An automatic recognition method and device based on the golden body color of large yellow croaker

Abstract

The present application provides a method and device for automatically identifying the golden body color of large yellow croakers. The method provided by the present application includes using the identified large yellow croakers as markers, setting the recognition threshold for the yellow degree of the color sensor; determining the first light avoidance time of the large yellow croaker to be measured, processing the large yellow croaker to be measured in a dark environment for the first light avoidance time length, irradiating the large yellow croaker to be measured with a light source in the dark environment, and detecting the target reflected light; filtering the target reflected light to obtain a yellow photoelectric signal; calculating the target color parameters according to the yellow photoelectric signal; and determining the quality information of the large yellow croaker to be measured based on the target color parameters and the recognition threshold for the yellow degree. The method and device for automatically identifying the golden body color of large yellow croakers provided by the present application are used to efficiently and accurately identify the body color of large yellow croakers.

Description

Technical Field

[0001] The present application relates to the technical field of fish detection, and particularly to an automatic recognition method and device based on the golden body color of large yellow croaker. Background Art

[0002] With the development of the aquaculture and fishing industries, the output of large yellow croaker has been increasing year by year, and the demand for the quality assessment of large yellow croaker has become increasingly urgent. As an important object of aquaculture and fishing, the quality of large yellow croaker is directly related to the market value and consumer satisfaction. In the quality assessment of large yellow croaker, body color is a key indicator, especially the golden body color, which is often regarded as a symbol of high-quality large yellow croaker.

[0003] In the existing technologies for determining the body color of large yellow croaker, one existing technology is to determine the body color of large yellow croaker through the observation of fishermen and farmers. Although this method is simple and intuitive, it also has the problems of strong subjectivity and inconsistent evaluation results. Especially in the case of a large number of large yellow croaker with subtle body color differences, it is difficult to ensure the accuracy and consistency of the evaluation by manual observation. Therefore, technicians thought of determining the body color by extracting pigments from the body of large yellow croaker in the laboratory. Although this method can analyze the pigment components in the body of large yellow croaker more accurately, it is complex in operation, high in cost, and cannot be directly applied to the rapid evaluation in actual production, and the efficiency cannot meet the actual requirements. To sum up, how to automatically, quickly, and accurately identify the golden body color of large yellow croaker has become an urgent problem to be solved currently. Summary of the Invention

[0004] In view of this, the present application provides an automatic recognition method and device based on the golden body color of large yellow croaker to efficiently and accurately identify the body color of large yellow croaker.

[0005] Specifically, the present application is implemented through the following technical solutions:

[0006] The first aspect of the present application provides an automatic recognition method based on the golden body color of large yellow croaker, and the method includes:

[0007] Using the recognized large yellow croaker as a marker to set the yellow degree recognition threshold of the color sensor;

[0008] Wherein, the yellow degree recognition threshold is used to recognize different degrees of yellow, and different degrees of yellow correspond to different qualities. Receive the reflected light of the marker after being irradiated by the light source. The setting of the yellow degree recognition threshold of the color sensor includes: using the color sensor to extract the first yellow reflection component from the reflected light of the marker and calculate the first reference color, and using the first reference color as the yellow degree recognition threshold;

[0009] Determine the first light avoidance time of the large yellow croaker to be measured. Treat the large yellow croaker to be measured for a first light avoidance time length in a dark environment, and the color of the large yellow croaker to be measured changes before and after the treatment;

[0010] Irradiate the large yellow croaker to be measured in a dark environment and detect the target reflected light;

[0011] Filter the target reflected light to obtain a yellow optical signal;

[0012] Calculate the target color parameters according to the yellow optical signal;

[0013] Based on the target color parameters and the yellow degree recognition threshold, determine the quality information of the large yellow croaker to be measured.

[0014] The second aspect of the present application provides an automatic recognition device based on the golden body color of large yellow croakers. The device includes a packaging module, a transmission module, an illumination module, a shooting module, a processing module, and a screening module; each of the other modules except the packaging module is arranged in the packaging module. The illumination module is fixed above the transmission module, one end of the screening module is fixed on the transmission module, and the other end of the screening module is fixed on the processing module, where:

[0015] The packaging module is used as the basic framework of the device to fix the device;

[0016] The transmission module is used to move the large yellow croaker to be measured to a position where the shooting module can collect reflected light;

[0017] The illumination module is used to provide light to irradiate the large yellow croaker to be measured;

[0018] The shooting module is used to capture the target reflected light of the large yellow croaker to be measured;

[0019] The processing module is used to filter the target reflected light to obtain a yellow optical signal and calculate the target color parameters according to the yellow optical signal;

[0020] The screening module is connected with a plurality of quality channels; the screening module is used to determine the quality information of the large yellow croaker to be measured based on the target color parameters and the yellow degree recognition threshold, and put the large yellow croaker to be measured into different quality channels based on the quality information.

