Aquatic organism detection system, method and device

Abstract

The invention discloses an aquatic organism detection system, method and device. The aquatic organism detection system comprises a detection cylinder, an optical microscope, a digital camera and an embedded computer, the detection cylinder comprises a cylinder wall and a base, and a plurality of supporting structures are arranged between the cylinder wall and the base; the digital camera, the optical microscope and the embedded computer are arranged in a closed space formed by the cylinder wall; the sampling channel is arranged in a flowable natural water body, and the natural water body passes through the sampling channel through gaps among the supporting structures to flow; the optical microscope is used for amplifying organisms in the natural water body to obtain a microscopic image; the digital camera is used for digitally acquiring microscopic images and sending acquired biological images to the embedded computer; the embedded computer is used for inputting the biological image into the target detection model and determining a detection result, and the detection result comprises the category and the motion trail of the aquatic organisms. According to the scheme, the accuracy of a detection result is improved.

Description

Technical Field

[0001] This specification relates to the technical field of biological collection, and particularly to an aquatic biological detection system, method and device. Background Art

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

[0003] Among them, plankton is the core of the lake ecosystem. They play an important role in the investigation and research of the water body biological ecology and play a core role in the biogeochemical cycle and carbon cycle. Most plankton are small in size, short in lifespan, and highly sensitive to environmental conditions, which makes their diversity and abundance very effective indicators of environmental change and ecosystem health.

[0004] However, currently, labor-intensive sampling and microscopes are usually used to detect the diversity and abundance of plankton in water bodies. In this process, it is necessary to manually sample in the water body multiple times and observe the samples through a microscope. The detection process is too dependent on the experience of the observers, with strong subjectivity, and it also requires a large amount of labor and time costs. In addition, the plankton in the water body is very likely to die during the sample collection and preservation processes, seriously affecting the accuracy of the detection results. Summary of the Invention

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

[0006] This specification adopts the following technical solutions: An aquatic biological detection system, the system includes: a detection cylinder, an optical microscope, a digital camera, and an embedded computer; The detection cylinder includes a cylinder wall and a base. A plurality of telescopic support structures are arranged between the cylinder wall and the base. The area between the cylinder wall and the base forms a sampling channel under the support of the plurality of support structures; the digital camera, the optical microscope, and the embedded computer are arranged in the enclosed space formed by the cylinder wall; the sampling channel is placed in a flowing natural water body, and the natural water body flows through the sampling channel through the gaps between the support structures; The digital camera is used to digitally collect the microscopic images obtained by the optical microscope and send the collected biological images to the embedded computer; The embedded computer includes an object detection module and a trajectory generation module. The object detection module is configured to perform object detection on the biological image through a preset object detection model to obtain a detection result for the aquatic organisms in the natural water body. The trajectory generation module is configured to generate a movement trajectory for each aquatic organism according to the detection result through a preset trajectory generation model.

[0007] Optionally, the aquatic organism detection system is provided with: a thermal sensor; The thermal sensor is disposed in the sampling channel and is configured to receive a heating signal generated by the embedded computer according to the temperature of the natural water body and heat the natural water body according to the heating signal when the temperature of the natural water body is lower than the active temperature of the preset aquatic organisms. In addition, the thermal sensor is configured to collect the temperature of the natural water body and send it to the embedded computer.

[0008] Optionally, the plurality of telescopic support structures are configured to adjust the height of the sampling channel.

[0009] Optionally, the aquatic organism detection system is provided with: a lighting device; The lighting device is disposed at a specified position in the sampling channel and is configured to provide an illumination light source for the optical microscope and the digital camera; The digital camera is configured to digitally collect the microscopic image under the illumination light source provided by the lighting device.

[0010] Optionally, a plurality of the optical microscopes and the digital cameras are respectively provided, and the optical microscopes with different configuration parameters are combined with the digital cameras with different configuration parameters; The configuration parameters of the optical microscope at least include: magnification and working distance, and the configuration parameters of the digital camera at least include: zoom ratio.

[0011] Optionally, the aquatic organism detection system is further provided with: a power supply, a power management device, and a solar energy collection device; The solar energy collection device is disposed on the barrel cover of the detection cylinder and is connected to the power management device; The power management device is configured to process the energy collected by the solar energy collection device and supply it to the power supply; The power supply is configured to supply power to the digital camera and the embedded computer.

