Aquatic organism detection system, method and device

Abstract

This specification discloses an aquatic organism detection system, method, and device. The aquatic organism detection system includes: a detection tube, an optical microscope, a digital camera, and an embedded computer. The detection tube includes a tube wall and a base, with multiple support structures disposed between the tube wall and the base. The digital camera, optical microscope, and embedded computer are disposed within the enclosed space formed by the tube wall. A sampling channel is placed within a flowable natural water body, and the natural water flows through the sampling channel through the gaps between the support structures. The optical microscope is used to magnify organisms in the natural water body to obtain microscopic images. The digital camera is used to digitally capture the microscopic images and send the captured biological images to the embedded computer. The embedded computer is used to input the biological images into a target detection model to determine the detection results, which include the category and movement trajectory of the aquatic organisms. This solution improves the accuracy of the detection results.

Description

Technical Field

[0001] This specification relates to the field of biological collection technology, and in particular to an aquatic organism detection system, method, and device. Background Art

[0002] Aquatic biological monitoring, as an important basis for evaluating water ecological environment quality, can supplement the limitations of traditional water quality physical and chemical monitoring that cannot reflect the biological effects of pollution.

[0003] Plankton are the core of lake ecosystems, occupying a crucial position in the investigation and research of aquatic biological ecology and playing a central role in biogeochemical and carbon cycles. Plankton are mostly small, short-lived, and highly sensitive to environmental conditions, making their diversity and abundance highly effective indicators of environmental change and ecosystem health.

[0004] However, labor-intensive sampling and microscopy are currently commonly used to detect the diversity and richness of plankton in water bodies. During this process, multiple samples need to be taken manually in the water body and observed through a microscope. The detection process is too dependent on the experience of the observer, is highly subjective, and requires a lot of manpower and time costs. In addition, the plankton in the water body is likely to die during the sample collection and storage process, which seriously affects the accuracy of the test results. Summary of the Invention

[0005] This specification provides an aquatic organism detection system, method and device to solve the above-mentioned problems existing in the prior art.

[0006] This manual adopts the following technical solutions:

[0007] An aquatic organism detection system, comprising: a detection tube, an optical microscope, a digital camera, and an embedded computer;

[0008] The detection cylinder includes a cylinder wall and a base, with multiple retractable support structures disposed between the cylinder wall and the base. The area between the cylinder wall and the base forms a sampling channel supported by the multiple support structures. The digital camera, the optical microscope, and the embedded computer are disposed in the enclosed space formed by the cylinder wall. The sampling channel is placed in a flowing natural water body, and the natural water flows through the sampling channel through the gaps between the support structures.

[0009] The digital camera is used to digitally capture the microscopic image obtained by the optical microscope and send the captured biological image to the embedded computer;

[0010] The embedded computer includes a target detection module and a trajectory generation module. The target detection module is used to perform target detection on the biological image through a preset target detection model to obtain detection results for aquatic organisms in the natural water body; the trajectory generation module is used to generate a motion trajectory of each aquatic organism according to the detection results through a preset trajectory generation model.

[0011] Optionally, the aquatic organism detection system is provided with: a thermal sensor;

[0012] The thermal sensor is arranged in the sampling channel, and is used to receive the heating signal generated by the embedded computer according to the temperature of the natural water body when the temperature of the natural water body is lower than the preset active temperature of aquatic organisms, and heat the natural water body according to the heating signal; and collect the temperature of the natural water body and send it to the embedded computer.

[0013] Optionally, the multiple retractable support structures are used to adjust the height of the sampling channel.

[0014] Optionally, the aquatic organism detection system is provided with: lighting equipment;

[0015] The lighting device is arranged at a designated position in the sampling channel, and is used to provide an illumination light source for the optical microscope and the digital camera;

[0016] The digital camera is used to digitally capture the microscopic image under the illumination light source provided by the illumination device.

[0017] Optionally, the optical microscope and the digital camera are respectively provided in plurality, and optical microscopes with different configuration parameters are combined with digital cameras with different configuration parameters;

[0018] The configuration parameters of the optical microscope include at least magnification and working distance, and the configuration parameters of the digital camera include at least zoom ratio.