[0021] The automatic recognition method and device based on the golden body color of large yellow croaker provided by this application utilize the combination of a color sensor and reasonable threshold setting to achieve the automatic recognition of the quality of large yellow croaker. That is, directly based on the relationship between the value of the yellow light reflection signal and the values of large yellow croakers at different quality levels, it realizes the automatic judgment from color to quality without relying on experience, improving the accuracy and consistency of the judgment. At the same time, there is no need to perform complex model training to achieve the quality recognition of large yellow croaker, with a fast recognition speed and low recognition cost. Further, by performing light-shielding treatment on the large yellow croaker, it can ensure that the body color of the large yellow croaker to be measured is fully displayed during detection. Combined with a wide spectral coverage, it helps to capture the body color information of the large yellow croaker more comprehensively, improving the scientificity and reliability of body color recognition. Further, by using the large yellow croaker with the best quality as a marker and setting the yellow degree recognition threshold, it can ensure the consistency and objectivity of the evaluation criteria. In this way, compared with the manual observation method, it reduces the influence of subjective factors on the detection results and ensures the accuracy of body color recognition. At the same time, compared with traditional sensors that can only recognize different colors such as red, yellow, and green, the method provided by the present invention uses a common color sensor and sets different yellow degree recognition thresholds according to market demands or quality standards, thereby realizing the recognition of very close different degrees of yellow and achieving the precise recognition and grading of large yellow croakers with different qualities. In this way, combining physical optics, spectral analysis, and image processing technologies makes the recognition of the body color of the large yellow croaker to be measured more scientific and reliable. By accurately calculating the target color parameters from the yellow light signal and comparing them with the yellow degree recognition threshold, the quality information of the large yellow croaker to be measured can be accurately and reliably determined. Description of the Drawings

[0022] Figure 1 It is a flowchart of the first embodiment of the automatic recognition method based on the golden body color of large yellow croaker provided by this application;

[0023] Figure 2 It is a schematic structural diagram of the first embodiment of the automatic recognition device based on the golden body color of large yellow croaker provided by this application. Detailed Embodiments

[0024] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0025] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a", "the", and "said" used in this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0026] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to a determination".

[0027] Specific embodiments are given below to introduce the technical solutions of this application in detail.

[0028] The automatic recognition method based on the golden body color of large yellow croaker provided by this application can be applied to the device for automatic recognition based on the golden body color of large yellow croaker. Specifically, in a possible implementation, the device for automatic recognition based on the golden body color of large yellow croaker can move the large yellow croaker through a conveyor belt, and the conveyor belt needs to have waterproof and anti-slip functions. Then, a high-resolution camera is installed above the conveyor belt, which is specifically used to capture the color and shape of the fish body. Further, LED lighting can be arranged around the camera to ensure uniform light source to improve the accuracy of color recognition. Then, an image processing unit is set up to calculate the values of multiple color channels based on the constructed RGB model and perform real-time image analysis. This unit can distinguish the golden body color of large yellow croaker from other colors and classify them; further, according to the results of image processing, a mechanical screening system is set up. For example, pneumatic or electric push rods are installed to push the fish into different collection boxes according to the recognition results. Further, a control panel is designed on one side of the device for the operator to monitor and adjust the device settings, including parameters such as sensitivity and speed. Finally, the device can be equipped with a data recording system to record the recognition results in real time for subsequent analysis and optimization.

[0029] Further, the reason why live large yellow croakers are silver-white during the day is that the pigment granules of xanthophores aggregate, while they are golden-yellow at night because the pigment granules of xanthophores disperse. The pigment granules of melanophores in live large yellow croakers are dispersed both during the day and at night.

[0030] In a specific implementation, in one embodiment, the color change of large yellow croaker is related to light. Under full-spectrum light (1000 lux) irradiation for 3 to 5 minutes, the body color changes from golden yellow to silver white, and the pigment granules of xanthophores contract; after shading for 30 to 40 minutes, the body color changes from silver white to golden yellow, and the pigment granules of xanthophores spread. When the body of the large yellow croaker (except the head) is blocked with opaque materials under light, the blocked part of the body is golden yellow, while the unblocked head is silver white. The pigment granules of xanthophores contract under light irradiation with different light intensities (10 - 6000 lux). After the large yellow croaker is irradiated with blue light (435 nm) for 2 minutes, the body color can change from golden yellow to silver white, and the degree of contraction of the pigment granules of xanthophores is the largest under blue light.

[0031] Figure 1 This is the flowchart of the first embodiment of the automatic recognition method based on the golden body color of large yellow croaker provided by this application. Please refer to Figure 1 , the method provided in this embodiment may include:

[0032] S101. Use the identified large yellow croaker as a marker to set the yellow degree recognition threshold of the color sensor.

[0033] Among them, the yellow degree recognition threshold is used to recognize different degrees of yellow, and different degrees of yellow correspond to different qualities. In a closed dark environment, receive the reflected light of the marker after being irradiated by the irradiation light. The setting of the yellow degree recognition threshold of the color sensor includes: using the color sensor to extract the first yellow reflection component from the reflected light of the marker and calculate the first reference color, and using the first reference color as the yellow degree recognition threshold.

[0034] Specifically, the identified large yellow croaker is a large yellow croaker that has been manually or preliminarily automatically screened, and the identified large yellow croaker contains the body color information of the large yellow croaker. It should be noted that the body color information of the large yellow croaker is golden yellow, and the better the quality of the large yellow croaker, the more obvious the golden yellow; while the golden yellow of the large yellow croaker with poor quality is not obvious. For example, in one embodiment, the large yellow croaker with the best quality has a golden yellow color, and the large yellow croaker with poor quality has a body color that is a mixture of silver white and golden yellow.

[0035] Furthermore, the marker is a reference for the yellow degree recognition threshold, and is used to set the yellow degree recognition threshold of the color sensor subsequently.

[0036] It should be noted that the marker can be the large yellow croaker with the best quality; or different grades of large yellow croakers can be divided according to the different body colors of the large yellow croaker as markers. For example, in one embodiment, inferior large yellow croakers, ordinary large yellow croakers, and high-quality large yellow croakers can be determined as markers.

[0037] Further, a color sensor is a device capable of sensing the spectral characteristics of light reflected, transmitted, or emitted by an object and determining the color of the object based thereon. Specifically, in implementation, the color sensor is used to capture the reflected light of the large yellow croaker.