[0012] This specification provides an aquatic organism detection method, and the method includes: Processing the received biological image to obtain a processed biological image; Input the processed biological image into a preset object detection model to determine the detection result for the aquatic organisms in the natural water body through the object detection model. Moreover, generate the movement trajectory of each aquatic organism according to the detection result through a preset trajectory generation model, and send the detection result and the movement trajectory to the client.

[0013] Optionally, the processing of the received biological image specifically includes: Perform defogging processing on the biological image to obtain candidate images; Determine the clarity corresponding to each candidate image, and delete the candidate images with clarity lower than the threshold to obtain the processed biological image.

[0014] Optionally, the biological image is digitized and sent by a digital camera after collecting a microscopic image, and the microscopic image is obtained by magnifying the organisms in the natural water body with an optical microscope; Determining the detection result for the aquatic organisms in the natural water body specifically includes: For each moment, if there are biological images collected by at least two digital cameras at this moment, then process the biological images collected by each digital camera at this moment respectively to obtain processed images; Input the processed images into the object detection model respectively to obtain intermediate results; Fuse the intermediate results to obtain the detection result for the aquatic organisms in the natural water body.

[0015] This specification discloses an aquatic organism detection device, including: A processing module for processing the received biological image to obtain a processed biological image; A determination module for inputting the processed biological image into a preset object detection model to determine the detection result for the aquatic organisms in the natural water body through the object detection model, and moreover, generating the movement trajectory of each aquatic organism according to the detection result through a preset trajectory generation model, and sending the detection result and the movement trajectory to the client.

[0016] This specification provides a computer-readable storage medium, where the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned aquatic organism detection method is implemented.

[0017] This specification provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the above-mentioned aquatic organism detection method is implemented.

[0018] The above at least one technical solution adopted in this specification can achieve the following beneficial effects: The aquatic biological detection system provided in this specification includes: a detection cylinder, an optical microscope, a digital camera, and an embedded computer; the detection cylinder includes a cylinder wall and a base, and a plurality of support structures are arranged between the cylinder wall and the base, and a sampling channel is formed in the area between the cylinder wall and the base under the support of the plurality of support structures; the digital camera and the embedded computer are arranged in the enclosed space formed by the cylinder wall; the sampling channel is placed in a flowing natural water body, and the natural water body flows through the sampling channel through the gaps between the support structures; the optical microscope is used to magnify the organisms in the natural water body to obtain a microscopic image; the digital camera is used to digitally collect the microscopic image and send the collected biological image to the embedded computer; the embedded computer is used to process the received biological image to obtain the detection result for the aquatic organisms in the natural water body.

[0019] As can be seen from the above, in this solution, the sampling channel of the aquatic biological detection system is placed in a flowing natural water body, and the microscope and the digital camera are used to collect real-time images of the water body flowing through the sampling channel, and then image processing is performed based on the built-in embedded computer to obtain the final detection result. The whole process realizes the automatic detection of aquatic organisms without manual intervention, improves the detection efficiency, reduces the labor cost, and effectively avoids the death of plankton in the water body during the sample collection and preservation process, improving the accuracy of aquatic biological detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of this specification and form a part of this specification. The schematic embodiments of this specification and their descriptions are used to explain this specification and do not constitute an improper limitation of this specification. In the drawings: Figure 1 is a schematic diagram of an aquatic biological detection system provided in this specification; Figure 2 is a schematic diagram of a lighting device provided in this specification; Figure 3 is an external structure schematic diagram of the aquatic biological detection system provided in this specification; Figure 4 is a schematic flowchart of an aquatic biological detection method provided in this specification; Figure 5 is a schematic diagram of an aquatic biological detection device provided in this specification; Figure 6 is provided in this specification for the above Figure 4 schematic diagram of an electronic device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all of them. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope protected by this specification.

[0022] The following details the technical solutions provided by each embodiment of this specification in conjunction with the drawings.

[0023] Figure 1 It is a schematic diagram of an aquatic organism detection system provided in this specification. The aquatic organism detection system is provided with a detection cylinder, an optical microscope 1, a digital camera 2, and an embedded computer 3.