[0019] Optionally, the aquatic organism detection system is further provided with: a power supply, a power management device and a solar energy collection device;

[0020] The solar energy collection device is arranged on the barrel cover of the detection barrel and is connected to the power management device;

[0021] The power management device is used to process the energy collected by the solar energy collection device and provide it to the power supply;

[0022] The power supply is used to supply power to the digital camera and the embedded computer.

[0023] This specification provides a method for detecting aquatic organisms, the method comprising:

[0024] processing the received biological image to obtain a processed biological image;

[0025] The processed biological image is input into a preset target detection model to determine the detection results for aquatic organisms in the natural water body through the target detection model, and the motion trajectory of each aquatic organism is generated according to the detection results through a preset trajectory generation model, and the detection results and the motion trajectory are sent to the client.

[0026] Optionally, processing the received biological image specifically includes:

[0027] Performing defogging processing on the biological image to obtain candidate images;

[0028] The clarity corresponding to each candidate image is determined, and candidate images with clarity lower than a threshold are deleted to obtain the processed biological image.

[0029] Optionally, the biological image is a microscopic image digitally captured and transmitted by a digital camera, and the microscopic image is obtained by magnifying the organisms in natural water bodies using an optical microscope;

[0030] Determining the test results for aquatic organisms in the natural water body, specifically including:

[0031] For each moment, if there are at least two biological images captured by digital cameras at that moment, then the biological images captured by each digital camera at that moment are processed respectively to obtain processed images;

[0032] Inputting the processed images into the target detection model respectively to obtain intermediate results;

[0033] The intermediate results are integrated to obtain the detection results for the aquatic organisms in the natural water body.

[0034] This specification approves an aquatic organism detection device, comprising:

[0035] A processing module, configured to process the received biological image to obtain a processed biological image;

[0036] A determination module is used to input the processed biological image into a preset target detection model to determine the detection results for aquatic organisms in the natural water body through the target detection model, and to generate a motion trajectory of each aquatic organism according to the detection results through a preset trajectory generation model, and to send the detection results and the motion trajectory to the client.

[0037] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned aquatic organism detection method.

[0038] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned aquatic organism detection method when executing the program.

[0039] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects:

[0040] The aquatic organism detection system provided in this specification includes: a detection tube, an optical microscope, a digital camera and an embedded computer; the detection tube includes a tube wall and a base, a plurality of supporting structures are arranged between the tube wall and the base, and the area between the tube wall and the base forms a sampling channel supported by the plurality of supporting structures; the digital camera and the embedded computer are arranged in a closed space formed by the tube wall; the sampling channel is placed in a flowable natural water body, and the natural water body flows through the sampling channel through the gaps between the supporting structures; the optical microscope is used to magnify the organisms in the natural water body and obtain a microscopic image; the digital camera is used to digitally capture the microscopic image and send the captured biological image to the embedded computer; the embedded computer is used to process the received biological image to obtain detection results for aquatic organisms in the natural water body.

[0041] From the above content, it can be seen that this solution places the sampling channel of the aquatic organism detection system in a flowing natural water body, and uses a microscope and a digital camera to collect real-time images of the water flowing through the sampling channel, and then performs image processing based on the built-in embedded computer to obtain the final detection results. The entire process does not require human intervention, realizes the automated detection of aquatic organisms, improves detection efficiency, reduces labor costs, and effectively avoids the death of plankton in the water body during sample collection and preservation, thereby improving the accuracy of aquatic organism detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The exemplary embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation of this specification. In the drawings:

[0043] Figure 1 A schematic diagram of an aquatic organism detection system provided in this manual;

[0044] Figure 2 A schematic diagram of a lighting device provided for this manual;

[0045] Figure 3 Schematic diagram of the external structure of the aquatic organism detection system provided in this manual;

[0046] Figure 4 A schematic diagram of a process for detecting aquatic organisms provided in this manual;

[0047] Figure 5 A schematic diagram of an aquatic organism detection device provided in this manual;

[0048] Figure 6 This specification provides a method for applying the above Figure 4 Schematic diagram of electronic equipment. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of this specification more clear, the following will clearly and completely describe the technical solutions of this specification in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this specification.

