A microalgae density measurement method and system based on lighting source and image analysis

Abstract

The present invention discloses a microalgae density measurement method and system based on an illumination light source and image analysis. The microalgae density measurement method comprises: preprocessing a collected image by an information processing terminal, including operations of unifying the image size and separating RGB channels; calculating and optimizing a scatter plot of nonlinear changes of various clarity calculation-related factors, comprehensive clarity, RGB channel color difference, and comprehensive color difference indicators under conditions of microalgae solutions with different densities, and a nonlinear fitting curve thereof; optimizing the nonlinear fitting curve to improve the correlation between the scatter points and the fitted curve and the smoothness of the curve, taking into account the advantages of the optimal intervals of each algorithm and reducing local anomalies; and performing nonlinear fitting on a scatter plot obtained by testing the optimized comprehensive clarity under conditions of different microalgae densities. The present invention obtains the characteristics of comprehensive color difference and comprehensive clarity through fitting and modeling, and can accurately distinguish the different characteristics of images of microalgae solutions with different densities.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical testing, and in particular relates to a microalgae density measurement method and system based on illumination light source and image analysis. Background Art

[0002] In the field of microalgae cultivation, traditional methods for accurately and rapidly measuring the content of microalgae particles include dry weight, ultrasonic detection, counting, and electrode methods. The dry weight method involves placing a certain volume of suspension in a high-speed centrifuge for solid-liquid separation. The separated precipitate is washed several times and then centrifuged again. The centrifuged particles are then dried at high temperature. The dried particles are then placed in a constant-weight, dry weighing bottle, the mass of the separated particles is measured, and the particle content is calculated. Counting methods are commonly used to measure cell counts, using a cell counter or staining with methylene blue. This method requires microscopic observation and counting, and multiple sample dilutions, which can lead to significant errors. Ultrasonic density detection works by attenuating the energy and amplitude of ultrasound waves as they pass through a suspension due to absorption by the particles. This results in changes in the intensity, velocity, or impedance of the sound before and after the ultrasound is incident. Density is determined by a specific relationship between the change in ultrasound and the intensity of the suspended particles. This principle allows the density of the suspended particles to be measured. However, such instruments are susceptible to changes in fermentation broth composition, bubbles, temperature fluctuations, and viscosity. The electrode method is a standard electrochemical detection method that uses changes in the permittivity between electrodes to measure the density of particles in a suspension. However, this method is typically used to measure the number of viable cells and has certain limitations for detecting all types of suspended microalgae in granular form.

[0003] In addition, microalgae density calculation techniques mainly include microscopic counting, in vivo fluorescence, spectrophotometry, high-performance liquid chromatography, remote sensing, hyperspectral imaging, and microfluidics-based and microfluorescence counting methods. Traditional microscopic techniques require extensive expertise in chemical classification, molecular biology, biochemical analysis, chemical separation and extraction, and instrumentation, resulting in significant limitations and challenges in microalgae density measurement. Remote sensing methods utilize satellite- or drone-borne remote sensing equipment to monitor microalgae density in water bodies over large areas. These methods are suitable for rapid monitoring of large water areas and offer significant advantages in field data collection and large-scale microalgae monitoring. However, the accuracy of test results is susceptible to factors such as weather, cloud cover, aerosols, and water vapor. Microfluidics-based and microfluorescence-based techniques, similar to hyperspectral imaging, can rapidly and accurately count individual microalgae cells. Most of these methods require multiple steps, including sampling of the microalgae solution, sample preparation, sample testing, and data analysis. Among them, water sample collection may cause contamination to the microalgae culture medium, which makes it difficult to meet the requirements of intelligent density monitoring in large-scale microalgae cultivation.

[0004] Image recognition provides a non-contact, intelligent, and environmentally friendly solution for microalgae density monitoring. By analyzing the image features of microalgae solutions and establishing a mapping relationship between these features and microalgae density, it can effectively assist in the development of density recognition algorithms and obtain the calculated density of the algae solution. Currently, image recognition is being combined with traditional experimental equipment such as biological microscopes, remote sensing equipment, and spectrophotometers (near-field imaging), further simplifying traditional testing processes and improving calculation accuracy. Research on imaging techniques and image recognition algorithms for microalgae density calculation under near-field imaging conditions is limited. Research on managing lighting conditions, considering the absorption characteristics of different algae species, and distinguishing properties of different microalgae densities remains limited, resulting in low accuracy in microalgae density calculations under different scenarios. Therefore, a collaborative testing method using a pure-color luminescent light source with adjustable light fields and image recognition under near-field imaging conditions is expected to address the challenges of standardizing microalgae image sample collection, refining microalgae feature extraction, and specifying sample evaluation criteria. This method will help improve the accuracy of microalgae density measurements and is key to developing a fast, accurate, and easy-to-use automatic microalgae density identification system, which will be crucial for large-scale microalgae cultivation, real-time measurement, and monitoring. Summary of the Invention

[0005] The present invention provides a microalgae density measurement method and system based on illumination light source and image analysis. By designing the illumination light source and microalgae density testing method and optimizing the image feature extraction algorithm, the problems of low adjustability and low test accuracy of microalgae density measurement in the prior art are solved.

[0006] To solve the above problems, the present invention provides the following technical solutions:

[0007] An embodiment of the present invention provides a method for measuring microalgae density based on an illumination light source and image analysis, comprising the following steps:

[0008] Step 1: characterize the luminous properties of the LED chip (2), such as driving current, light power, and luminous spectrum; characterize the luminous properties of the light conversion material layer (4), such as light conversion efficiency and luminous spectrum; characterize the density and algae species properties of the microalgae solution to determine the biological properties of the microalgae solution to be tested;

[0009] Step 2: combining and fixing the LED chip (2) and the reflective cup (3) to form an LED lighting device with a specific lighting angle; fixing the light conversion material layer (4) to the cup mouth of the reflective cup (3) to form an LED lighting device that has excitation light, can realize light conversion, emits light of different colors, and the light intensity of the light can be adjusted by current;

[0010] Step 3, using the microalgae solution container to be tested (1) to hold the configured microalgae solution of fixed volume, different algae species, and different densities; placing the microalgae solution container to be tested (1) on the lifting platform (6), adjusting the height and horizontal position of the lifting platform (6), the first bracket (7-1), and the second bracket (7-2) to ensure that the center points of the LED chip (2), the reflective cup (3), the light conversion material layer (4), the microalgae solution container to be tested (1), and the camera of the imaging device (5) are aligned and on the same straight line;

[0011] Step 4, adjusting the camera of the imaging device (5) to ensure that the same focal length and the same aperture are maintained when measuring different microalgae solution samples; ensuring that in the same set of experiments, each time the microalgae solution is measured, the microalgae solution container (1) to be measured is placed at the same vertical and horizontal position on the lifting platform (6); the camera of the imaging device (5) is aimed at the halo passing through the microalgae solution to image, collect representative image data, and transmit it back to the information processing terminal (9);

[0012] Step 5: The information processing terminal (9) pre-processes the collected image, including cutting out the halo core part, unifying the image size, and separating the RGB channels; on this basis, the brightness, clarity, and RGB color difference parameters of the pre-processed image are calculated.