[0024] As Figure 1 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 telescopic support structures 6 are provided 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 flowing natural water body, and the natural water body can flow through the sampling channel 7 through the gaps between the support structures 6.

[0025] Among them, the above-mentioned plurality of telescopic support structures 6 are used to adjust the height of the sampling channel 7. Since the depths of different water bodies are different, in order to ensure that the optical microscope 1 and the digital camera 2 can capture clear images within their adapted working areas, when placing the aquatic organism detection system in the water body, the sampling channel 7 can be adjusted to a suitable height and fixed by adjusting the support structure 6.

[0026] 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, so as to achieve clear images can be captured in the water body whether in deep water areas or shallow water areas.

[0027] Among them, corresponding limiting devices (such as clamping grooves, bolts, pins, cam mechanisms, etc.) can be provided at designated positions of each support structure. In this way, after the support structure is adjusted to a suitable height, it can be fixed by the limiting device to prevent slipping.

[0028] Of course, in actual applications, the above-mentioned plurality of support structures can also be fixed support structures.

[0029] It should be noted that the aquatic organisms detected by the aquatic organism detection system in this specification can be plankton. Of course, they can also be other aquatic organisms such as algae and aquatic plants that can be imaged by the digital camera 2 and the optical microscope 1. This specification does not make specific limitations on this.

[0030] Among them, the above-mentioned support structure 6 can be a support rod or a support column. Of course, it can also be other supports with gaps. This specification does not make specific limitations on this.

[0031] The optical microscope 1 is arranged in the sampling channel 7 between the barrel wall 4 and the base 5 of the detection barrel, and is used to magnify the organisms in the natural water body to obtain microscopic images.

[0032] Furthermore, the above-mentioned aquatic organism detection system can also be provided with: a thermal sensor 13.

[0033] Among them, the thermal sensor can be arranged in the sampling channel 7, installed at the bottom of the closed area formed by the barrel wall 4, and connected to the embedded computer 3 and the power supply 9 respectively to realize signal transmission with the embedded computer 3 and power supply from the power supply 9.

[0034] Of course, in actual applications, the thermal sensor can also be arranged at other positions in the sampling channel 7, such as installed on the upper part of each support structure. This specification does not make specific limitations on this.

[0035] The thermal sensor 13 collects the temperature of the natural water body in real time and sends it to the embedded computer 3. When the embedded computer determines that the current temperature of the water body is lower than the preset active temperature of the aquatic organisms, it generates a heating signal and sends it to the thermal sensor 13. Among them, the above-mentioned active temperature of the aquatic organisms can be set according to the actual situation. This specification does not make specific limitations on this.

[0036] After receiving the heating signal, the thermal sensor 13 can heat the natural water body according to the heating signal, so as to heat the water body in the sampling channel 7 to the active temperature of the aquatic organisms, so as to facilitate the recognition of their movement trajectories.

[0037] The digital camera 2 and the optical microscope 1 are arranged in the closed area formed by the barrel wall 4 and are connected to the optical microscope 1, and are used to collect images of the above-mentioned microscopic images.

[0038] In this specification, the aquatic organism detection system can be provided with multiple optical microscopes 1 with different configuration parameters and multiple 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.

[0039] Among them, the configuration parameters of the optical microscope 1 can at least include: magnification and working distance (such asFigure 1 (the strip-shaped part in the middle sampling channel 7), the configuration parameters of the digital camera 2 may at least include: the zoom ratio. Among them, the above working distance is used to characterize the distance at which the optical microscope 1 can clearly observe the target object, that is, when the target object is within this working distance, the optical microscope 1 can clearly observe the target object.

[0040] 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 ratio of the digital camera 2 connected to the optical microscope 1, and the smaller the magnification of the optical microscope 1, the greater the zoom ratio of the digital camera 2 connected to the optical microscope 1. To achieve digital camera 2 - optical microscope 1 combinations with different configuration parameters.

[0041] Of course, in practical applications, the configuration parameters of the optical microscope 1 may also include, for example, aperture, working distance, correction ring, etc., and the configuration parameters of the digital camera 2 may also include, for example, resolution, contrast, depth of field, etc. This specification does not make specific limitations on this.