[0050] The technical solutions provided by the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0051] Figure 1 This is a schematic diagram of an aquatic organism detection system provided in this specification. The aquatic organism detection system is provided with a detection tube, an optical microscope 1, a digital camera 2 and an embedded computer 3.

[0052] like Figure 1 As shown, the detection cylinder of the aquatic organism detection system includes a cylinder cover, a cylinder wall 4 and a base 5. A plurality of retractable support structures 6 are arranged between the cylinder wall 4 and the base 5. The area between the cylinder wall 4 and the base 5 forms a sampling channel 7 under the support of the plurality of support structures 6. When detecting aquatic organisms, the sampling channel 7 can be placed in a flowable natural water body, and the natural water body can flow through the sampling channel 7 through the gaps between the support structures 6.

[0053] The multiple retractable support structures 6 are used to adjust the height of the sampling channel 7. Since the depths of different water bodies vary, to ensure that the optical microscope 1 and the digital camera 2 can capture clear images within their adapted working areas, the sampling channel 7 can be adjusted to a suitable height and secured by adjusting the support structures 6 when the aquatic organism detection system is placed in the water body.

[0054] For example, for deeper water bodies, the support structure 6 can be adjusted to a higher height, while for shallower water bodies, the support structure 6 can be adjusted to a lower height, thereby achieving clear images being captured in the water body regardless of whether it is in deep water areas or in shallow water areas.

[0055] Among them, a corresponding limiting device (such as a slot, bolt, pin, cam mechanism, etc.) can be set at a designated position of each supporting structure. In this way, when the supporting structure is adjusted to a suitable height, it can be fixed by the limiting device to prevent it from slipping.

[0056] Of course, in practical applications, the above-mentioned multiple support structures may also be fixed support structures.

[0057] It should be pointed out that the aquatic organisms detected by the aquatic organism detection system in this specification can be plankton, and of course, can also be other aquatic organisms such as algae, aquatic plants, etc., whose images can be captured by the digital camera 2 and the optical microscope 1. This specification does not make specific restrictions on this.

[0058] The supporting structure 6 may be a supporting rod or a supporting column, or other supporting objects with gaps, which is not specifically limited in this specification.

[0059] The optical microscope 1 is arranged in the sampling channel 7 between the cylinder wall 4 and the base 5 of the detection cylinder, and is used to magnify the organisms in the natural water body to obtain a microscopic image.

[0060] Furthermore, the aquatic life detection system may also be provided with: a thermal sensor 13 .

[0061] The thermal sensor can be arranged in the sampling channel 7 and installed at the bottom of the closed area formed by the cylinder wall 4, and connected to the embedded computer 3 and the power supply 9 respectively to realize signal transmission between the embedded computer 3 and the power supply 9.

[0062] Of course, in actual applications, the thermal sensor can also be set at other positions in the sampling channel 7, such as being installed on the upper part of each supporting structure, and this specification does not make specific limitations on this.

[0063] Thermal sensor 13 collects the temperature of the natural water body in real time and transmits it to embedded computer 3. When the embedded computer determines that the current water temperature is lower than the preset activation temperature of aquatic organisms, it generates a heating signal and transmits it to thermal sensor 13. The activation temperature of aquatic organisms can be set based on actual conditions and is not specifically limited in this specification.

[0064] After receiving the heating signal, the thermal sensor 13 can heat the natural water body according to the heating signal, thereby heating the water body in the sampling channel 7 to the active temperature of aquatic organisms, so as to facilitate the identification of their movement trajectory.

[0065] The digital camera 2 and the optical microscope 1 are arranged in a closed area formed by the cylinder wall 4 and connected to the optical microscope 1 for collecting the above-mentioned microscopic images.