[0013] In an optional embodiment of the present invention, step 5 further includes:

[0014] The selected clarity calculation related factors include: Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor CSE And Canny edge detection factor C CE ; After normalization, the above factors are added according to the set weights to obtain the comprehensive clarity C A ; Comprehensive clarity C A The expression is as follows:

[0015] C A =αC L +βC SSIM +γC LBP +δC G +εC SE +ζC CE ; Among them, α, β, γ, δ,

[0016] ε and ζ are the Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE The weight coefficient of

[0017] RGB color difference calculation method: extract the RGB value of each pixel from the image, and calculate the difference between it and the reference standard color to obtain the color difference of each color channel. Then, perform Euclidean distance calculation based on the preset weight of each channel to finally obtain the comprehensive color difference.

[0018] An optional embodiment of the present invention further includes:

[0019] Step 6: Keep the illumination conditions unchanged, change the microalgae solution of the same species and different density to collect images, and repeat steps 1 to 5; obtain the correlation factors of each clarity calculation and the comprehensive clarity C A , RGB channel color difference, comprehensive color difference index nonlinear changes under different density microalgae solution conditions; comprehensive clarity C A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting to find the optimal nonlinear fitting function;

[0020] Step 7: Optimize the overall clarity C A Nonlinear fitting curves under different microalgae densities improve the correlation and smoothness of the scatter points and fitted curves;

[0021] Step 8: The optimized comprehensive clarity C obtained in step 7 is A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting, and the nonlinear fitting curves under different color illumination conditions were compared;

[0022] Step 9: After testing the microalgae solution with known density, use steps 1 to 8 to perform imaging, image processing, image feature extraction and analysis on the microalgae solution with unknown density to obtain the comprehensive clarity C under different luminous color conditions. B The index of the comprehensive clarity C obtained by referring to the microalgae solution sample with known density A The nonlinear fitting curve of microalgae density was used to obtain the comprehensive clarity C B The corresponding microalgae solution density D B ;

[0023] Step 10, by measuring the comprehensive clarity index of the microalgae sample with known density under different luminous color conditions, and inferring the unknown microalgae density; the accuracy η is D B With D A The absolute value of the difference between A The formula for calculating the microalgae density accuracy η is as follows: η=|D B -D A | / D A , where D A The microalgae density was obtained by the traditional manual counting method.

[0024] Calculate the value of the accuracy rate η of the microalgae density measurement method under different luminescence color conditions; calculate the value of the accuracy rate η of the microalgae density measurement method under different algae species conditions; through the analysis of the accuracy rate η, further optimize the weights of the clarity-related calculation factors for calculating the comprehensive clarity, and improve the final calculated accuracy rate η.

[0025] In an optional embodiment of the present invention, step S7 includes: selecting appropriate clarity calculation correlation factor calculation weights and RGB color difference calculation weights according to the illumination wavelength to obtain a better fitting result of the comprehensive clarity C A Nonlinear fitting curves under different microalgae densities; First, the default weights were used to calculate the comprehensive clarity C A , and plot the comprehensive clarity C A and the relationship curve between the density of microalgae; then, analyze the abnormal points in the curve, and gradually try to reduce the weight of the clarity calculation related factors that cause the abnormalities; for the clarity calculation related factors with good linearity, try to increase their weight appropriately; in this way, gradually adjust the weights of different clarity calculation related factors, and finally make the comprehensive clarity C A There is a good linear correlation between the density of microalgae and the

[0026] In an optional embodiment of the present invention, step S7 calculates the comprehensive clarity C AWhen optimizing the weights of the relevant factors for different clarity calculations, the default weights of the relevant factors for clarity calculations can be adjusted according to the actual curve shape, or some verified weights can be directly used to optimize according to the principle of not expanding local anomalies and giving full play to the advantages of the optimal interval.

[0027] An embodiment of the present invention provides a microalgae density measurement system based on an illumination light source and image analysis, which is used to implement the steps of a microalgae density measurement method based on an illumination light source and image analysis of the above embodiment, characterized in that it comprises a microalgae solution container (1) to be measured, an LED lighting device, an imaging device (5), a lifting platform (6), a first bracket (7-1), a second bracket (7-2), a current source (8) and an information processing terminal (9); the microalgae solution container (1) to be measured is fixed on the top of the lifting platform (6), the first bracket (7-1) and the second bracket (7-2) are arranged on both sides of the lifting platform (6), the LED lighting device is arranged on the top of the first bracket (7-1), and the second bracket (7-2) is arranged on the top of the second bracket (7-1). The imaging device (5) is provided on the top of the frame (7-2), and the LED lighting device and the imaging device (5) are both arranged in alignment with the microalgae solution container (1) to be tested; the LED lighting device is electrically connected to the current source (8), and the imaging device (5) is electrically connected to the information processing terminal (9), and the information processing terminal (9) is used to obtain information from the imaging device (5) and perform calculations and analyses; wherein the LED lighting device includes an LED chip (2), a reflective cup (3), and a light conversion material layer (4) covering the light-emitting surface of the reflective cup (3); the current source (8) supplies power to the LED chip (2) and controls the current of the LED chip (2);

[0028] The microalgae solution container (1) to be tested is used to hold microalgae solutions of different types and densities; the LED chip (2) is used as an excitation light source for the light conversion material; the reflective cup (3) is used to collect the light generated by the LED chip (2), guide the light to pass through the light conversion material layer (4), and excite the light conversion material layer (4) to emit light of a specific wavelength; at the same time, the edge size of the reflective cup (3) matches the edge size of the light conversion material layer (4) and is used to fix the light conversion material layer (4); the lifting platform (6) is used to adjust the microalgae solution to be tested. The vertical height of the algae solution container (1) is such that the halo emitted by the light conversion material layer (4) passes through the central position of the microalgae solution container (1); the imaging device (5) is used to record the halo state of the light emitted by the LED chip (2) after passing through the reflective cup (3) and the light conversion material layer (4) and then passing through the microalgae solution container (1) to be measured; before imaging, the positions of the first bracket (7-1) and the second bracket (7-2) can be adjusted to meet the shooting focal length requirements of the imaging device (5) and achieve the best imaging effect.

[0029] In an optional embodiment of the present invention, the light emitting band of the LED chip (2) is blue light or ultraviolet light, wherein, when the thickness of the microalgae solution container (1) to be tested is relatively thick, a higher-power LED chip can be selected to emit light to ensure that the emitted light has higher penetrability; when the thickness of the microalgae solution container (1) to be tested is relatively thin, a lower-power LED chip can be selected to emit light to ensure that the halo will not be overexposed when imaging the imaging device (5).

[0030] In an optional embodiment of the present invention, the material of the light conversion material layer (4) is any one of the light conversion materials selected from fluorescent powder, quantum dots, perovskites or organic dyes; the reflective cup (3) is made of aluminum or acrylic, and its inner wall has a smooth or rough texture structure; the container for the microalgae solution to be tested (1) is made of transparent acrylic, transparent glass or transparent quartz, and the container for the microalgae solution to be tested (1) is used to store one or more common microalgae such as Navicula, Thalassiosira, Haematococcus pluvialis, and Oocystis.