[0042] It should be added that in this specification, an optical microscope 1 can be connected to a digital camera 2. Of course, a digital camera 2 can also be connected to multiple optical microscopes 1 to simultaneously collect microscopic images of multiple optical microscopes 1.

[0043] In addition, an aquatic biological detection system may also be provided with: a lighting device 8, which is arranged at a specified 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 collect images of microscopic images under the lighting source provided by the lighting device 8.

[0044] For example, the lighting device 8 can be arranged at the bottom of the cylinder wall 4 to irradiate the water body from top to bottom at a certain angle, or the lighting device 8 can be arranged on the base 5 to irradiate the water body from bottom to top at a certain angle. Of course, the lighting device 8 can also be arranged at the middle position of the sampling channel 7 to irradiate the water body with parallel light.

[0045] In practical applications, the above lighting device 8 can be a light strip provided with multiple lamp beads, and the light strip is arranged in a ring shape around the support structure 6 (support rod) between the cylinder wall 4 and the base 5 and irradiates the imaging area in the sampling channel 7 at a certain angle.

[0046] For ease of understanding, this specification provides a schematic diagram of a lighting device 8, as Figure 2 shown.

[0047] Among them, the lighting device 8 is a strip light deployed in a ring shape, and irradiates the sampling channel 7 from top to bottom at an angle of 45°. A wire groove for paralleling all the lamp beads is arranged at the bottom of each lamp bead, and the wire groove is connected to the power supply 9 of the aquatic organism detection system to be powered by the power supply 9.

[0048] Furthermore, the digital camera 2 is connected to the embedded computer 3 arranged in the cylinder wall 4. After the digital camera 2 captures a biological image, the captured biological image is sent to the embedded computer 3.

[0049] In practical applications, a certain sampling interval can be preset for the digital camera 2 in advance, and then the digital camera 2 can capture the biological images observed by the optical microscope 1 according to this sampling interval.

[0050] 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 the detection result for the aquatic organisms in the natural water body; the trajectory generation module is used to generate the movement trajectory of each aquatic organism through a preset trajectory generation model according to the detection result.

[0051] Among them, the detection result includes: the category and pose of the aquatic organism. For each aquatic organism, the movement trajectory of the aquatic organism is generated according to the pose of the aquatic organism in each frame of the biological image.

[0052] In this specification, the above-mentioned target detection module and trajectory generation module can be two hardware modules set in the embedded computer. Of course, they can also be two software modules implemented by the embedded computer through algorithms. This specification does not make specific limitations on this.

[0053] The process of the embedded computer 3 processing the biological image will be described in detail below, and this specification will not elaborate too much here.

[0054] Furthermore, a network device can be set in the aquatic organism detection system. The network device is used to provide a network signal for the embedded computer 3 so that the embedded computer 3 can use the network signal to send the detection result to the client. The network signal provided by the above-mentioned network device can include 3G, 4G, 5G, and WIFI signals, etc. This specification does not make specific limitations on this.

[0055] In addition, the aquatic organism detection system is also 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.

[0056] The solar energy collection device is arranged on the lid 11 of the detection cylinder 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.

[0057] Among them, a line management port 12 can be arranged on the lid 11 of the detection cylinder, and the power line of the power management device 10 can pass through the line management port 12 and be connected to the solar energy collection device.

[0058] Furthermore, the above aquatic biological detection system is also provided with a controller, which is connected to the digital camera 2 through a multi-core cable and is used to control the digital camera 2.

[0059] The embedded computer 3 has built-in software modules. The software modules include support components and a user interface. The support components include a motion control software module that interacts with the controller, an image acquisition module that interacts with the digital camera 2, as well as an image selection and preprocessing module, an identification and statistical algorithm module, a picture library, and a database.

[0060] 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 biological images.

[0061] For the convenience of understanding, this specification provides a schematic diagram of the external structure of an aquatic biological detection system, as Figure 3 shown.

[0062] 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. Among them, the embedded computer 3, the digital camera 2, the optical microscope 1, the power supply 9, the power management device 10, and the network device can be respectively arranged in the waterproof-designed first cylinder wall 41 and second cylinder wall 42 according to space requirements and wiring layouts.

[0063] A ring-shaped lighting device 8 can be arranged in the sampling channel 7 between the base 5 and the second cylinder wall 42 to provide a lighting source for the sampling channel 7.