[0066] In this specification, the aquatic life detection system may be provided with a plurality of optical microscopes 1 with different configuration parameters and a plurality of digital cameras 2 with different configuration parameters, and the optical microscopes 1 with different configuration parameters are combined with the digital cameras 2 with different configuration parameters.

[0067] The configuration parameters of the optical microscope 1 may include at least: magnification and working distance (e.g. Figure 1 The configuration parameters of the digital camera 2 may include at least a zoom factor. The working distance represents the distance at which the optical microscope 1 can clearly observe the target object. Specifically, when the target object is within the working distance, the optical microscope 1 can clearly observe the target object.

[0068] In this specification, optical microscopes 1 and digital cameras 2 with different parameters can be combined. For example, for each optical microscope 1, the greater the magnification of the optical microscope 1, the smaller the zoom factor of the digital camera 2 connected to the optical microscope 1, and vice versa. The smaller the magnification of the optical microscope 1, the larger the zoom factor of the digital camera 2 connected to the optical microscope 1. This allows for the realization of digital camera 2-optical microscope 1 combinations with different configuration parameters.

[0069] Of course, in actual applications, the configuration parameters of the optical microscope 1 may also include aperture, working distance, correction ring, etc., and the configuration parameters of the digital camera 2 may also include resolution, contrast, depth of field, etc., which are not specifically limited in this specification.

[0070] It should be added that, in this specification, one optical microscope 1 can be connected to one digital camera 2 . Of course, one digital camera 2 can also be connected to multiple optical microscopes 1 to simultaneously capture microscopic images of multiple optical microscopes 1 .

[0071] In addition, the aquatic organism detection system can also be provided with: a lighting device 8, which is set at a designated position in the sampling channel 7, and is used to provide a lighting source for the optical microscope 1 and the digital camera 2. In this way, the digital camera 2 can capture microscopic images under the lighting source provided by the lighting device 8.

[0072] For example, the lighting device 8 can be set at the bottom of the cylinder wall 4 to illuminate the water body from top to bottom at a certain angle, or the lighting device 8 can be set on the base 5 to illuminate the water body from bottom to top at a certain angle. Of course, the lighting device 8 can also be set in the middle position of the sampling channel 7 to illuminate the water body with parallel light.

[0073] In practical applications, the lighting device 8 may be a light strip provided with a plurality of light beads, which is arranged in a ring around the support structure 6 (support rod) between the cylinder wall 4 and the base 5, and illuminates the imaging area in the sampling channel 7 at a certain angle.

[0074] For ease of understanding, this specification provides a schematic diagram of a lighting device 8, such as Figure 2 shown.

[0075] The lighting device 8 is a ring-shaped light strip that illuminates the sampling channel 7 from top to bottom at a 45° angle. A wire slot is provided at the bottom of each lamp bead for connecting all lamp beads in parallel. The wire slot is connected to the power supply 9 of the aquatic life detection system to supply power through the power supply 9.

[0076] Furthermore, the digital camera 2 is connected to the embedded computer 3 provided in the cylinder wall 4 . When the digital camera 2 captures a biological image, the captured biological image is sent to the embedded computer 3 .

[0077] In practical applications, a certain sampling interval can be set in advance for the digital camera 2 , and then the digital camera 2 can collect the biological image observed by the optical microscope 1 according to the sampling interval.

[0078] The embedded computer 3 includes a target detection module and a trajectory generation module. The target detection module is used to perform target detection on biological images using a preset target detection model to obtain detection results for aquatic organisms in natural water bodies; the trajectory generation module is used to generate the movement trajectory of each aquatic organism according to the detection results using a preset trajectory generation model.

[0079] The detection results include: the category and posture of the aquatic organism. For each aquatic organism, the motion trajectory of the aquatic organism is generated according to the posture of the aquatic organism in each frame of the organism image.

[0080] In this specification, the target detection module and trajectory generation module can be two hardware modules provided in an embedded computer. Of course, they can also be two software modules implemented by algorithms in the embedded computer. This specification does not make any specific limitations on this.