[0031] In an optional embodiment of the present invention, the imaging device (5) is a camera or a mobile phone, wherein the aperture of the imaging device (5) is adjustable and can be adjusted to the minimum aperture that can just capture the halo at the highest density of the microalgae solution as needed.

[0032] In an optional embodiment of the present invention, the information processing terminal (9) is a desktop computer or a tablet computer, which is used for image processing and analysis; wherein the information processing terminal (9) uses Photoshop, GIMP, Affinity Photo software to perform preliminary processing on videos and images, and to crop the parts of the images with halo characteristics.

[0033] Compared with the prior art, the embodiments of the present invention provide a method and system for measuring microalgae density based on illumination light source and image analysis, which has the following beneficial effects:

[0034] (1) The present invention proposes a microalgae density measurement method and system based on lighting source and image analysis. The microalgae density measurement method uses light as a medium, is contactless, environmentally friendly, and does not require frequent sampling. The density of the microalgae solution can be monitored at different parts of the microalgae cultivation container only by using a mobile testing device, thereby avoiding the contamination of the microalgae solution caused by frequent sampling.

[0035] (2) The present invention can directly use cheap LED lighting devices as light sources, use common imaging devices such as mobile phones as monitoring tools for microalgae density, and use the imaging image centered on the halo of the microalgae solution as the monitoring object. It has the advantages of being simple and easy to test. The test system is portable and can be widely used in various types of microalgae density monitoring occasions.

[0036] (3) The present invention assembles the light source required for the microalgae density test by combining a light conversion material layer with a reflective cup and an LED chip. It has flexible adjustability in the microalgae density test, and a suitable light source combination can be selected from any assembled LED lighting device to assist in microalgae imaging. Compared with the traditional single-luminescence spectrum LED lighting device, the present invention is more suitable for studying the imaging mechanism of microalgae halo images from the perspective of light source-assisted imaging, and is suitable for multiple fields such as scientific research and monitoring.

[0037] (4) The present invention proposes a method for imaging a microalgae solution of known density and extracting image features under the conditions of LED lighting devices with different luminous colors, and further proposes concepts such as comprehensive color difference and comprehensive clarity through fitting and modeling, which can accurately distinguish the different features of the imaging images of microalgae solutions under conditions of different microalgae densities; compared with the traditional method of directly photographing the microalgae solution to obtain an image, this method solves the problem that the imaging features of microalgae solutions under high-density and low-density conditions are not obvious and the distinction is not high.

[0038] (5) The present invention proposes a new method for evaluating the density of microalgae using the concepts of comprehensive color difference and comprehensive clarity. By calculating and optimizing the parameters of comprehensive color difference and comprehensive clarity, the efficiency of image feature extraction of microalgae solutions under high-density and low-density conditions can be improved, and a nonlinear fitting curve that better matches the experimental results can be obtained, thereby solving the problem of inaccurate calculation of microalgae density.

[0039] (6) The present invention proposes a method for calculating the accuracy rate, which can evaluate the accuracy of calculating the density of microalgae using the method of the present invention compared with the traditional counting method under the conditions of different combinations of light conversion materials and LED chips. The accuracy evaluation further clarifies the scope of application of the present invention under different test conditions.

[0040] (7) The testing method of the present invention is simple, easy to operate, low-cost, flexible and adjustable. After a large number of experimental verifications, it has a high test accuracy for the calculation of microalgae density. Therefore, the present invention has certain commercial value. Whether in the fields of marine sewage detection, microalgae solution culture monitoring, or breakthroughs in key technologies of marine visible light sensing, the present invention can support their technical needs and effectively assist in the realization of the "carbon neutrality and carbon peak" goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments or prior arts, the drawings required for use in the embodiments or prior art descriptions will be introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 This is a flow chart of a method for measuring microalgae density based on illumination light source and image analysis provided in an embodiment of the present application.

[0043] Figure 2 This is a schematic diagram of a microalgae density measurement system based on illumination light source and image analysis provided in an embodiment of the present application.

[0044] Figure 3 Schematic diagram of the relationship between the brown algae solution under orange light and the clarity calculation correlation factor provided in the examples of this application.

[0045] Figure 4 Schematic diagram of the brightness change curve of brown algae images of different densities under blue light provided in the embodiment of this application.

[0046] Figure 5 This is the RGB color difference of green algae images of different densities under orange light provided in the embodiments of this application.

[0047] Figure 6This is the RGB color difference of green algae images of different densities under blue light, green light, orange light, and red light provided in the embodiments of this application.

[0048] Figure 7 This is the density calculation accuracy of the brown algae solution provided in the embodiment of this application under different color light conditions. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only 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 those skilled in the art without making creative efforts are within the scope of protection of this application.

[0050] The present invention provides a method and system for measuring microalgae density based on illumination sources and image analysis. This method achieves different light intensities and colors by preparing and packaging a luminous light source, and uses a current source to control the driving current of the luminous light source. A camera is used at a certain distance and the same focal length to collect, process, and analyze images of microalgae halos of different densities, obtaining various characteristics of the images of microalgae halos of different densities under RGB channels, including brightness variation characteristics, color difference variation characteristics, brightness uniformity characteristics, and clarity. Furthermore, the present invention proposes an accuracy algorithm for calculating microalgae density. The accuracy of microalgae density measurements with and without a luminous light source is calculated and analyzed, and compared with the accuracy of microalgae density calculations obtained using traditional measurement methods such as counting methods to evaluate the feasibility and accuracy of the present method. The present invention's method for measuring microalgae density is simple and accurate, ensuring the reliability of microalgae density calculations.

[0051] Specifically, if Figure 1 As shown, an embodiment of the present invention provides a method for measuring microalgae density based on an illumination light source and image analysis, comprising the following steps:

[0052] Step 1: Characterize the luminous properties of the LED chip 2, such as drive current, optical power, and luminous spectrum; characterize the luminous properties of the light conversion material layer 4, such as light conversion efficiency and luminous spectrum; and characterize the density and algae species properties of the microalgae solution to determine the biological properties of the microalgae solution to be tested.

[0053] Step 2: Assemble and fix the LED chip 2 and the reflective cup 3 to form an LED lighting device with a specific lighting angle; fix the light conversion material layer 4 to the cup mouth of the reflective cup 3 to form an LED lighting device that has excitation light, can realize light conversion, emits light of different colors, and the light intensity of the light can be adjusted by current;

[0054] Step 3: Use the microalgae solution container 1 to be tested to hold the prepared microalgae solution of fixed volume, different algae species, and different densities; place the microalgae solution container 1 to be tested on the lifting platform 6, and adjust the height and horizontal position of the lifting platform 6, the first bracket 7-1, and the second bracket 7-2 to ensure that the center points of the LED chip 2, the reflective cup 3, the light conversion material layer 4, the microalgae solution container 1 to be tested, and the camera of the imaging device 5 are aligned and in a straight line;

[0055] Step 4: Adjust the camera of the imaging device 5 to ensure that the same focal length and aperture are maintained when measuring different microalgae solution samples; ensure that the microalgae solution container 1 to be measured is placed in the same vertical and horizontal position on the lifting platform 6 each time the microalgae solution is measured in the same set of experiments; the camera of the imaging device 5 is aimed at the halo of light passing through the microalgae solution to image, collect representative image data, and transmit it back to the information processing terminal 9;

[0056] In step 5, the information processing terminal 9 pre-processes the collected image, including cropping the halo core part, unifying the image size, and separating the RGB channels. On this basis, the brightness, clarity, and RGB color difference parameters of the pre-processed image are calculated.