[0064] It should be noted that in actual applications, the cylinder wall 4 can also be composed of a part, and the lighting device 8 in the sampling channel 7 can be set with only one or multiple.

[0065] In an embodiment provided in this specification, the heights of the first cylinder wall 41 and the second cylinder wall 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 arranged in the cylinder wall 4. In this specification, the digital camera 2 - optical microscope 1 combination can include two types, namely combination A and combination B. Among them, the overall magnification of combination A is 5x, and the overall magnification of combination B is 0.5x. In addition, the working distance of combination A in the sampling channel 7 is 4.53 cm, the working distance of combination B in the sampling channel 7 is 6.5 cm, the size of the power supply 9 is (2 * 1 * 4) cm, the size of the embedded computer 3 is (6.96 * 4.5) cm, the total height of combination A is 14 cm, and the total height of combination B is 20 cm.

[0066] Among them, the digital cameras 2 can all adopt black light level 0.00001 Lux low - illumination COMS chips. The digital camera 2A adopts a 0.75x low - distortion high - depth - of - field telecentric lens, and the digital camera 2B adopts a 5.0 x metallographic flat - field apochromatic super - long working - distance lens.

[0067] Furthermore, this specification also provides an aquatic organism detection method for the embedded computer 3 applied to the above - mentioned aquatic organism detection system, as Figure 4 shown.

[0068] Figure 4 is a schematic flow chart of an aquatic organism detection method provided in this specification, including the following steps: S401: Process the received biological image to obtain a processed biological image; S402: Input the processed biological image into a preset target detection model to determine the detection result for the aquatic organisms in the natural water body through the target detection model, and generate the movement trajectory of each aquatic organism according to the detection result through a preset trajectory generation model, and send the detection result and the movement trajectory to the client.

[0069] Among them, the embedded computer 3 can first perform defogging processing on the biological image to obtain each candidate image, then determine the clarity corresponding to each candidate image, and delete the candidate images with clarity lower than the threshold, so as to obtain a processed biological image.

[0070] It should be added that for each moment, if there are at least two biological images collected by the digital cameras 2 at this moment, the embedded computer 3 can process the biological images collected by each digital camera 2 at this moment respectively to obtain processed images; then input the processed images into the target detection model respectively to obtain intermediate results; and then fuse the intermediate results at this moment to obtain the detection result at this moment. Thus, the accuracy of the detection result is improved by the results collected by multiple digital cameras 2.

[0071] Specifically, the embedded computer 3 can transmit the acquired multiple biological images to the image selection and preprocessing module through the built-in image processing module for selection and processing, then store the processed images in the image library, and perform preprocessing through Dark Channel Prior (DCP). Then, through the recognition and statistical algorithm module, recognition and statistics are performed to obtain the final detection result, and the detection result is stored in the database.

[0072] The embedded computer 3 can send the recognition result 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, image library operation, recognition operation, parameter setting, automatic operation menu, and dialog box.

[0073] 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 lighting device 8.

[0074] The embedded computer 3 can perform defogging processing on the biological images collected by the digital camera 2. The defogged images can provide more accurate information, improve the performance and reliability of the task, and provide a better basis for subsequent image analysis and recognition tasks.

[0075] Since a large number of images are generated during the shooting process, most of the large number of images may be blank or out of focus. 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, and remove those with clarity less than a certain threshold, and retain those with higher clarity for subsequent image recognition.

[0076] After that, the processed image can be detected and recognized by a target detection model (such as YOLO11). In practical applications, the imaging size during the target detection process can be set to 640*640. During the detection process, the image data can be rotated and the contrast can be enhanced, and the recognized biological regions can be framed. When all regions in an image have been detected, the final detection result is output. Among them, the detection result can include the category and pose of aquatic organisms.

[0077] After determining the target detection result, an ID can be assigned to each recognized aquatic organism, and the target detection result corresponding to each frame of image can be input into a trajectory generation model (such as Deep SORT). Thus, through the trajectory generation model, according to the pose of each aquatic organism in each frame of image, the movement trajectory of each aquatic organism can be generated.

[0078] Among them, the above target detection result can be determined by the target detection model according to the framed results of each aquatic organism.

