vision. Background Technology

[0002] Chlorophyll fluorescence is an effective probe of plant photosynthesis, capable of elucidating information about light capture, energy conversion, and electron transfer during photosynthesis. It is used to detect indicators such as photosynthetic activity, physiological function, pathological condition, and stress resistance at the leaf and canopy scales. Traditional chlorophyll fluorescence measurement techniques typically employ single-point or multi-point sampling to measure chlorophyll fluorescence values ​​at specific locations on plant leaves. However, chlorophyll fluorescence values ​​vary across different parts of a plant leaf. While measuring chlorophyll fluorescence at single or multiple points can reflect the photosynthetic characteristics of plant leaves to some extent, it is difficult to capture the three-dimensional spatial heterogeneity of photosynthesis in plant leaves.

[0003] To overcome the aforementioned limitations, chlorophyll fluorescence imaging technology can simultaneously acquire chlorophyll fluorescence images of individual leaves, single plants, or plant populations, enabling visualization of differences in photosynthetic performance and quantitative assessment of the spatial heterogeneity of photosynthesis at different locations on a single leaf, between different leaves of a single plant, or among different plants within a plant population. However, different leaves of a single plant or different plants within a plant population exhibit three-dimensional spatial distribution characteristics, making it difficult for two-dimensional chlorophyll fluorescence images to reflect the influence of factors such as different canopy heights and leaf shading on the photosynthetic characteristics of plant leaves. Therefore, acquiring three-dimensional chlorophyll fluorescence images of individual plants or plant populations is crucial for studying plant morphological and structural traits and photosynthetic physiological characteristics, and for elucidating the three-dimensional spatial heterogeneity of plant photosynthesis. Summary of the Invention

[0004] This invention provides a three-dimensional chlorophyll fluorescence imaging system for plants based on structured light vision, in order to solve the problems existing in the above-mentioned background art.

[0005] To achieve the above objectives, the technical solution adopted by this invention is: a three-dimensional chlorophyll fluorescence imaging system for plants based on structured light vision, specifically including the following steps:

[0006] Step S1: Construct a three-dimensional chlorophyll fluorescence imaging system, which mainly includes a near-infrared camera, an electric filter wheel, a digital projector, a measurement light source, a photochemical light source, a saturated pulse light source, a far-infrared light source, a normal white light source, a light source controller, and the plant to be tested. The electric filter wheel is installed directly in front of the near-infrared camera.

[0007] Step S2: Switch the electric filter wheel to red filter mode; ① First, turn on the measurement light source, and the near-infrared camera acquires the minimum fluorescence image Fo after the plant has dark adapted; ② Next, turn on the saturated pulse light source, and the near-infrared camera acquires the maximum fluorescence image Fm after the plant has dark adapted; ③ Then turn on the photochemical light source, and then turn on the saturated pulse light source, and the near-infrared camera acquires the maximum fluorescence image Fm′ and the steady-state fluorescence image Fs after the plant has light adapted in sequence; ④ Finally, turn on the far-infrared light source, and the near-infrared camera acquires the minimum fluorescence image Fo′ after the plant has light adapted.

[0008] Step S3: Turn on the ordinary white light source, and the electric filter wheel switches to three modes in sequence: red filter, green filter, and blue filter. The near-infrared camera sequentially acquires single-channel images of plants under different color modes, and uses them as the three-channel color components of the color image. By fusing them, a three-channel color image can be obtained.

[0009] Step S4: Turn off all light sources, switch the electric filter wheel to neutral filter mode, project dual-frequency twelve-step phase-shifting fringes onto the plant under test using a digital projector, and simultaneously acquire images of the dual-frequency twelve-step phase-shifting fringes modulated by the plant using a near-infrared camera to calculate the high-frequency absolute phase. Then, based on the calibration results of the near-infrared camera-digital projector system, map the high-frequency absolute phase pixel by pixel into three-dimensional space to reconstruct the three-dimensional point cloud model of the plant.

[0010] Step S5: During the above image data acquisition process, the entire three-dimensional chlorophyll fluorescence imaging system remains fixed. Therefore, the chlorophyll fluorescence image and the three-channel color image can be directly used to render the three-dimensional point cloud model of the plant pixel by pixel to obtain the chlorophyll fluorescence image and color image in three-dimensional space, which helps to analyze the spatial distribution of chlorophyll fluorescence in the plant.