[0057] Preferably, step 5 further comprises: the selected clarity calculation related factors include: Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE ; After normalization, the above factors are added according to the set weights to obtain the comprehensive clarity C A Comprehensive clarity table C A The expression is as follows:

[0058] C A =αC L +βC SSIM +γC LBP +δC G +εC SE +ζC CE ;

[0059] Among them, α, β, γ, δ, ε, and ζ are the Laplace variance sharpness factors C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SEAnd Canny edge detection factor C CE The weight coefficient of .

[0060] RGB color difference calculation method: extract the RGB value of each pixel from the image, and calculate the difference between it and the reference standard color to obtain the color difference of each color channel. Then, perform Euclidean distance calculation based on the preset weight of each channel to finally obtain the comprehensive color difference.

[0061] Preferably, a method for measuring microalgae density based on illumination light source and image analysis further comprises:

[0062] Step 6: Keep the illumination conditions unchanged, change the microalgae solution of the same species and different density to collect images, and repeat steps 1 to 5; obtain the correlation factors of each clarity calculation and the comprehensive clarity C A , RGB channel color difference, comprehensive color difference index nonlinear changes under different density microalgae solution conditions; comprehensive clarity C A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting to find the optimal nonlinear fitting function;

[0063] Step 7: Optimize the overall clarity C A Nonlinear fitting curves under different microalgae densities improve the correlation between scattered points and fitted curves and the smoothness of the curves;

[0064] Step 8: The optimized comprehensive clarity C obtained in step 7 is A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting, and the nonlinear fitting curves under different color illumination conditions were compared. In the embodiment, a conventional double exponential decay model was mainly used for processing to establish a corresponding relationship between the microalgae density in the solution and the image clarity, thereby realizing the calculation of microalgae density based on image clarity. Similarly, the method of step 7 can be used to calculate the clarity correlation factor (Laplace variance sharpness factor C) in step 6. L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE The same optimization was performed on the fitting curves of indicators such as RGB color difference and comprehensive color difference under different microalgae density conditions.

[0065] Step 9: After testing the microalgae solution with known density, use steps 1 to 8 to perform imaging, image processing, image feature extraction and analysis on the microalgae solution with unknown density to obtain the comprehensive clarity C under different luminous color conditions. BThe index of the comprehensive clarity C obtained by referring to the microalgae solution sample with known density A The nonlinear fitting curve of microalgae density was used to obtain the comprehensive clarity C B The corresponding microalgae solution density D B ;

[0066] Step 10, by measuring the comprehensive clarity index of the microalgae sample with known density under different luminous color conditions, and inferring the unknown microalgae density; the accuracy η is D B With D A The absolute value of the difference between A The formula for calculating the microalgae density accuracy η is as follows: η=|D B -D A | / D A , where D A The microalgae density was obtained by the traditional manual counting method.

[0067] Calculate the values ​​of the test accuracy η of the microalgae density measurement method under different luminescence color conditions; calculate the values ​​of the test accuracy η of the microalgae density measurement method under different algae species conditions; through the analysis of the accuracy η, further optimize the weights of the clarity-related calculation factors for calculating the comprehensive clarity, and improve the final calculated accuracy η.

[0068] Similarly, the calculation formula of the accuracy η can also be used to characterize the correlation factor calculated by clarity (Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE etc.), RGB color difference and comprehensive color difference to calculate the accuracy of unknown microalgae density.

[0069] Preferably, the specific operation of step 7 is as follows: Since the corresponding density intervals of the color difference characterization of microalgae properties by various clarity algorithms and channels are significantly different. For example, Sobel edge detection and Canny edge detection perform better under conditions where the halo edge is more obvious, while Laplace variance often performs better under conditions where the halo is severely diffused. In addition, since the absorption and scattering characteristics of different light sources and luminous spectra are different, which will directly affect the degree of halo diffusion, it is necessary to select appropriate clarity calculation correlation factor calculation weights and RGB color difference calculation weights in accordance with the illumination wavelength to obtain a comprehensive clarity C with a better fitting result. A Nonlinear fitting curves under different microalgae densities. First, the default weights were used to calculate the comprehensive clarity CA , and plot the comprehensive clarity C A Then, analyze the abnormal points in the curve, and try to reduce the weight of the clarity calculation related factors that cause the abnormalities; try to increase the weight of the clarity calculation related factors with good linearity. In this way, gradually adjust the weights of different clarity calculation related factors, and finally make the comprehensive clarity C A A good linear correlation is formed between the density of microalgae and the number of microalgae. Preferably, the entire optimization process can also be implemented through common optimization algorithms such as gradient descent and differential evolution to improve adjustment efficiency and automation.

[0070] Step 7 Calculate the comprehensive clarity C A When optimizing the weights of the relevant factors for different clarity calculations, the default weights of the relevant factors for clarity calculations can be adjusted according to the actual curve shape, or some verified weights can be directly used to optimize according to the principle of not expanding local anomalies and giving full play to the advantages of the optimal interval.

[0071] like Figure 2 As shown, an embodiment of the present invention also provides a microalgae density measurement system based on an illumination source and image analysis, which is used to implement the steps of the microalgae density measurement method based on an illumination source and image analysis described in the above embodiment. The microalgae density measurement system based on an illumination source and image analysis includes a microalgae solution container 1 to be measured, an LED lighting device, an imaging device 5, a lifting platform 6, a first bracket 7-1, a second bracket 7-2, a current source 8, and an information processing terminal 9. The microalgae solution container 1 to be measured is fixed to the top of the lifting platform 6. The first bracket 7-1 and the second bracket 7-2 are disposed on either side of the lifting platform 6. The LED lighting device is disposed on the top of the first bracket 7-1, and the imaging device 5 is disposed on the top of the second bracket 7-2. The LED lighting device and the imaging device 5 are both positioned in alignment with the microalgae solution container 1 to be measured. The LED lighting device is electrically connected to the current source 8, and the imaging device 5 is electrically connected to the information processing terminal 9. The information processing terminal 9 is used to obtain information from the imaging device 5 and perform calculations and analysis. The LED lighting device includes an LED chip 2, a reflective cup 3, and a light conversion material layer 4 covering the light-emitting surface of the reflective cup 3. The current source 8 supplies power to the LED chip 2 and controls the current size of the LED chip 2.