[0079] The embedded computer 3 can pick out the aquatic organisms that cannot be recognized or the images with a recognition accuracy lower than 50%, and store them separately in a folder for subsequent manual verification and naming. The images with a recognition accuracy greater than 50% are stored separately in another folder, and each biological image is named separately for verification.

[0080] In addition, the embedded computer 3 can also output statistical counts through the calculation module, merge and statistically analyze the detection results of all biological images, accumulate and calculate the number of different types of aquatic organisms appearing in each biological image, and perform statistical counting by type.

[0081] In practical applications, the accuracy of the trained detection model can be evaluated using Precision and Recall, that is:

[0082]

[0083]

[0084]

[0085]

[0086] Among them, TP represents the number of positive classes predicted as positive classes, FP represents the number of negative classes predicted as positive classes, that is, the number of false positives, and FN represents the number of positive classes predicted as negative classes, that is, the number of missed detections. In the p(r) curve with the Recall value as the horizontal axis and the Precision value as the vertical axis, the average precision AP is the mean of Precision on the p(r) curve; the F1 index and mAP are the main evaluation indicators for measuring the comprehensive performance of object detection.

[0087] As can be seen from the above content, compared with the existing manual detection method, this solution realizes the automatic detection of aquatic organisms without human intervention, improves the detection efficiency, reduces the labor cost, and effectively avoids the death of plankton in the water during the sample collection and preservation process, improving the accuracy of aquatic organism detection. The detection accuracy of aquatic organisms is further improved through preprocessing and the target detection model, and the detection performance is greatly improved. The online detection of zooplankton is realized, making the detection efficiency significantly improved. The overall lightweight design of the device effectively reduces the detection power consumption.

[0088] This specification also provides an aquatic organism detection device for the embedded computer 3 applied to the above-mentioned aquatic organism detection system, as Figure 5 shown.

[0089] Figure 5 Schematic diagram of an aquatic organism detection device provided by this specification, including: A processing module 501, configured to process the received biological image to obtain a processed biological image; A determination module 502, configured to input the processed biological image into a preset target detection model, so as to determine the detection result for the aquatic organisms in the natural water body through the target detection model, and send the detection result to the client, where the detection result includes: the category and movement trajectory of the aquatic organisms.

[0090] Optionally, the processing module 501 is specifically configured to perform defogging processing on the biological image to obtain each candidate image; determine the clarity corresponding to each candidate image, and delete the candidate images with clarity lower than the threshold to obtain the processed biological image.

[0091] Optionally, the biological image is digitally collected and sent by the digital camera 2 for the microscopic image, and the microscopic image is obtained by magnifying the organisms in the natural water body by the optical microscope 1; Specifically, for each moment, if there are at least two biological images collected by the digital cameras 2 at this moment, the determining module 502 is configured to process the biological images collected by each digital camera 2 at this 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 a detection result for the aquatic organisms in the natural water body.

[0092] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above Figure 4 provided method for detecting aquatic organisms.

[0093] This specification also provides Figure 6 a schematic structural diagram of an electronic device corresponding to Figure 4 as shown. As Figure 6 described, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, other hardware required for other services may also be included. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the above Figure 4 described method for detecting aquatic organisms. Of course, in addition to the software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware. That is to say, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or a logic device.

[0094] For an improvement in a technology, it can be clearly distinguished whether it is a hardware improvement (e.g., improvement in circuit structures such as diodes, transistors, switches, etc.) or a software improvement (improvement in method flows). However, with the development of technology, many improvements in method flows today can be regarded as direct improvements in hardware circuit structures. Almost all designers obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement in a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logic function is determined by the user's programming of the device. The designer programs by himself to "integrate" a digital system on a piece of PLD, without having to ask a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called a hardware description language (HDL), and there is not only one type of 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. Currently, the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog.

[0095] The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as 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 the controller 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 control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, it is entirely possible to logically program the method steps to enable the controller to be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers to achieve the same function. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0096] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0097] For the convenience of description, when describing the above devices, they are described separately as 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.

[0098] Those skilled in the art should understand that the embodiments of this specification can be provided as a method, a system, or a computer program product. Therefore, this specification can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0099] This specification is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the specification. It should be understood that each flow and / or block in the flowchart and / or block diagram, and combinations of flows 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 the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0100] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0102] In a typical configuration, a processing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0103] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash RAM. The memory is an example of computer-readable media.