[0038] Further, the yellow degree recognition threshold is a preset color range or standard for distinguishing large yellow croakers of different qualities. Specifically, in implementation, by setting the yellow degree recognition threshold, the color sensor can identify large yellow croakers that meet or are close to the yellow degree recognition threshold, thereby judging their qualities.

[0039] It can be understood that when screening the quality of large yellow croakers, there is a tendency to obtain large yellow croakers whose body colors are close to that of the large yellow croaker with the best quality. Therefore, the large yellow croaker with the best quality is determined as the marker.

[0040] Further, the first yellow reflection component is a spectral component related to yellow extracted from the reflected light of the marker, and then is quantified by the color sensor to determine the first yellow reflection component.

[0041] Further, the first reference color is a color value calculated based on the first yellow reflection component and serves as the benchmark for the yellow degree recognition threshold. It should be noted that since the marker is the large yellow croaker with the best quality, the first reference color represents the body color characteristics of the large yellow croaker with the best quality.

[0042] The following gives a specific embodiment for introducing in detail the process of obtaining the first reference color:

[0043] (1) Obtain the first yellow reflection component of the marker based on the color sensor in a dark environment.

[0044] Specifically, a dark environment is an environment without interference from natural light or artificial light sources. In a dark environment, the color sensor can more accurately capture the color characteristics of the large yellow croaker itself and avoid the influence of other lights on the recognition result.

[0045] Specifically, in implementation, in a dark environment, the spectral component related to yellow captured by the color sensor from the large yellow croaker with the best quality is the first yellow reflection component. The first yellow reflection component is the basis for subsequent color analysis and recognition.

[0046] (2) Obtain the first color parameter based on the first yellow reflection component and generate the first reference color.

[0047] Specifically, the first color parameter is a color characteristic value calculated based on the first yellow reflection component for describing the large yellow croaker. Specifically, in implementation, the hue, saturation, brightness, etc. corresponding to the first reflection component of the large yellow croaker with the best quality are obtained through the first yellow reflection component.

[0048] It can be understood that the body color characteristics of the large yellow croaker with the best quality can be described by the first color parameter.

[0049] The automatic recognition method based on the golden body color of the large yellow croaker provided in this embodiment uses the large yellow croaker with the best quality as a marker. The generated first reference color provides a stable benchmark for the subsequent recognition process, which helps the color sensor maintain a consistent judgment standard in the subsequent recognition tasks, reducing misjudgment and missed judgment. Further, the recognition threshold set based on the first reference color enables the color sensor to automatically recognize and screen out the large yellow croakers that meet the standards, improving the screening efficiency and accuracy, and reducing the cost and error rate.

[0050] Further, in the threshold adjustment mode of the color sensor, the lower limit of the yellow degree recognition threshold can be determined based on the color parameter of the marker. Then, continuously detect the large yellow croaker, and use the actual body color of the detected large yellow croaker as the color parameter of the upper limit of the yellow degree recognition threshold, and set the upper limit of the yellow degree recognition threshold based on this.

[0051] When specifically implemented, enter the yellow degree recognition threshold adjustment mode, press a specific key or combination of keys until the sensor enters the adjustment state. At this time, the sensor will display a specific indicator light or screen information to indicate that it is currently in the adjustment mode. Then, in the yellow degree recognition threshold adjustment mode, use the color sensor to scan the marker (the marker can be a large yellow croaker with a known color, a color card with a known color, or a scale of a large yellow croaker with a known color). Press the "ON" key (or a similar "setting" key) to make the sensor remember this color as the reference color. At this time, the "GOOD" green indicator light may flash, indicating that the lower limit of the yellow degree recognition threshold is being set. Next, this usually involves pressing the "OFF" key (or a similar "adjustment" key) to set the upper limit of the yellow degree recognition threshold. During the adjustment process, the proper setting of the yellow degree recognition threshold can be judged by observing the flashing states of the "GOOD" and "ERR" indicator lights. If the "GOOD" indicator light is always on, it means that the current color is within the yellow degree recognition threshold range; if the "ERR" indicator light flashes, it means that the current color exceeds the yellow degree recognition threshold range. According to the actual situation, gradually adjust the upper limit of the yellow degree recognition threshold until the required large yellow croaker yellow can be accurately recognized. Then, after adjusting the yellow degree recognition threshold, use multiple large yellow croaker samples with different colors for testing to verify whether the yellow degree recognition threshold set by the color sensor is accurate.

[0052] It should be noted that by setting the upper limit of the yellow degree recognition threshold, the color sensor can be prevented from misidentifying other colors.

[0053] Further, when detecting the body color of large yellow croakers, place the large yellow croakers in a dark environment so that there is no interference from ambient light. When the environment is not a dark environment, it is necessary to adjust to remove the interference of light in the environment.

[0054] Optionally, generate the light data to be adjusted based on the difference between the real-time background light information and the standard background light information;

[0055] Adjust the color sensor in combination with the light data to be adjusted.

[0056] Specifically, the real-time background light information is the data of the surrounding light conditions captured by the color sensor in the real-time working environment. In specific implementation, the real-time background light information may include parameters such as light intensity and spectral distribution, and the real-time background light information directly affects the recognition result of the body color of large yellow croakers by the color sensor.

[0057] Further, the standard background light information is the data of the light conditions that are most favorable for the recognition of the body color of large yellow croakers, which are preset or determined through multiple measurements. In specific implementation, the standard background light information can be determined based on a lightless dark environment.