[0081] The process of processing the biological image by the embedded computer 3 will be described in detail below, and this specification will not go into details here.

[0082] Furthermore, the aquatic organism detection system may be provided with a network device for providing a network signal to the embedded computer 3, so that the embedded computer 3 uses the network signal to send the detection results to the client. The network signal provided by the network device may include 3G, 4G, 5G, and WIFI signals, etc., which are not specifically limited in this specification.

[0083] In addition, the aquatic life detection system is further provided with: a power supply 9, a power management device 10 and a solar energy collection device. The power supply 9 is used to supply power to the lighting device 8, the digital camera 2 and the embedded computer 3.

[0084] The solar energy collection device is arranged on the barrel cover 11 of the detection barrel and is connected to the power management device 10 . The power management device 9 is used to process the energy collected by the solar energy collection device and store it in the power supply 9 .

[0085] The barrel cover 11 of the detection barrel may be provided with a line management port 12 , and the power line 9 of the power management device 10 may pass through the line management port 12 and be connected to the solar energy collection device.

[0086] Furthermore, the aquatic life detection system is further provided with a controller, which is connected to the digital camera 2 via a multi-core cable and is used to control the digital camera 2 .

[0087] The embedded computer 3 has built-in software modules, which include support components and a user interface. The support components include a motion control software module that interacts with the controller and an image acquisition module that interacts with the digital camera 2, as well as an image selection and preprocessing module, a recognition and statistical algorithm module, a gallery and a database.

[0088] The digital camera 2 is controlled by the image acquisition module and provides biological images to the software module. The database is used to store the biological images.

[0089] For ease of understanding, this specification provides a schematic diagram of the external structure of an aquatic organism detection system, such as Figure 3 shown.

[0090] Among them, the cylinder wall 4 of the detection cylinder can be composed of a first cylinder wall 41 and a second cylinder wall 42, wherein the embedded computer 3, digital camera 2, optical microscope 1, power supply 9, power management device 10 and network equipment can be respectively arranged in the first cylinder wall 41 and the second cylinder wall 42 which have been waterproofed according to space requirements and line layout.

[0091] The sampling channel 7 between the base 5 and the second cylinder wall 42 may be provided with an annular lighting device 8 to provide an illumination light source for the sampling channel 7 .

[0092] It should be noted that, in actual applications, the cylinder wall 4 may also be composed of a part, and the number of lighting devices 8 in the sampling channel 7 may be only one or multiple.

[0093] In one embodiment provided herein, the heights of the first and second cylinder walls 41, 42 are both 17.5 cm, the height of the sampling channel 7 is 10 cm, the diameter of the detection cylinder is 20 cm, and the thickness of the base 5 is 0.5 cm. The outer diameter of the lighting device 8 is 2 cm, the inner diameter can be set to 1.7 cm, and the number of lamp beads is 30. Different digital camera 2-optical microscope 1 combinations are installed in the cylinder wall 4. In this specification, the digital camera 2-optical microscope 1 combinations can include two types, namely, combination A and combination B. The overall magnification of combination A is 5x, and the overall magnification of combination B is 0.5x. Furthermore, the working distance of combination A in the sampling channel 7 is 4.53 cm, and the working distance of combination B in the sampling channel 7 is 6.5 cm. The dimensions of the power supply 9 are (2*1*4) cm, and the dimensions of the embedded computer 3 are (6.96*4.5) cm. The total height of combination A is 14 cm, and the total height of combination B is 20 cm.

[0094] Among them, digital camera 2 can use black light level 0.00001Lux low illumination COMS chip, digital camera 2A uses 0.75x low distortion high field telecentric lens, and digital camera 2B uses 5.0x metallographic plan apochromatic ultra-long working distance lens.

[0095] Furthermore, this specification also provides an aquatic organism detection method for the embedded computer 3 applied to the above-mentioned aquatic organism detection system, such as Figure 4 shown.