[0104] 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.

[0105] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0106] 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.

[0107] 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.

[0108] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiment.

[0109] The above description is only for the embodiments of this specification and is not intended to limit this specification. For those skilled in the art, various modifications and changes can be made to this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this specification shall be included within the scope of the claims of this specification.

Claims

1. An aquatic organism detection system, characterized in that, The system includes: a detection cylinder, an optical microscope (1), a digital camera (2), and an embedded computer (3); The detection cylinder includes a cylinder wall (4) and a base (5). A plurality of telescopic 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). The digital camera (2), the optical microscope (1), and the embedded computer (3) are arranged in the enclosed 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 configured to digitally collect the microscopic images obtained by the optical microscope (1) and send the collected biological images to the embedded computer (3); The embedded computer (3) includes an object detection module and a trajectory generation module. The object detection module is configured to perform object detection on the biological images through a preset object detection model to obtain a detection result for the aquatic organisms in the natural water body. The trajectory generation module is configured to generate the movement trajectories of each aquatic organism according to the detection result through a preset trajectory generation model.

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 configured to receive a heating signal generated by the embedded computer (3) according to the temperature of the natural water body and heat the natural water body according to the heating signal when the temperature of the natural water body is lower than the active temperature of the preset aquatic organisms. In addition, it collects the temperature of the natural water body and sends it to the embedded computer (3).

3. The aquatic organism detection system according to claim 1, characterized in that, The plurality of telescopic support structures (6) are configured to adjust the height of the sampling channel (7).

4. The aquatic organism detection system according to claim 1, characterized in that, The aquatic organism detection system is provided with: a lighting device (8); The lighting device (8) is arranged at a specified position in the sampling channel (7) and is configured to provide a lighting source for the optical microscope (1) and the digital camera (2); The digital camera (2) is configured to digitally collect the microscopic images under the lighting source provided by the lighting device (8).

5. The aquatic organism detection system according to claim 1, characterized in that, A plurality of the optical microscopes (1) and the digital cameras (2) are respectively provided, 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) at least include: magnification and working distance, and the configuration parameters of the digital camera (2) at least include: zoom ratio.

6. 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 cylinder and is connected to the power management device (10); The power management device (10) is configured to process the energy collected by the solar energy collection device and supply it to the power supply (9); The power supply (9) is configured to supply power to the digital camera (2) and the embedded computer (3).

7. An aquatic organism detection method, which is applied to the embedded computer (3) of the aquatic organism detection system according to any one of claims 1 to 6 above, and is characterized in that, The method includes: Processing the received biological image to obtain a processed biological image; Inputting the processed biological image into a preset target detection model to determine, through the target detection model, the detection result for aquatic organisms in natural water bodies, and generating, through a preset trajectory generation model, the movement trajectory of each aquatic organism according to the detection result, and sending the detection result and the movement trajectory to the client.

8. The method according to claim 7, characterized in that Processing the received biological image specifically includes: Performing defogging processing on the biological image to obtain candidate images; Determining the clarity corresponding to each candidate image, and deleting the candidate images with clarity lower than the threshold to obtain the processed biological image.

9. The method according to claim 8, wherein The biological image is digitally collected and sent by the digital camera (2) from a microscopic image, and the microscopic image is obtained by magnifying organisms in natural water bodies with an optical microscope (1); Determining the detection result for aquatic organisms in the natural water body specifically includes: For each moment, if there are biological images collected by at least two digital cameras (2) at this moment, then process the biological images collected by each digital camera (2) at this moment respectively to obtain processed images; Inputting the processed images into the target detection model respectively to obtain intermediate results; Fusing the intermediate results to obtain the detection result for aquatic organisms in the natural water body.

10. An aquatic organism detection device, characterized in that, It includes: A processing module configured to process the received biological image to obtain a processed biological image; A determination module configured to input the processed biological image into a preset target detection model to determine, through the target detection model, the detection result for aquatic organisms in natural water bodies, and generate, through a preset trajectory generation model, the movement trajectory of each aquatic organism according to the detection result, and send the detection result and the movement trajectory to the client.

11. 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 7 to 9 above is implemented.

12. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the method according to any one of claims 7 to 9 above is implemented.

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