[0058] Further, the light data to be adjusted is calculated based on the difference between the real-time background light information and the standard background light information and is used to adjust the light conditions. It should be noted that the light data to be adjusted may include parameters such as the light intensity that needs to be increased or decreased and the spectral distribution that needs to be adjusted.

[0059] Further, the target controller determines the light data to be adjusted based on the difference and adjusts the recognition parameters of the color sensor accordingly, so that the color sensor can work in an environment closer to the standard background light information.

[0060] Further, the light data to be adjusted can be determined based on the following formula:

[0061] ;

[0062] where Y is the calibrated parameter value, X n is the different color features read by the color sensor, a n is the corresponding weight parameter, and b is the calibration bias. It should be noted that the systematic error of the color sensor is compensated based on the calibration bias.

[0063] Optionally, the generating the light data to be adjusted and adjusting the color sensor in combination with the light data to be adjusted includes:

[0064] Detect the light difference between the real-time background light and the standard background light, and calculate the ambient yellow light reflection value according to the light difference;

[0065] Calculate the yellow light reflection change value of the large yellow croaker under the real-time background light according to the change relationship between the color of the large yellow croaker to be measured and the light intensity;

[0066] Use the color sensor to detect the yellow light electrical signal of the large yellow croaker to be measured;

[0067] Subtract the electrical signals corresponding to the ambient yellow light reflection value and the yellow light reflection change value of the large yellow croaker from the yellow light electrical signal to obtain the calibrated yellow light electrical signal;

[0068] Determine the quality information of the large yellow croaker to be measured based on the calibrated yellow light electrical signal.

[0069] The automatic recognition method based on the golden body color of the large yellow croaker provided in this embodiment can accurately calculate the ambient yellow light reflection value by detecting the light difference between the real-time background light and the standard background light, and can eliminate or reduce the influence of external environmental light changes on the detection results of the color sensor. Ensure that under different light conditions, the color sensor can accurately capture the yellow light reflection characteristics of the large yellow croaker itself, improving the accuracy and stability of the detection. Further, according to the change relationship between the color of the large yellow croaker and the light intensity, the influence of light changes on the body color reflection characteristics of the large yellow croaker is considered, and the true body color of the large yellow croaker under specific light conditions can be more accurately reflected, improving the accuracy of the quality information determination. Further, through the calibrated yellow light electrical signal, the interference of ambient light and light changes on the detection results is eliminated, making the final detection result closer to the yellow light reflection characteristics of the large yellow croaker itself, providing reliable data support for the subsequent quality information determination.

[0070] The automatic recognition method based on the golden body color of the large yellow croaker provided in this embodiment can ensure that the color sensor always adapts to the current environment by real-time monitoring and adjusting the light conditions, thereby reducing the color recognition error caused by the change of light conditions. This dynamic adjustment mechanism enables the color sensor to more accurately capture the golden body color characteristics of the large yellow croaker. Further, in the face of the working environment under different light conditions, the parameters of the color sensor are automatically adjusted by the target controller, and stable measurement work can be completed even in a complex and changeable light environment, improving the reliability of the large yellow croaker body color detection.

[0071] S102. Determine the first light avoidance time of the large yellow croaker to be measured, and process the large yellow croaker to be measured in a dark environment for the first light avoidance time length, and the color of the large yellow croaker before and after processing changes.

[0072] Specifically, the first light avoidance time is to determine a suitable light avoidance time length according to the body color change mechanism of large yellow croaker. It can be understood that the first light avoidance time needs to be long enough to ensure that the pigment granules in the xanthophores of large yellow croaker can fully diffuse. At the same time, the first light avoidance time cannot be too long to avoid adverse effects on large yellow croaker.

[0073] It should be noted that when large yellow croaker is subjected to light avoidance treatment, its body color will change from silver-white to golden-yellow. In other words, if the body surface color of large yellow croaker changes from silver-white to golden-yellow, it means that light avoidance makes the pigment granules in the xanthophores fully diffuse.

[0074] In specific implementation, the large yellow croaker to be tested is placed in a dark environment and processed according to the preset first light avoidance time. During the processing, it is necessary to ensure that the large yellow croaker will not be stimulated by any external light.

[0075] The following gives a specific embodiment to introduce in detail the process of obtaining the first light avoidance time:

[0076] (1) Detect the color change of the large yellow croaker to be tested in the dark environment and record the time point when the color of the large yellow croaker to be tested stops changing.

[0077] Specifically, when the large yellow croaker to be tested is in a dark environment, its body surface color gradually changes from silver-white to golden-yellow, and this change is caused by the diffusion of pigment granules in the xanthophores under the lack of light stimulation.

[0078] In specific implementation, when the color of the large yellow croaker to be tested stops changing, record the time point at this time.

[0079] (2) Determine the duration from when the large yellow croaker to be tested enters the dark environment to when its color stops changing as the first light avoidance time.

[0080] In specific implementation, determine the duration when the body color of the large yellow croaker to be tested stops changing as the first light avoidance time. After the first light avoidance time, the large yellow croaker can reach the best body color state under the same conditions. In specific implementation, the time point when the color change amplitude of the large yellow croaker to be tested is less than the predetermined amplitude within a certain time can be determined as the time point when the color of the large yellow croaker to be tested stops changing. For example, in one embodiment, a certain time is set to 1 minute, and the preset amplitude is set to a very small amplitude. When the color change of the large yellow croaker to be tested is less than the preset amplitude within 1 minute, it can be determined that the color of the large yellow croaker to be tested stops changing.