[0011] Preferably, in step S1, the spectral range of the near-infrared camera is 400nm to 1000nm.

[0012] Preferably, in step S1, the electric filter wheel can be switched to four modes: red-green filter, green filter, blue filter, and neutral filter; wherein the center wavelength of the red filter is 690nm, the center wavelength of the green filter is 550nm, and the center wavelength of the blue filter is 450nm.

[0013] Preferably, in step S1, the wavelength of the measuring light source is 450nm, the wavelength of the photochemical light source is 660nm, the wavelength of the saturated pulse light source is 450nm, the maximum light intensity is 4000umol m-2s-1, and the wavelength of the far-infrared light source is 740nm.

[0014] Preferably, in step S2, based on the chlorophyll fluorescence images Fo, Fm, Fm′, Fs, and Fo′, the following chlorophyll fluorescence parameters reflecting plant photosynthetic physiology are further calculated:

[0015] The maximum photochemical quantum yield of PS II is Fv / Fm = (Fm-Fo) / Fm;

[0016] PS II photochemical quenching coefficient qP=(Fm′-Fs) / (Fm′-Fo′);

[0017] Chl fluorescence non-photochemical quenching coefficient NPQ=(Fm-Fm′) / Fm′;

[0018] PS II photochemical effective quantum yield Fv′ / Fm′=(Fm′-Fo′) / Fm′.

[0019] Preferably, in step S4, the dual-frequency twelve-step phase-shifting fringe image modulated by the plant is represented as follows:

[0020]

[0021]

[0022] In the formula: n = 1, 2, ..., 12; and This represents high-frequency and low-frequency fringes, with the frequency of the low-frequency fringes set to be less than 1; A(x,y) and B(x,y) represent the background intensity and modulation intensity, respectively; φ h (x,y) and φ l (x, y) represent the high-frequency cutoff phase and the low-frequency cutoff phase, respectively, which can be solved using the following formula:

[0023]

[0024]

[0025] Where: High-frequency cutoff phase φ h (x,y) and low-frequency truncated phase φ l The values ​​of (x, y) are all in the range [-π, +π); because the frequency of the low-frequency fringes is less than 1, the low-frequency truncated phase φ l (x,y) does not require phase expansion, i.e., low-frequency absolute phase Φ l (x,y) equals the low-frequency truncation phase φ l (x,y); based on the high-frequency absolute phase Φ h (x,y) and low-frequency absolute phase Φ l By establishing the mathematical constraints on (x,y), the high-frequency absolute phase Φ can be recovered. h (x,y) are as follows:

[0026]

[0027] In the formula: f h and f l These represent the frequencies of the high-frequency and low-frequency fringes, respectively; Round indicates the rounding function; note the absolute phase Φ of the high-frequency fringes. h (x,y) is closely related to the three-dimensional morphology of plants.

[0028] Preferably, in step S5, the three-dimensional point cloud is rendered pixel by pixel, that is, the three-dimensional point cloud is colored pixel by pixel using the fluorescence value in the chlorophyll fluorescence image, and the three-dimensional point cloud is colored pixel by pixel using the color value in the three-channel color image.

[0029] The beneficial effects of adopting the above technical solutions are:

[0030] 1. The plant three-dimensional chlorophyll fluorescence imaging system based on structured light vision provided by this invention can simultaneously acquire chlorophyll fluorescence images and three-dimensional point cloud images of plants, which is beneficial for studying the morphological and structural traits and photosynthetic physiological traits of plants, and helps to analyze the three-dimensional spatial heterogeneity of plant photosynthesis. It has the advantages of high speed, high precision and strong robustness. Attached Figure Description

[0031] Figure 1 A flowchart of the workflow of a three-dimensional chlorophyll fluorescence imaging system for plants is shown.

[0032] Figure 2 The three-dimensional point cloud rendering effect of chlorophyll fluorescence images and three-channel color images is shown; Detailed Implementation

[0033] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, in order to help those skilled in the art to have a more complete, accurate and in-depth understanding of the concept and technical solutions of the present invention, and to facilitate its implementation.