[0072] The microalgae solution container 1 to be tested is used to hold microalgae solutions of different types and densities; the LED chip 2 is used as an excitation light source for the light conversion material; the reflective cup 3 is used to collect the light generated by the LED chip 2, guide the light through the light conversion material layer 4, and excite the light conversion material layer 4 to emit light of a specific wavelength; at the same time, the edge size of the reflective cup 3 matches the edge size of the light conversion material layer 4, and is used to fix the light conversion material layer 4; the lifting platform 6 is used to adjust the vertical height so that the halo emitted by the light conversion material layer 4 passes through the central position of the microalgae solution container 1; the imaging device 5 is used to record the halo state of the light emitted by the LED chip 2 after passing through the reflective cup 3, the light conversion material layer 4 and the microalgae solution container 1; before imaging, the position of the first bracket 7-1 and the second bracket 7-2 can be adjusted to meet the shooting focal length requirements of the imaging device 5 to achieve the best imaging effect.

[0073] The LED chip 2 emits light in the wavelength range of various common short-wavelength excitation light sources, such as blue light and ultraviolet light. The LED chip 2 can be carefully selected to ensure that the light power and light intensity of the LED chip 2 in the illumination light source match those of the microalgae solution container 1 to be tested. If the microalgae solution container 1 to be tested is thick, a higher-power LED chip can be used to ensure greater light penetration. If the microalgae solution container 1 to be tested is thin, a lower-power LED chip can be used to prevent haloing and overexposure in the imaging device 5.

[0074] In order to ensure that the light power, light intensity, and other parameters emitted by the LED chip 2 in the LED lighting device match those of the microalgae solution container 1 to be tested, the current source 8 that drives the LED chip 2 to emit light can be adjusted: if the thickness of the microalgae solution container 1 to be tested is relatively thick, the driving current of the LED chip 2 can be increased through the current source 8 to obtain higher-power light output to ensure higher light penetration; if the thickness of the microalgae solution container 1 to be tested is relatively thin, the driving current of the LED chip 2 can be reduced through the current source 8 to ensure that the light halo does not appear overexposed at the imaging terminal.

[0075] In order to ensure that the parameters such as the light power and light intensity emitted by the LED chip 2 in the LED lighting device match those of the microalgae solution container 1 to be tested, the microalgae solution container 1 to be tested can be selected: if the LED chip 2 has a high light power and a strong light intensity, a microalgae solution container 1 to be tested with a thicker container thickness can be selected to ensure higher light penetration; if the LED chip 2 has a low light power and a weak light intensity, a microalgae solution container 1 to be tested with a thinner container thickness can be selected to ensure that the halo in the imaging of the imaging terminal does not appear to be unable to penetrate or cross the edge.

[0076] The material for the light-conversion material layer 4 can be any of a variety of commonly used light-conversion materials, including phosphors, quantum dots, perovskites, and organic dyes. Phosphors offer relatively stable light emission but a broad spectrum; quantum dots and perovskites offer a single light spectrum and can be used to study the effects of monochromatic light on imaging; and organic dyes can produce light of varying colors but lack high spectral symmetry. The light-conversion material can be selected based on test requirements.

[0077] After the light conversion material layer 4 is determined, the luminescent color can be any one or more within the visible light range. The luminescent color can be controlled and modified based on the synthesis mechanism of the light conversion material layer 4. When using the same LED chip 2 with different light conversion materials 4, the overall color of the illumination source can be modified; when using different LED chips 2 and different light conversion materials 4, the overall color of the illumination source can also be modified. The light conversion material layer 4 of this embodiment is in a thin sheet form to facilitate light transmission through the light conversion material. The thickness of the light conversion material layer 4 is typically approximately 2 to 3 mm, which ensures a certain degree of light transmittance and a high purity of the luminescent color transmitted through the light conversion material. At the same time, the selection of the light conversion material must simultaneously consider its optical properties such as luminescent color, quantum efficiency, and luminous power, as well as its conversion rate and related response speed during the light conversion process, which are related to detection and sensing.

[0078] Among the various light conversion materials used for lighting and display, such as commercial phosphors, organic dyes, perovskites, carbon dots, and quantum dots, quantum dot materials with high quantum efficiency, good monochromaticity, stable luminescence, and fast modulation rate can be selected; taking cadmium selenide quantum dots as an example, it can produce any required luminescence wavelength in the visible light range under blue light or ultraviolet light excitation, and can achieve stable luminescence under high temperature conditions, which meets the requirements of realizing multiple different light conversion wavelengths to test microalgae density in this embodiment.

[0079] The use of quantum dots as light-conversion materials plays a great supporting role in achieving its effects. Compared with other light-conversion materials, the technical advantages of quantum dots include: 1. The luminescence peak of quantum dots is narrow, with a half-peak width ranging from approximately 20 nanometers to 40 nanometers, which helps to avoid the impact of inconsistent absorption coefficients of different bands in microalgae solutions on the experiment; 2. The internal quantum yield of quantum dots can be as high as 90%, with high luminescence intensity, thereby ensuring the stability of the total luminescence intensity; 3. The response speed of quantum dots is higher than that of ordinary commercial phosphors. Their fluorescence lifetime is usually on the order of 10 nanoseconds, while the fluorescence lifetime of commercial phosphors is as long as microseconds, which limits their response speed in light detection. Therefore, when using quantum dots for testing, the test requirements of rapid response can be met; 4. The luminescent color of quantum dots can be conveniently adjusted by controlling the size of quantum dots, the ratio of elements, etc., so the density of microalgae can be tested using continuously changing monochromatic light in the experiment, and this continuously changing test effect cannot be achieved using traditional discrete luminescent peak semiconductor devices such as laser diodes and high-power light-emitting diodes; 5. The luminescent properties of quantum dots are relatively stable in a water-oxygen environment and can withstand high temperatures. They can be paired with high-power LEDs and lasers to produce stable light output, thereby supporting the implementation of the experiment; 6. Compared with materials such as perovskites that have high requirements for non-polar environments, their film-forming properties are poor, and the manufacturing process of quantum dot membranes made of silicone can support quantum dots to be made into various flexible shapes to meet the needs of co-packaging with high-power light-emitting diodes in experiments.

[0080] The reflective cup 3 is made of aluminum or acrylic, with a smooth or rough inner wall. The size and thickness of the test microalgae solution container 1 are adjustable to meet the testing requirements of various light sources. The test microalgae solution container 1 can be made of transparent acrylic, transparent glass, or transparent quartz. For cost and ease of use, transparent acrylic is preferred. The test microalgae solution container 1 is used to store one or more common microalgae species, such as Navicula, Thalassiosira, Haematococcus pluvialis, and Oocystis.

[0081] The imaging device 5 is a camera or mobile phone. Its focal length is adjustable. Adjustment is achieved when the imaging terminal can clearly display an image of a standard light source when no microalgae solution is present. The aperture of the imaging device 5 is adjustable, adjusting it to the minimum aperture that captures the halo of light at the highest density of the microalgae solution. In other embodiments, the imaging device 5 and the information processing terminal 9 can be integrated into a dedicated embedded device, or they can be a separate component of the system, connected via a data cable.

[0082] The fixed positions of the lifting platform 6, first bracket 7-1, and second bracket 7-2 are adjustable; they can be fixed to an optical breadboard or an optical platform using screws. By adjusting the fixed positions of the lifting platform 6, first bracket 7-1, and second bracket 7-2, the illumination distance between the photoconversion material layer 4 and the microalgae solution container 1 to be tested can be adjusted during testing, thereby adjusting the imaging distance of the imaging device 5.