[0081] The automatic recognition method based on the golden body color of large yellow croaker provided by this embodiment accurately extracts the time required for the large yellow croaker to complete color change in the dark, and determines the first light avoidance time based on this, which can ensure that the large yellow croaker reaches the best body color state before color recognition, avoiding body color differences caused by insufficient or excessive processing time, thereby improving the accuracy of color recognition. Further, each large yellow croaker is processed according to the first light avoidance time, so that all large yellow croakers are in the same state during color evaluation, which helps to eliminate the influence of individual differences on the screening results and ensure the consistency of the screening results. Further, through the accurate first light avoidance duration, the adverse consequences caused by insufficient or excessive light shielding time can be avoided, and the reliability and scientificity of the body color detection of large yellow croaker are improved.

[0082] S103. Irradiate the large yellow croaker to be measured in a dark environment and detect the target reflected light.

[0083] Specifically, the irradiation light is a light mixed with lights of various colors, including all colors in the visible spectrum such as red, orange, yellow, green, blue, indigo, and violet. In specific implementation, a white light source (such as a white LED lamp) is used to irradiate the large yellow croaker to be measured in a dark environment. Through a wide spectral coverage, it can help the color sensor capture more details.

[0084] Further, when the irradiation light irradiates the large yellow croaker to be measured, part of the light will be reflected from the body surface of the large yellow croaker, and the reflected light contains information about the body color of the large yellow croaker, that is, the intensity and distribution of light with different wavelengths. The target reflected light is detected by a color sensor.

[0085] A specific embodiment is given below to introduce the specific implementation process of this step in detail:

[0086] (1) Determine the lightless environment as the dark environment.

[0087] In specific implementation, an environment with extremely weak light or no light at all is selected, resulting in the color sensor being unable to capture sufficient light signals from the surface of the large yellow croaker to be measured. In this environment, it can be ensured that the large yellow croaker to be measured is in a lightless environment, facilitating the change of the body color of the large yellow croaker to be measured.

[0088] (2) Determine the full-spectrum light source as the irradiation light, and irradiate the large yellow croaker to be measured in the dark environment based on the irradiation light.

[0089] Specifically, the full-spectrum light source can emit a light source containing all colors of light within the visible spectrum range. The light emitted by the full-spectrum light source has a wide spectral coverage, can simulate natural light or provide sufficient lighting conditions so that the color sensor can capture the complete color information of the object.

[0090] In specific implementation, the illumination of the large yellow croaker to be measured can be achieved by a white LED lamp or other types of illumination light sources.

[0091] The automatic recognition method based on the golden body color of large yellow croaker provided in this embodiment ensures that the large yellow croaker to be measured can obtain sufficient and uniform illumination in a dark environment through a full-spectrum light source, and stable target reflected light can be obtained. Further, irradiating the large yellow croaker to be measured with illumination light in a dark environment can significantly reduce the interference of ambient light. The traditional method using natural light may affect the recognition result of the color sensor, while the method provided in this application can effectively eliminate these interference factors by creating a dark environment close to no light, improving the accuracy of color recognition. Further, by adjusting the brightness and angle of the light source, it is possible to adapt to large yellow croaker screening scenarios of different scales and different illumination conditions, improving the reliability of large yellow croaker body color detection.

[0092] S104. Filter the target reflected light to obtain a yellow electrical signal.

[0093] Specifically, the target reflected light is the light that is irradiated on the large yellow croaker to be measured and reflected back by the large yellow croaker to be measured, and contains the body color information of the large yellow croaker.

[0094] Further, by filtering the target reflected light, the spectral components related to the body color (golden yellow) of the large yellow croaker can be screened out. In specific implementation, according to the spectral characteristics of the yellow color of the large yellow croaker to be measured, a suitable filter can be selected to screen out the spectral components related to the yellow color.

[0095] It should be noted that it is necessary to ensure the quality of the filter to avoid color recognition errors caused by filter quality problems.

[0096] The following gives a specific embodiment to introduce in detail the determination process of the yellow electrical signal:

[0097] (1) Filter the reflected light based on the filter to obtain light rays only containing the yellow light wavelength.

[0098] Specifically, the wavelength or frequency corresponding to the golden yellow light rays is screened out from the reflected light. In specific implementation, the reflected light is filtered by the filter. The filter only allows light rays with the yellow light wavelength to pass through, while blocking light rays with other wavelengths, obtaining light rays only containing the yellow light wavelength.

[0099] Further, regularly clean the sensor lens and the filter to prevent dust and dirt from affecting the accuracy of color recognition.

[0100] (2) Based on the photoelectric converter, receive the light rays with the yellow light wavelength and obtain the current change of the photoelectric converter.

[0101] Specifically, an optoelectronic converter is a device that can convert optical signals into electrical signals. In other words, the optoelectronic converter is used to receive filtered yellow light wavelength rays and convert them into electrical signals for subsequent processing and analysis.

[0102] In specific implementation, the optoelectronic converter can be determined as a photodiode. It should be noted that a photodiode with high sensitivity and low noise can be selected to improve the accuracy of optoelectronic conversion. It should be noted that when light irradiates on the photodiode, the energy of photons is absorbed by electrons, resulting in a current change, which is related to the intensity and wavelength of light. The wavelength of golden light is about 550 nanometers.

[0103] Furthermore, the electrical signal output by the photodiode can be processed with high precision, including amplification, filtering, etc., to reduce signal noise and interference.

[0104] (3)Determine the yellow optoelectronic signal based on the current change.

[0105] Specifically, the yellow optoelectronic signal refers to an electrical signal that only contains yellow light wavelength information after being filtered and optoelectronically converted.

[0106] In specific implementation, based on the monitored current change, through processing and analysis, the yellow optoelectronic signal is determined based on a high-resolution A / D converter.