[0034] like Figures 1 to 2 As shown, this invention is a three-dimensional chlorophyll fluorescence imaging system for plants based on structured light vision. It can simultaneously acquire chlorophyll fluorescence images and three-dimensional point cloud images of plants, which is beneficial for studying the morphological and structural traits and photosynthetic physiological traits of plants. It also helps to analyze the three-dimensional spatial heterogeneity of plant photosynthesis and has the advantages of high speed, high precision, and strong robustness.

[0035] The specific working method is described below using specific embodiments:

[0036] Example 1:

[0037] Step S1: Construct a three-dimensional chlorophyll fluorescence imaging system, which mainly includes a near-infrared camera, an electric filter wheel, a digital projector, a measurement light source, a photochemical light source, a saturated pulse light source, a far-infrared light source, a normal white light source, a light source controller, and the plant to be tested. The electric filter wheel is installed directly in front of the camera.

[0038] Step S2: Switch the electric filter wheel to red filter mode; ① First, turn on the measurement light source, and the near-infrared camera acquires the minimum fluorescence image Fo after the plant has dark adapted; ② Next, turn on the saturated pulse light source, and the near-infrared camera acquires the maximum fluorescence image Fm after the plant has dark adapted; ③ Then turn on the photochemical light source, and then turn on the saturated pulse light source, and the near-infrared camera acquires the maximum fluorescence image Fm′ and the steady-state fluorescence image Fs after the plant has light adapted in sequence; ④ Finally, turn on the far-infrared light source, and the near-infrared camera acquires the minimum fluorescence image Fo′ after the plant has light adapted.

[0039] Step S3: Turn on the ordinary white light source, and the electric filter wheel switches to three modes in sequence: red filter, green filter, and blue filter. The near-infrared camera sequentially acquires single-channel images of plants under different color modes, and uses them as the three-channel color components of the color image. By fusing them, a three-channel color image can be obtained.

[0040] Step S4: Turn off all light sources, switch the electric filter wheel to neutral filter mode, project dual-frequency twelve-step phase-shifting fringes onto the plant under test using a digital projector, and simultaneously acquire images of the dual-frequency twelve-step phase-shifting fringes modulated by the plant using a near-infrared camera to calculate the high-frequency absolute phase. Then, based on the calibration results of the near-infrared camera-digital projector system, map the high-frequency absolute phase pixel by pixel into three-dimensional space to reconstruct the three-dimensional point cloud model of the plant.

[0041] Step S5: During the above image data acquisition process, the entire three-dimensional chlorophyll fluorescence imaging system remains fixed. Therefore, the chlorophyll fluorescence image and the three-channel color image can be directly used to render the three-dimensional point cloud model of the plant pixel by pixel to obtain the chlorophyll fluorescence image and color image in three-dimensional space, which helps to analyze the spatial distribution of chlorophyll fluorescence in the plant.

[0042] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A plant three-dimensional chlorophyll fluorescence imaging system based on structured light vision, characterized in that: Specifically comprising the following steps: Step S1: build a three-dimensional chlorophyll fluorescence imaging system, mainly including a near-infrared camera, a motorized filter wheel, a digital projector, a measuring light source, an actinic light source, a saturated pulse light source, a far-infrared light source, a common white light source, a light source controller and a plant to be measured, wherein the motorized filter wheel is installed in front of the near-infrared camera; Step S2: the motorized filter wheel is switched to a red filter mode; ① first turn on the measuring light source, and the near-infrared camera collects the minimum fluorescence image Fo of the plant after dark adaptation; ② then turn on the saturated pulse light source, and the near-infrared camera collects the maximum fluorescence image Fm of the plant after dark adaptation; ③ then turn on the actinic light source, and then turn on the saturated pulse light source, and the near-infrared camera collects the maximum fluorescence image Fm' and the steady-state fluorescence image Fs of the plant after light adaptation in turn; ④ finally turn on the far-infrared light source, and the near-infrared camera collects the minimum fluorescence image Fo' of the plant after light adaptation; Step S3: turn on the common white light source, and the motorized filter wheel is switched to a red filter, a green filter and a blue filter in turn, and the near-infrared camera collects single-channel images of the plant under different color modes in turn, and takes them as three-channel color components of a color image, and a three-channel color image can be obtained by fusion; Step S4: turn off all light sources, switch the motorized filter wheel to a neutral filter mode, project a double-frequency twelve-step phase shift fringe to the plant to be measured by the digital projector, and synchronously collect the double-frequency twelve-step phase shift fringe image modulated by the plant by the near-infrared camera, and the high-frequency absolute phase is calculated; then, according to the near-infrared camera-digital projector system calibration result, the high-frequency absolute phase is mapped to the three-dimensional space pixel by pixel, and the three-dimensional point cloud model of the plant can be reconstructed; Step S5: during the above image data collection process, the entire three-dimensional chlorophyll fluorescence imaging system remains fixed, so the chlorophyll fluorescence image and the three-channel color image can be directly used to render the three-dimensional point cloud model of the plant pixel by pixel, and the chlorophyll fluorescence image and the color image in the three-dimensional space are obtained, which is helpful for analyzing the three-dimensional chlorophyll fluorescence spatial distribution of the plant. In the step S1, the spectral range of the near-infrared camera is 400nm to 1000nm.