[0083] The horizontal height of the lifting platform 6, the first bracket 7-1, and the second bracket 7-2 is adjustable by adjusting the bracket knob of the lifting platform 6 and the height of the support rods of the first bracket 7-1 and the second bracket 7-2; the height can be selected according to the size of the reflective cup 3, the size of the microalgae solution container 1 to be tested, etc.

[0084] The information processing terminal 9 is a desktop computer or tablet computer used for image processing and analysis. It uses Photoshop, GIMP, or AffinityPhoto software to pre-process videos and images, and automatically crop portions of images with halo characteristics. The information processing terminal 9 can use programs such as Matlab and Python to calculate parameters such as the Laplacian operator and Canny operator. The ambient light intensity during image acquisition is adjustable, and this affects image brightness. Therefore, prior to testing, the ambient light intensity can be set to a certain value and recorded to facilitate comparison and analysis of microalgae density test results under different ambient light intensities.

[0085] In this embodiment, a green quantum dot film and a 450nm blue LED chip are selected to form an LED lighting device, and the LED lighting device is defined as a standard LED lighting device. The density of the standard LED lighting device is 3.15×10 8 , 9.46×10 8 , 2.21×10 9 , 3.47×10 9 , 4.73×10 9 , 5.99×10 9 , 7.88×10 9 The green algae samples with a density of 3.12×10 8 , 4.68×10 8 , 1.24×10 9 , 2.51×10 9 , 3.77×10 9 , 4.99×10 9 , 6.24×10 9The brown algae sample was tested, and the imaging equipment was used to obtain the imaging photos of the microalgae solution under natural light conditions and under the conditions of lighting the LED lighting device, and the comparison was made. The imaging pictures of the microalgae solution under natural light conditions and under the conditions of lighting the LED lighting device were processed to obtain the clarity of the pictures and calculate the correlation factors (Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE etc.), RGB color difference and comprehensive color difference and other indicators.

[0086] Figure 3 The experimental results of Example 1 are as follows: When orange light is used as background light, the relationship curve between the density of the green algae solution and the clarity calculation correlation factor is shown in the figure. The results show that when the Laplace variance sharpness factor C is considered alone, the sharpness factor C is the same as the green algae solution. L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE Or Canny edge detection factor C CE Under the conditions of the six clarity calculation related factors, there are problems such as the clarity value does not change significantly under high density microalgae conditions, and the clarity value changes too quickly and irregularly under low density microalgae conditions. However, after further comprehensive consideration of the Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE By optimizing the corresponding weights for the six clarity-related factors, we can obtain a comprehensive clarity curve with a significant slope change under both high and low microalgae densities. These results demonstrate that the comprehensive clarity curve with optimized weights has significant advantages over other methods for characterizing different microalgae densities.

[0087] Figure 4This is Experimental Result 2 of Example 2: Horizontal brightness variation curve of an image of a brown algae solution using blue light as the background light. The results show that the horizontal brightness of the image of the brown algae solution exhibits a distinct inverted U-shaped variation, with a distinct boundary and a flat brightness distribution in the center. When the microalgae density is low, the horizontal brightness values ​​are higher, and the boundary variation is most pronounced. This is due to the higher light intensity passing through the microalgae solution, which is sensitive to light source boundaries. When the microalgae density is high, the overall horizontal brightness values ​​of the image are lower, and the boundary variation is less pronounced. This is due to the lower light intensity passing through the microalgae solution, which is less sensitive to light source boundaries after scattering. As the microalgae density changes, the overall horizontal brightness decreases unidirectionally as the microalgae density increases. Therefore, the analysis of the horizontal brightness variation in the image effectively characterizes the changing microalgae density.

[0088] Figure 5 Experimental Result 3 of Example 3: RGB color difference curves of an image of a green algae solution using orange light as the background illumination. The results show significant differences in R, G, and B channel color differences. The R channel color difference has the lowest value and shows almost no significant change with microalgae density. The B channel color difference has the highest value and shows a similar trend to the G channel color difference. Both the B and G channel color differences show a linear trend at low microalgae density but tend to saturate at high microalgae density. The differences in R, G, or B channel color differences are due to the different absorption characteristics of algae for different colors of light. In summary, using R, G, or B channel color differences alone cannot effectively represent the linear or nonlinear changes in microalgae density. After calculating the comprehensive color difference, the R, G, or B channel color differences within the comprehensive color difference were optimized to obtain a curve of the comprehensive color difference as a function of microalgae density. The changing trend of comprehensive color difference under different microalgae densities showed that comprehensive color difference could describe the changes of microalgae density linearly and sensitively.

[0089] Figure 6 Example Experiment 4 shows the calculation results of the comprehensive clarity of images of brown algae solutions at different microalgae densities using blue, green, orange, and red light as background illumination, along with the corresponding fitting curves. The results show that the optimized weighted comprehensive clarity effectively describes the changes in microalgae density under different background illumination colors. The fitting curves closely match the resulting scatter plots. In particular, the comprehensive clarity of orange and red light exhibits neither a sharp increase nor a gradual change at either high or low microalgae densities. This indicates that the comprehensive clarity of orange and red light, with their longer wavelengths, performs well in characterizing both high and low microalgae densities.

[0090] Figure 7The experimental result of Example 5 is the average accuracy of density calculation of brown algae solution when using blue light, green light, orange light, and red light as background light. The results show that under the test conditions of any color light, the average accuracy of density calculation of brown algae solution is generally higher than 90%, and the highest accuracy is 98%. Comparing the average accuracy of high-density and low-density microalgae solution samples, it can be found that, except for the results tested under green light conditions, the average accuracy of low-density microalgae solution samples is slightly higher. In general, Figure 7 The results show that the method of the present invention has a high test accuracy under different lighting test conditions and can be well used to evaluate the numerical changes in microalgae density.

[0091] Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed.

[0092] The technical effects and advantages of the present invention are as follows: (1) Technically, the present invention uses conventional quantum dots, phosphors and other materials to prepare light conversion materials with the support of existing technologies, which have the characteristics of high stability and easy preparation. (2) Technically, the present invention uses captured images as the monitoring object for feedback of microalgae density under the premise of LED lighting devices, which has the advantages of simple operation and high accuracy. The light source halo contained in the captured image has rich image features and can generate timely feedback on the real-time changes in microalgae density. The image obtained by the imaging terminal can directly reflect the dynamic changes in microalgae density without sampling, and the observation is convenient and accurate. (3) Theoretically, the present invention proposes a method for imaging microalgae solutions of known density and extracting image features under the conditions of LED lighting devices with different luminous colors, and further proposes through fitting and modeling the concepts of comprehensive color difference, comprehensive clarity, etc., which can accurately distinguish the different features of microalgae solution imaging images under different microalgae densities. Compared with the traditional method of directly shooting microalgae pictures, this method solves the problem that the image features of microalgae solutions under high-density and low-density conditions are not obvious and the distinction is not high. (4) In theory, the present invention proposes a new method for evaluating the density of microalgae using concepts such as comprehensive color difference and comprehensive clarity. By calculating and optimizing parameters such as comprehensive color difference and comprehensive clarity, the efficiency of image feature extraction of microalgae solutions under high-density and low-density conditions can be improved, and a nonlinear fitting curve that better matches the experimental results can be obtained, thereby solving the problem of inaccurate microalgae density evaluation. (5) In theory, the present invention proposes a method for calculating the accuracy of microalgae density by comparing different light conversion materials and LED chip combinations using parameters such as image color difference and clarity. The universality of the present invention can be evaluated under conditions such as different algae species, different imaging equipment, light conversion material types, and LED chip types. (6) The present invention is technically feasible, and after the technology of the present invention matures, it can be used for marine environmental monitoring. Under outdoor test conditions, all test instruments involved in the present invention can be used for underwater detection after being waterproofed. (7) The function of the present invention is not only applicable to monitoring the density of a single microalgae species, but also to monitoring the density of multiple microalgae.