[0096] Figure 4 A schematic flow chart of an aquatic organism detection method provided in this specification includes the following steps:

[0097] S401: Processing the received biological image to obtain a processed biological image;

[0098] S402: Input the processed biological image into a preset target detection model to determine the detection results for aquatic organisms in the natural water body through the target detection model, and generate the motion trajectory of each aquatic organism according to the detection results through a preset trajectory generation model, and send the detection results and the motion trajectory to the client.

[0099] The embedded computer 3 may first perform dehazing processing on the biological image to obtain candidate images, then determine the clarity corresponding to each candidate image, and delete the candidate images whose clarity is lower than a threshold, thereby obtaining a processed biological image.

[0100] It should be noted that at each moment, if there are at least two biological images captured by digital cameras 2 at that moment, the embedded computer 3 can process the biological images captured by each digital camera 2 at that moment to obtain processed images; then, each processed image can be input into the target detection model to obtain intermediate results; and then, the intermediate results at that moment can be fused to obtain the detection result at that moment. In this way, the accuracy of the detection results can be improved by utilizing the results captured by multiple digital cameras 2.

[0101] Specifically, embedded computer 3 can transmit multiple acquired biological images to the image selection and preprocessing module through the built-in image processing module for selection and processing. The processed images are then stored in the image library and preprocessed using a dark channel prior (DCP). The recognition and statistical algorithm module then performs recognition and statistics to obtain the final detection results, which are then stored in the database.

[0102] The embedded computer 3 can send the recognition results in the database to the client, and the user can perform graphical human-computer interaction through the user interface provided by the client. The user interface can provide functions such as report image output, database operation, gallery operation, recognition operation, parameter setting, automatic operation menu and dialog box.

[0103] Aquatic organisms flow through the sampling channel 7 through the flow of natural water bodies and are photographed by the digital camera 2 connected to the optical microscope 1 under the illumination light source provided by the illumination device 8.

[0104] The embedded computer 3 can perform defogging on the biological images captured by the digital camera 2. The defogging images can provide more accurate information, improve the performance and reliability of the task, and provide a better foundation for subsequent image analysis and recognition tasks.

[0105] Since the shooting process generates a large number of images, most of them may be blank or out of focus. In order to reduce the workload of subsequent artificial intelligence recognition, the biological images can be screened first. The method is to calculate the clarity of the images of all focal planes in each field of view. Those with clarity less than a certain threshold will be removed, and those with higher clarity will be retained for subsequent image recognition.

[0106] The processed image can then be used for detection and recognition using an object detection model (such as YOLO11). In practical applications, the image size during object detection can be set to 640*640. During detection, the image data can be rotated and contrast enhanced, and the identified biological regions can be selected. Once all regions in an image have been detected, the final detection results are output. These results can include the category and pose of the aquatic organism.

[0107] After determining the target detection results, an ID can be assigned to each identified aquatic organism, and the target detection results corresponding to each frame of the image can be input into a trajectory generation model (such as Deep SORT). The trajectory generation model can then generate the movement trajectory of each aquatic organism based on its position in each frame of the image.

[0108] Among them, the above-mentioned target detection results can be determined by the target detection model based on the frame selection results of each aquatic organism.

[0109] The embedded computer 3 can pick out unrecognizable aquatic organisms or images with recognition accuracy lower than 50%, and store them separately in a folder for easy subsequent manual verification and naming. It can also store images with recognition accuracy higher than 50% in another folder, and name each biological image separately for future verification.

[0110] In addition, the embedded computer 3 can also output statistical counts through the calculation module, combine the detection results of all biological images, cumulatively calculate the number of different types of aquatic organisms appearing in each biological image, and count them by type.

[0111] In practical applications, the accuracy of the trained detection model can be evaluated using precision and recall, namely:

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] TP represents the number of positive predictions, FP represents the number of negative predictions, or false positives, and FN represents the number of negative predictions, or missed negatives. In the p(r) curve, which has Recall on the horizontal axis and Precision on the vertical axis, Average Precision (AP) is the mean of the Precision values ​​on the p(r) curve. The F1 index and mean Average Precision (mAP) are the primary metrics for evaluating the overall performance of object detection.