[0107] Furthermore, after obtaining the yellow optoelectronic signal, a microcontroller with stable performance and fast processing speed can be selected to perform real-time processing and analysis on the yellow optoelectronic signal.

[0108] The automatic recognition method based on the golden body color of large yellow croaker provided in this embodiment filters out unnecessary spectral components through a filter, only retaining the light wavelengths related to yellow, significantly reducing the interference factors in the color recognition process, thereby improving the accuracy of color recognition. Furthermore, through the filtering process, it is ensured that the signals received by the color sensor mainly come from the golden body color of the large yellow croaker, reducing the interference of external factors such as ambient light and reflected light of other colors. Furthermore, the combined use of the filter and the optoelectronic converter makes the color recognition system have better adaptability to changes in light conditions. Even under unstable light intensity or changing light angles, it can still maintain a stable reception of yellow light wavelength rays through the screening effect of the filter.

[0109] The following gives a specific embodiment to introduce the filtering process in detail:

[0110] (1)Obtain the average spectral characteristics of a specified number of large yellow croakers.

[0111] Specifically, the specific value of the specified number is determined according to actual needs and is not limited in this embodiment.

[0112] Furthermore, the average spectral characteristic refers to the average reflection or transmission characteristic of these samples at each wavelength of the spectrum, which is calculated after measuring the spectral data of a specified number of large yellow croakers.

[0113] It should be noted that by the average spectral characteristic, the influence of individual differences of large yellow croakers on spectral data can be reduced, and more representative spectral characteristics of large yellow croakers can be obtained.

[0114] (2) Input the average spectral characteristic into the correspondence table between spectral information and filter model numbers to determine the model number of the optimal filter.

[0115] Specifically, the correspondence table between spectral information and filter model numbers is a pre-established table, which contains the corresponding relationships between different spectral characteristics and the model numbers of optimal filters. By querying this table, the model number of the optimal filter suitable for filtering the target reflected light can be quickly determined according to the average spectral characteristic of large yellow croakers.

[0116] Furthermore, the optimal filter can effectively screen out the light wavelengths related to the golden body color of large yellow croakers and filter out other interfering light wavelengths.

[0117] (3) Filter the target reflected light based on the optimal filter.

[0118] In specific implementation, select and install the optimal filter. When the target reflected light of large yellow croakers passes through the optimal filter, the optimal filter will screen out the light wavelengths related to the golden body color of large yellow croakers and allow these light rays to pass through, and other light wavelengths irrelevant to recognition will be blocked by the filter.

[0119] The automatic recognition method based on the golden body color of large yellow croakers provided in this embodiment can reduce the fluctuation of spectral data caused by individual differences by obtaining the average spectral characteristics of multiple large yellow croakers, making the subsequent color recognition more accurate. Furthermore, selecting the optimal filter model number according to the average spectral characteristic can more effectively filter out the light wavelengths irrelevant to the golden body color of large yellow croakers and reduce the interference factors in the color recognition process. Furthermore, due to the adoption of the filter selection method based on spectral characteristics, it can be adjusted according to the spectral characteristics of large yellow croaker samples in different batches and different growth environments, ensuring the accuracy and reliability of the body color recognition of large yellow croakers.

[0120] S105. Calculate the target color parameters according to the yellow electric signal.

[0121] Specifically, the target color parameters are a set of numerical values used to describe and quantify the golden body color characteristics of large yellow croakers. In specific implementation, the target color parameters can include hue, saturation, brightness, etc., which together constitute the color space representation of the body color of large yellow croakers.

[0122] In this step, the processed electrical signal is further analyzed using a color recognition algorithm, which calculates the target color parameters based on characteristics such as the intensity and waveform of the yellow electrical signal.

[0123] A specific embodiment is given below to introduce in detail the process of obtaining the target color parameters:

[0124] (1) Obtain the spectral information of the yellow electrical signal at different wavelengths; each spectral information has a corresponding preset number of color components.

[0125] Specifically, the spectral information refers to the intensity and distribution characteristics of the yellow electrical signal at different wavelengths.

[0126] It should be noted that the specific value of the preset number is set according to actual needs and is not limited in this embodiment. For example, in one embodiment, the preset number is 3.

[0127] Specifically, when implemented, the color components are the basic units that make up the color space, such as the red color component, the green color component, and the blue color component.

[0128] Furthermore, the spectral information can be calculated by the following formula:

[0129] S(λ)=[S(λ1), S(λ2),..., S(λ n )];

[0130] where λ represents the wavelength and S(λ) represents the vector of spectral information.

[0131] (2) Add up the spectral information included in each color component to calculate the corresponding component parameter value of the color component.

[0132] Specifically, when implemented, for each color component, the spectral information it contains is added up to calculate the parameter value of this color component. This parameter value reflects the intensity and characteristics of a color component in the body color of large yellow croaker.

[0133] (3) Fuse the component parameter values to obtain the target color parameters.

[0134] Specifically, when implemented, the target color parameters can be determined by the following formula:

[0135] ;

[0136] where R is the red color component, G is the green color component, B is the blue color component, λ is the wavelength data, R λ 、the G λ and the B λThey are the wavelength index sets corresponding to the red, green, and blue channels respectively.

[0137] It should be noted that RGB is an additive color model, which generates other colors based on different intensity combinations of the three primary colors: red, green, and blue. In specific implementation, the color of each pixel is mixed by different proportions of these three colors. During the process of identifying the golden body color of large yellow croakers, RGB can be used to capture the red, green, and blue component values of the yellow target reflected light in the large yellow croaker image for further color analysis and processing.

[0138] During the process of identifying the golden body color of large yellow croakers, the RGB model may be used to capture the red, green, and blue component values of each pixel in the large yellow croaker image, and these values can then be used for further color analysis and processing.