[0093] In addition, the following important aspects serve as supporting evidence for the novelty of the present invention:

[0094] The expected benefits and commercial value of the present invention after transformation are as follows: a. In marine sewage treatment, it is usually necessary to analyze the composition and characteristics of microalgae suspension in seawater sample suspensions. The method of combining lighting source and image analysis to obtain the density of microalgae suspension under different light source conditions can effectively evaluate the quality of seawater from the perspective of optical testing. b. At present, the cultivation of functional microalgae has occupied a certain market share nationwide. At the same time, the cultivation and monitoring of microalgae are also developing in the direction of intelligent suspension solution monitoring and evaluation. The microalgae density evaluation mechanism based on lighting source regulation proposed in the present invention can provide convenient technical support for this process. c. When light passes through different types of marine microalgae, the microalgae have different optical processes such as absorption and reflection of different colors of light. According to the above mechanism, the light transmission process of microalgae can be studied and analyzed by combining lighting source and image analysis, and further develop new optical equipment for testing the optical properties of microalgae solutions. In summary, whether from the aspects of marine sewage treatment, microalgae solution cultivation monitoring, or the key technologies for the development of new optical equipment related to microalgae, the present invention can effectively meet the technical needs;

[0095] This invention fills a technological gap in the industry, both domestically and internationally: current research focuses on microscopic measurement of microalgae density and remote sensing measurement of microalgae distribution density, while research on optical measurement of microalgae density under near-field light distribution conditions is limited. Compared to traditional microalgae density measurement methods, which require multiple steps, including sample collection, testing, calculation, and storage, this invention offers simplicity, efficiency, and the flexibility to change light sources when monitoring microalgae density.

[0096] Does the technical solution of the present invention solve the current technical problem: People have always hoped to obtain a reliable, accurate, fast, and suitable density monitoring device for different marine microalgae for use in seawater monitoring, microalgae cultivation monitoring and other fields. In the present invention, this problem is solved.

[0097] Does the technical solution of this invention overcome technological bias? Traditionally, microalgae density measurement relies on specialized instruments such as microscopes and photometers. However, the present invention proposes a low-cost, simple-to-use, and flexible microalgae density measurement system and method. The system allows for adjustment of test distance, test angle, test light power, and imaging focal length based on the thickness of the microalgae solution container. Compared to existing microscopic and dry weight testing methods, this method offers a simpler and more flexible testing system. Compared to existing spectrophotometric testing methods, this method utilizes more intuitive image display technology and more comprehensive image analysis methods.

[0098] Obviously, the above embodiments of the present invention are merely examples for the purpose of clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the claims of the present invention.

[0099] In summary, although the present invention has been disclosed above with reference to preferred embodiments, the above preferred embodiments are not intended to limit the present invention. A person skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be based on the scope defined in the claims.

Claims

1. A method for measuring microalgae density based on illumination light source and image analysis, characterized in that: The following steps are involved: Step 1, characterizing the luminous properties of the LED chip (2), including driving current, optical power, and luminous spectrum; Characterizing the luminescent properties of the light conversion material layer (4), including light conversion efficiency and luminescent spectrum; Characterize the density and algae species properties of the microalgae solution to determine the biological properties of the microalgae solution to be tested; Step 2, combining and fixing the LED chip (2) and the reflective cup (3) to form an LED lighting device with a specific lighting angle; fixing the light conversion material layer (4) to the cup mouth of the reflective cup (3) to form an LED lighting device that has excitation light, can realize light conversion, emits light of different colors, and the light intensity of which can be adjusted by current; Step 3, using the microalgae solution container to be tested (1) to hold the configured microalgae solution of fixed volume, different algae species, and different densities; placing the microalgae solution container to be tested (1) on the lifting platform (6), adjusting the height and horizontal position of the lifting platform (6), the first bracket (7-1), and the second bracket (7-2) to ensure that the center points of the LED chip (2), the reflective cup (3), the light conversion material layer (4), the microalgae solution container to be tested (1), and the camera of the imaging device (5) are aligned and on the same straight line; Step 4, adjusting the camera of the imaging device (5) to ensure that the same focal length and the same aperture are maintained when measuring different microalgae solution samples; ensuring that in the same set of experiments, each time the microalgae solution is measured, the microalgae solution container (1) to be measured is placed at the same vertical and horizontal position on the lifting platform (6); the camera of the imaging device (5) is aimed at the halo passing through the microalgae solution to image, collect representative image data, and transmit it back to the information processing terminal (9); In step 5, the information processing terminal (9) pre-processes the collected image, including cutting out the core part of the halo, unifying the image size, and separating the RGB channels; on this basis, the brightness, clarity, and RGB color difference parameters of the pre-processed image are calculated.

2. The microalgae density measurement method based on illumination light source and image analysis according to claim 1, characterized in that: Step 5 also includes: The selected clarity calculation related factors include: Laplace variance sharpness factor C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE ; After normalization, the above factors are added according to the set weights to obtain the comprehensive clarity C A ; Comprehensive clarity C A The expression is as follows: C A =αC L +βC SSIM +γC LBP +δC G +εC SE +ζC CE ; Among them, α, β, γ, δ, ε, ζ are the Laplace variance sharpness factors C L , structural similarity index factor C SSIM , local binary clarity factor C LBP , Gaussian blur factor C G , Sobel edge detection factor C SE And Canny edge detection factor C CE The weight coefficient of RGB color difference calculation method: extract the RGB value of each pixel from the image, and calculate the difference between it and the reference standard color to obtain the color difference of each color channel. Then, perform Euclidean distance calculation based on the preset weight of each channel to finally obtain the comprehensive color difference.