2. The structured light vision based plant three-dimensional chlorophyll fluorescence imaging system according to claim 1, characterized in that: In the step S1, the motorized filter wheel can be switched to four modes, namely a red green filter, a green filter, a blue filter and a neutral filter; wherein the center wavelength of the red filter is 690nm, the center wavelength of the green filter is 550nm, and the center wavelength of the blue filter is 450nm. 3.The structured light vision-based plant three-dimensional chlorophyll fluorescence imaging system according to claim 1, characterized in that: In the step S2, according to the chlorophyll fluorescence images Fo, Fm, Fm', Fs and Fo', the chlorophyll fluorescence parameters reflecting the photosynthetic physiology of the plant are further calculated as follows:

4. The structured light vision based three-dimensional chlorophyll fluorescence imaging system for plants of claim 1, wherein: The wavelength of the measuring light source is 450 nm, the wavelength of the actinic light source is 660 nm, the wavelength of the saturated pulse light source is 450 nm, the maximum light intensity is 4000 umol m -2 s -1 , and the wavelength of the far infrared light source is 740 nm.

5. The structured light vision based three-dimensional chlorophyll fluorescence imaging system for plants of claim 1, wherein: PS II maximum photochemical quantum yield Fv / Fm=(Fm-Fo) / Fm; PS II photochemical quenching coefficient qP=(Fm'-Fs) / (Fm'-Fo'); Chl fluorescence non-photochemical quenching coefficient NPQ=(Fm-Fm') / Fm'; PS II photochemical effective quantum yield Fv' / Fm'=(Fm'-Fo') / Fm'. ​ 6.The structured light vision-based plant three-dimensional chlorophyll fluorescence imaging system according to claim 1, characterized in that: The dual-frequency twelve-step phase-shift fringe image modulated by the plant in the step S4 is represented as: where n = 1, 2,..., 12; and denote the high frequency fringe and the low frequency fringe, and the frequency of the low frequency fringe is set to be less than 1; A(x, y) and B(x, y) represent the background intensity and the modulation intensity, respectively; φ h (x, y) and φ l (x, y) represent the high frequency truncated phase and the low frequency truncated phase, respectively, and can be solved by the following calculation formula: where: high-frequency cut-off phase φ h (x,y) and low-frequency cut-off phase φ l (x,y) are both in the interval [-π,+π); since the frequency of the low-frequency fringes is smaller than 1, the low-frequency cut-off phase φ l (x,y) does not need to be unwrapped, i.e. the low-frequency absolute phase Φ l (x,y) is equal to the low-frequency cut-off phase φ l (x,y); according to the high-frequency absolute phase Φ h (x,y) and the low-frequency absolute phase Φ l (x,y) can be recovered from the mathematical constraint relation between the high-frequency absolute phase Φ h (x,y) as follows: where f h and f l represent the frequency of the high and low frequency fringes, respectively; Round denotes the rounding function; note that the high frequency absolute phase Φ h (x,y) is closely related to the three-dimensional topography of the plant.

7. The structured light vision based three-dimensional chlorophyll fluorescence imaging system for plants of claim 1, wherein: In the step S5, the three-dimensional point cloud is rendered pixel by pixel, that is, the three-dimensional point cloud is colored pixel by pixel using the fluorescence value in the chlorophyll fluorescence image, and the three-dimensional point cloud is colored pixel by pixel using the color value in the three-channel color image.

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