[0139] The automatic recognition method based on the golden body color of large yellow croakers provided in this embodiment can more accurately identify the target color parameters by precisely obtaining the spectral information of the yellow light component in the body color of large yellow croakers and performing detailed analysis and calculation on it. Further, by fusing the parameter values of each color component to obtain the target color parameters, more precise and scientific screening criteria can be formulated, improving the accuracy and effectiveness of screening.

[0140] S106. Determine the quality information of the large yellow croaker to be tested based on the target color parameters and the yellow degree recognition threshold.

[0141] Specifically, the quality information refers to the quality evaluation result of large yellow croakers obtained through color recognition and processing. It should be noted that the more yellow the golden body color of large yellow croakers, the higher the quality information. In specific implementation, the specific data type included in the quality information is determined according to actual needs, and this is not limited in this embodiment. For example, the quality information can be set as high-quality and ordinary.

[0142] In specific implementation, compare the target color parameters of the large yellow croaker to be tested with the yellow degree recognition threshold. If the target color parameters reach the yellow degree recognition threshold, it is considered that the quality of this large yellow croaker is "high-quality". If the target color parameters are lower than the yellow degree recognition threshold, it is considered that the quality of this large yellow croaker does not meet the high-quality standard, and record its quality information as "ordinary".

[0143] It should be noted that during the detection process of large yellow croakers, the color detector can be adjusted in real time based on a PID controller to make the detection result more accurate.

[0144] In specific implementation, the color sensor can be adjusted in real time based on the following formula:

[0145] ;

[0146] Among them, u(t) is the control output (such as the sensor adjustment value), e(t) is the error between the expected value and the actual value, Kp is the proportional gain, Ki is the integral gain, Kd is the derivative gain, and ∫e(τ)dτ is the integral of the error between the expected value and the actual value with respect to time. It should be noted that Kp reflects the direct influence of the deviation on the control quantity; Ki eliminates the static error by accumulating the deviation; Kd predicts future behavior based on the rate of change of the deviation; and ∫e(τ)dτ represents the past deviation.

[0147] The automatic recognition method based on the golden body color of large yellow croaker provided in this embodiment realizes the automatic recognition of the golden body color of large yellow croaker through a color sensor and subsequent processing of yellow photoelectric signals. Compared with the traditional manual screening method, it improves the screening efficiency and reduces the labor cost and error. Further, by accurately sensing the spectral characteristics of the body color of large yellow croaker through the color sensor and calculating the target color parameters through an algorithm, the recognition result of the body color of large yellow croaker is more accurate and reliable. Further, by setting the recognition threshold for the degree of yellow, it is ensured that the large yellow croaker selected meets certain standards in terms of body color, thus ensuring the reliability and scientificity of obtaining the quality information of large yellow croaker. In this way, the quality information of large yellow croaker can be accurately and reliably determined according to the target color parameters and the recognition threshold for the degree of yellow.

[0148] Corresponding to the foregoing embodiment of an automatic recognition method based on the golden body color of large yellow croaker, this application also provides an embodiment of an automatic recognition device based on the golden body color of large yellow croaker.

[0149] Figure 2 It is a schematic structural diagram of Embodiment 1 of the automatic recognition device based on the golden body color of large yellow croaker provided by this application. Please refer to Figure 2 The device provided in this embodiment includes a packaging module 210, a conveying module 220, an illumination module 230, a photographing module 240, a processing module 250, a screening module 260, a control module 270, and a recording module 280; except for the packaging module 210, each of the other modules is arranged in the packaging module 210. The illumination module 230 is fixed above the conveying module 220, the photographing module 240 is connected to the illumination module 230, the processing module 250 is connected to the photographing module 240, one end of the screening module 260 is fixed on the conveying module 220, the other end of the screening module 260 is fixed on the processing module 270, the control module 270 is connected to the processing module 250, and the recording module 280 is connected to the processing module 250, where:

[0150] The packaging module 210 is used as the basic framework of the device, encapsulating all other parts of the device and fixing the device;

[0151] The transfer module 220 is configured to move the large yellow croaker to be measured to a position where the shooting module can collect reflected light;

[0152] The lighting module 230 is configured to provide a light source to irradiate the large yellow croaker to be measured;

[0153] The shooting module 240 is configured to capture the target reflected light of the large yellow croaker to be measured;

[0154] The processing module 250 is configured to filter the target reflected light to obtain a yellow photoelectric signal, and calculate target color parameters according to the yellow photoelectric signal;

[0155] The screening module 260 is configured to determine the quality information of the large yellow croaker to be measured based on the target color parameters and the yellow degree recognition threshold, and classify the large yellow croaker to be measured based on the quality information;

[0156] The control module 270 is configured to adjust the parameters of the device based on adjustment information;

[0157] The recording module 280 is configured to record the classification result of the large yellow croaker to be measured.

[0158] The device of this embodiment can be used to execute Figure 1 the steps of the method embodiment shown. The specific implementation principle and process are similar and will not be elaborated here.

[0159] Furthermore, a strong metal material is used as the basic framework of the device to ensure stability and durability.

[0160] Furthermore, the transfer module 220 for moving the large yellow croaker needs to have waterproof and anti-slip functions.

[0161] Furthermore, the shooting module 240 can be a high-resolution camera installed above the transfer module 220, which is specifically used to capture the color and shape of the fish body. Multi-angle cameras can be considered to obtain comprehensive image data.

[0162] Furthermore, the lighting module 230 can be LED lighting arranged around the shooting module 240 to ensure uniform light source and improve the accuracy of color recognition.