[0118] As can be seen from the above, compared to existing manual detection methods, this solution achieves automated detection of aquatic organisms without the need for human intervention, improving detection efficiency and reducing labor costs. It also effectively avoids the death of plankton in the water during sample collection and storage, thereby increasing the accuracy of aquatic organism detection. Preprocessing and target detection models further enhance the detection accuracy of aquatic organisms, significantly improving detection performance. Online detection of zooplankton is achieved, significantly improving detection efficiency. The overall lightweight design of the device effectively reduces detection power consumption.

[0119] This specification also provides an aquatic organism detection device for the embedded computer 3 used in the above-mentioned aquatic organism detection system, such as Figure 5 shown.

[0120] Figure 5 A schematic diagram of an aquatic organism detection device provided in this manual includes:

[0121] The processing module 501 is used to process the received biological image to obtain a processed biological image;

[0122] The determination module 502 is used to input the processed biological image into a preset target detection model to determine the detection results for aquatic organisms in the natural water body through the target detection model, and send the detection results to the client. The detection results include: the category and movement trajectory of the aquatic organisms.

[0123] Optionally, the processing module 501 is specifically configured to perform dehazing processing on the biological image to obtain candidate images; determine the clarity corresponding to each candidate image, and delete the candidate images whose clarity is lower than a threshold to obtain the processed biological image.

[0124] Optionally, the biological image is a microscopic image digitally captured and sent by the digital camera 2, and the microscopic image is obtained by magnifying the organisms in natural water bodies by the optical microscope 1;

[0125] The determination module 502 is specifically used to, for each moment, if there are biological images captured by at least two digital cameras 2 at that moment, process the biological images captured by each digital camera 2 at that moment respectively to obtain processed images; input the processed images into the target detection model respectively to obtain intermediate results; and fuse the intermediate results to obtain detection results for aquatic organisms in the natural water body.

[0126] This specification also provides a computer-readable storage medium, which stores a computer program that can be used to execute the above Figure 4 A method for detecting aquatic organisms is provided.

[0127] This manual also provides Figure 6 The one shown corresponds to Figure 4 Schematic diagram of the electronic equipment. Figure 6 As mentioned above, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 4 Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0128] Improvements to a technology can be clearly categorized as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with technological advancements, many process flow improvements can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using physical hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can integrate a digital system onto a PLD by programming it themselves, without having to hire a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually making integrated circuit chips, this type of programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used when developing and writing programs. The original code before compilation must also be written in a specific programming language, which is called Hardware Description Language (HDL). There is not only one HDL, but many types, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog.

[0129] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the memory control logic. Those skilled in the art will also appreciate that, in addition to implementing the controller purely in computer-readable program code, the controller can also be implemented in the form of logic gates, switches, an application-specific integrated circuit, a programmable logic controller, an embedded microcontroller, etc. by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the means for implementing the various functions included therein can also be considered as structures within the hardware component. Alternatively, the means for implementing the various functions can be considered both a software module implementing the method and a structure within the hardware component.

[0130] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0131] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0132] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0134] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0136] In a typical configuration, a processing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0137] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0138] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a processing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0139] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0140] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0141] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including storage devices.

[0142] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0143] The foregoing is merely an example of the present invention and is not intended to limit the present invention. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. An aquatic organism detection system, characterized in that: The system comprises: a detection tube, an optical microscope (1), a digital camera (2) and an embedded computer (3); the aquatic organisms comprise: plankton; The detection cylinder comprises a cylinder wall (4) and a base (5), a plurality of retractable support structures (6) are arranged between the cylinder wall (4) and the base (5), and a sampling channel (7) is formed in the area between the cylinder wall (4) and the base (5) under the support of the plurality of support structures (6); the digital camera (2), the optical microscope (1) and the embedded computer (3) are arranged in the closed space formed by the cylinder wall (4); the sampling channel (7) is placed in a flowing natural water body, and the natural water body flows through the sampling channel (7) through the gaps between the support structures (6); The digital camera (2) is used to digitally capture the microscopic image obtained by the optical microscope (1) and send the captured biological image to the embedded computer (3); The embedded computer (3) includes a target detection module and a trajectory generation module. The target detection module is used to perform target detection on the biological image through a preset target detection model to obtain a detection result for aquatic organisms in the natural water body; the trajectory generation module is used to generate a motion trajectory of each aquatic organism according to the detection result through a preset trajectory generation model. The multiple retractable support structures (6) are used to adjust the height of the sampling channel (7) so that the optical microscope (1) and the digital camera (2) can capture clear images within a working area adapted to their configuration parameters.