3. The method for measuring microalgae density based on illumination light source and image analysis according to claim 2, characterized in that: Also includes: Step 6: Keep the illumination conditions unchanged, change the microalgae solution of the same species and different density to collect images, and repeat steps 1 to 5; obtain the correlation factors of each clarity calculation and the comprehensive clarity C A , RGB channel color difference, comprehensive color difference index nonlinear changes under different density microalgae solution conditions; comprehensive clarity C A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting to find the optimal nonlinear fitting function; Step 7: Optimize the overall clarity C A Nonlinear fitting curves under different microalgae densities improve the correlation and smoothness of the scatter points and fitted curves; Step 8: The optimized comprehensive clarity C obtained in step 7 is A The scatter plots obtained under different microalgae density conditions were subjected to nonlinear fitting, and the nonlinear fitting curves under different color illumination conditions were compared; Step 9: After testing the microalgae solution with known density, use steps 1 to 8 to perform imaging, image processing, image feature extraction and analysis on the microalgae solution with unknown density to obtain the comprehensive clarity C under different luminous color conditions. B The index of the comprehensive clarity C obtained by referring to the microalgae solution sample with known density A The nonlinear fitting curve of microalgae density was used to obtain the comprehensive clarity C B The corresponding microalgae solution density D B ; Step 10, by measuring the comprehensive clarity index of the microalgae sample with known density under different luminous color conditions, and inferring the unknown microalgae density; the accuracy η is D B With D A The absolute value of the difference between A The formula for calculating the microalgae density accuracy η is as follows: η=|D B -D A | / D A , where D A The microalgae density was obtained by the traditional manual counting method. Calculate the value of the accuracy rate η of the microalgae density measurement method under different luminescence color conditions; calculate the value of the accuracy rate η of the microalgae density measurement method under different algae species conditions; through the analysis of the accuracy rate η, further optimize the weights of the clarity-related calculation factors for calculating the comprehensive clarity, and improve the final calculated accuracy rate η.

4. The method for measuring microalgae density based on illumination light source and image analysis according to claim 3, characterized in that: Step S7 includes: selecting appropriate clarity calculation correlation factor calculation weights and RGB color difference calculation weights according to the illumination wavelength to obtain a better fitting result of comprehensive clarity C A Nonlinear fitting curves under different microalgae densities; First, the default weights were used to calculate the comprehensive clarity C A , and plot the comprehensive clarity C A and the relationship curve between the density of microalgae; then, analyze the abnormal points in the curve, and gradually try to reduce the weight of the clarity calculation related factors that cause the abnormalities; for the clarity calculation related factors with good linearity, try to increase their weight appropriately; in this way, gradually adjust the weights of different clarity calculation related factors, and finally make the comprehensive clarity C A There is a good linear correlation between the density of microalgae and the 5. The method for measuring microalgae density based on illumination light source and image analysis according to claim 4, characterized in that: Step S7 calculates the comprehensive clarity C A When optimizing the weights of the relevant factors for different clarity calculations, the default weights of the relevant factors for clarity calculations are adjusted according to the actual curve shape, or some verified weights are directly used, and the optimization is carried out in accordance with the principle of not expanding local anomalies and giving full play to the advantages of the optimal interval.

6. A microalgae density measurement system based on illumination light source and image analysis, used to implement the steps of the microalgae density measurement method based on illumination light source and image analysis according to any one of claims 1 to 5, characterized in that: The invention comprises a container for a microalgae solution to be tested (1), an LED lighting device, an imaging device (5), a lifting platform (6), a first bracket (7-1), a second bracket (7-2), a current source (8) and an information processing terminal (9); the container for a microalgae solution to be tested (1) is fixed on the top of the lifting platform (6); the first bracket (7-1) and the second bracket (7-2) are arranged on both sides of the lifting platform (6); the LED lighting device is arranged on the top of the first bracket (7-1); the imaging device (5) is arranged on the top of the second bracket (7-2); the LED lighting device and the imaging device The devices (5) are all arranged in alignment with the microalgae solution container (1) to be tested; the LED lighting device is electrically connected to the current source (8), and the imaging device (5) is electrically connected to the information processing terminal (9), and the information processing terminal (9) is used to obtain information from the imaging device (5) and perform calculations and analyses; wherein the LED lighting device includes an LED chip (2), a reflective cup (3), and a light conversion material layer (4) covering the light-emitting surface of the reflective cup (3); the current source (8) supplies power to the LED chip (2) and controls the current of the LED chip (2); The microalgae solution container (1) is used to hold microalgae solutions of different types and densities; the LED chip (2) is used as an excitation light source for the light conversion material; the reflective cup (3) is used to collect the light generated by the LED chip (2), guide the light to pass through the light conversion material layer (4), and excite the light conversion material layer (4) to emit light of a specific wavelength; at the same time, the edge size of the reflective cup (3) matches the edge size of the light conversion material layer (4) and is used to fix the light conversion material layer (4); the lifting platform (6) is used to adjust the microalgae solution container (1) to contain ... to excite the light conversion material; the reflective cup (3) is used to collect the light generated by the LED chip (2), guide the light to pass through the light conversion material layer (4), and excite the light conversion material layer (4) to emit light of a specific wavelength; at the same time, the reflective cup (3) is used to adjust the edge size of the reflective cup (3) to match the edge size of the light conversion material layer (4) The vertical height of the algae solution container (1) is such that the halo emitted by the light conversion material layer (4) passes through the central position of the microalgae solution container (1); the imaging device (5) is used to record the halo state of the light emitted by the LED chip (2) after passing through the reflective cup (3) and the light conversion material layer (4) and then passing through the microalgae solution container (1) to be measured; before imaging, the positions of the first bracket (7-1) and the second bracket (7-2) can be adjusted to meet the shooting focal length requirements of the imaging device (5) and achieve the best imaging effect.

7. The microalgae density measurement system based on illumination light source and image analysis according to claim 6, characterized in that: The light emitting wavelength band of the LED chip (2) is blue light or ultraviolet light, wherein, when the thickness of the microalgae solution container (1) to be tested is relatively thick, a high-power LED chip can be selected to emit light to ensure that the emitted light has high penetrability; when the thickness of the microalgae solution container (1) to be tested is relatively thin, a low-power LED chip can be selected to emit light to ensure that the halo in the imaging of the imaging device (5) will not be overexposed.

8. The microalgae density measurement system based on illumination light source and image analysis according to claim 7, characterized in that: The material of the light conversion material layer (4) is any one of the light conversion materials selected from fluorescent powder, quantum dots, perovskite or organic dyes; the reflective cup (3) is made of aluminum or acrylic, and its inner wall has a smooth or rough texture structure; the container for the microalgae solution to be tested (1) is made of transparent acrylic, transparent glass or transparent quartz, and the container for the microalgae solution to be tested (1) is used to store one or more algae selected from Navicula, Thalassiosira, Haematococcus pluvialis and Oocystis.

9. The microalgae density measurement system based on illumination light source and image analysis according to claim 8, characterized in that: The imaging device (5) is a camera or a mobile phone, wherein the aperture of the imaging device (5) is adjustable and can be adjusted to the minimum aperture that can just capture the halo at the highest density of the microalgae solution as needed.

10. The microalgae density measurement system based on illumination light source and image analysis according to claim 9, characterized in that: The information processing terminal (9) is a desktop computer or a tablet computer, and is used for image processing and analysis; wherein the information processing terminal (9) uses Photoshop, GIMP, and Affinity Photo software to perform preliminary processing on videos and images, and to crop portions of the images that have halo characteristics.

Images