2. The aquatic organism detection system according to claim 1, wherein: The aquatic organism detection system is provided with: a thermal sensor (13); The thermal sensor (13) is arranged in the sampling channel (7) and is used to receive a heating signal generated by the embedded computer (3) according to the temperature of the natural water body when the temperature of the natural water body is lower than a preset active temperature of aquatic organisms, and heat the natural water body according to the heating signal; and collect the temperature of the natural water body and send it to the embedded computer (3).

3. The aquatic organism detection system according to claim 1, wherein: The aquatic organism detection system is provided with: a lighting device (8); The lighting device (8) is arranged at a designated position in the sampling channel (7) and is used to provide an illumination light source for the optical microscope (1) and the digital camera (2); The digital camera (2) is used to digitally capture the microscopic image under the illumination light source provided by the illumination device (8).

4. The aquatic organism detection system according to claim 1, wherein: The optical microscope (1) and the digital camera (2) are respectively provided in plurality, and the optical microscopes (1) with different configuration parameters are combined with the digital cameras (2) with different configuration parameters; The configuration parameters of the optical microscope (1) include at least magnification and working distance, and the configuration parameters of the digital camera (2) include at least zoom ratio.

5. The aquatic organism detection system according to claim 1, wherein: The aquatic organism detection system is further provided with: a power supply (9), a power management device (10) and a solar energy collection device; The solar energy collection device is arranged on the barrel cover (11) of the detection barrel and is connected to the power management device (10); The power management device (10) is used to process the energy collected by the solar energy collection device and provide it to the power supply (9); The power supply (9) is used to supply power to the digital camera (2) and the embedded computer (3).

6. A method for detecting aquatic organisms, said method being applied to the embedded computer (3) of the aquatic organism detection system according to any one of claims 1 to 5, characterized in that: The method comprises: processing the received biological image to obtain a processed biological image; The processed biological image is input into a preset target detection model to determine the detection results for aquatic organisms in natural water bodies through the target detection model, and the motion trajectory of each aquatic organism is generated according to the detection results through a preset trajectory generation model, and the detection results and the motion trajectory are sent to the client.

7. The method according to claim 6, wherein Processing the received biological image, specifically including: Performing defogging processing on the biological image to obtain candidate images; The clarity corresponding to each candidate image is determined, and candidate images with clarity lower than a threshold are deleted to obtain the processed biological image.

8. The method according to claim 7, wherein The biological image is a microscopic image digitally captured and sent by a digital camera (2), and the microscopic image is obtained by magnifying the organisms in natural water bodies by an optical microscope (1); Determining the test results for aquatic organisms in the natural water body, specifically including: For each moment, if there are biological images captured by at least two digital cameras (2) at that moment, the biological images captured by each digital camera (2) at that moment are processed respectively to obtain processed images; Inputting the processed images into the target detection model respectively to obtain intermediate results; The intermediate results are integrated to obtain the detection results for the aquatic organisms in the natural water body.

9. An aquatic organism detection device, applied to the embedded computer (3) of the aquatic organism detection system according to any one of claims 1 to 5, characterized in that: include: A processing module, configured to process the received biological image to obtain a processed biological image; A determination module is used to input the processed biological image into a preset target detection model to determine the detection results for aquatic organisms in natural water bodies through the target detection model, and to generate a motion trajectory of each aquatic organism based on the detection results through a preset trajectory generation model, and to send the detection results and the motion trajectory to the client.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 6 to 8 is implemented.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When executing the program, the processor implements the method according to any one of claims 6 to 8.

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