[0163] Furthermore, the processing module 250 uses machine learning algorithms for real-time image analysis. This unit can distinguish the golden body color of the large yellow croaker from other colors and classify them.

[0164] Furthermore, the control module 270 can be a control panel designed on one side of the device for the operator to monitor and adjust device settings, including parameters such as sensitivity and speed. In specific implementation, an intuitive and user-friendly interface can be designed to facilitate the user to view color data, set parameters, and receive alarm information.

[0165] Furthermore, the screening module 260 can be a mechanical screening system set according to the results of image processing. In specific implementation, the screening module 260 can be installed with pneumatic or electric push rods to push the fish into different collection boxes according to the recognition results.

[0166] Furthermore, the recording module 280 is a equipped data recording system that records the recognition results in real time for subsequent analysis and optimization.

[0167] For the implementation processes of the functions and roles of each unit in the above device, please refer to the implementation processes of the corresponding steps in the above method for details, which will not be elaborated here.

[0168] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0169] The above are only the preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this application shall be included within the scope of protection of this application.

Claims

1. An automatic identification method based on the golden body color of large yellow croaker, characterized in that: The method comprises: Using the identified large yellow croaker as a marker, the yellow degree recognition threshold of the color sensor is set; Generate the illumination data to be adjusted based on the real-time background illumination information and the standard background illumination information, and adjust the color sensor; The adjusting the color sensor comprises: Detecting the illumination difference between the real-time background illumination and the standard background illumination, and calculating the ambient yellow light reflection value according to the illumination difference; Calculate the yellow light reflection change value of the large yellow croaker under the real-time background illumination according to the relationship between the color of the large yellow croaker to be tested and the light intensity; Utilizing the color sensor to detect the yellow photoelectric signal of the large yellow croaker to be tested; Subtracting the electrical signals corresponding to the ambient yellow light reflection value and the yellow light reflection change value of the large yellow croaker from the yellow photoelectric signal to obtain a calibrated yellow photoelectric signal; Determine the quality information of the large yellow croaker to be tested based on the calibrated yellow photoelectric signal; The yellow level recognition threshold is used to recognize different levels of yellow, and different levels of yellow correspond to different qualities. After receiving the reflected light of the marker after being irradiated by the light source, the yellow level recognition threshold of the color sensor is set, including: The large yellow croaker with the best quality is determined as a marker, a spectral component related to yellow is extracted from the marker, and a first yellow reflection component is determined by quantifying the spectral component through a color sensor; Calculating a yellow color value based on the first yellow reflection component as a reference for a yellow level recognition threshold, and determining the reference for the yellow level recognition threshold as the yellow level recognition threshold; The method of using the identified large yellow croaker as a marker to set the yellow degree recognition threshold of the color sensor includes: Acquire a first yellow reflection component of the marker in a dark environment based on the color sensor; Obtain the hue, saturation and brightness corresponding to the first reflection component of the large yellow croaker with the best quality through the first yellow reflection component, generate a first reference color; and use the first reference color as the yellow degree recognition threshold; Determine a first light-avoiding time for the large yellow croaker to be tested, subject the large yellow croaker to the first light-avoiding time in a dark environment, and the color of the large yellow croaker to be tested changes before and after the treatment; Illuminate the large yellow croaker to be tested in a dark environment to detect the reflected light of the target; Filtering the target reflected light to obtain a yellow photoelectric signal; Calculating target color parameters according to the yellow photoelectric signal; Based on the target color parameter and the yellow degree recognition threshold, the quality information of the large yellow croaker to be tested is determined.

2. The method according to claim 1, characterized in that The step of determining a first light-avoiding time for the large yellow croaker to be tested, and subjecting the large yellow croaker to be tested to a first light-avoiding time length in a dark environment, comprises: Detecting the change in color of the large yellow croaker to be tested under the dark environment, and recording the time point when the color of the large yellow croaker to be tested stops changing; The time from when the large yellow croaker to be tested enters the dark environment to when the color stops changing is determined as the first light-avoiding time.

3. The method according to claim 1, characterized in that The step of irradiating the large yellow croaker to be tested in a dark environment and detecting target reflected light comprises: Determine a dark environment as the dark environment; A full-spectrum light source is determined as the illumination light, and the large yellow croaker to be tested is illuminated in the dark environment based on the illumination light.

4. The method according to claim 1, characterized in that: The filtering of the target reflected light to obtain a yellow photoelectric signal comprises: Filtering the reflected light based on a filter to obtain light containing only yellow light wavelengths; Based on the photoelectric converter receiving light of yellow light wavelength, obtaining a current change of the photoelectric converter; The yellow photoelectric signal is determined based on the current change.

5. The method according to claim 1, characterized in that The calculating the target color parameter according to the yellow photoelectric signal comprises: Acquire spectrum information of different wavelengths of the yellow photoelectric signal; each spectrum information has a corresponding preset number of color components; Adding the spectral information contained in each of the color components, and calculating the component parameter value corresponding to the color component; The component parameter values ​​are fused to obtain the target color parameter.

6. The method according to claim 1, characterized in that The filtering of the target reflected light comprises: Get the average spectral characteristics of a specified number of large yellow croakers; Inputting the average spectral characteristics into a correspondence table of spectral information and filter models to determine the model of the best filter; The target reflected light is filtered based on the optimal filter.

7. The method according to claim 1, characterized in that Before setting the yellow level recognition threshold of the color sensor, the method further includes: Based on the gap between the real-time background illumination information and the standard background illumination information, the illumination data to be adjusted is generated; The color sensor is adjusted in combination with the light data to be adjusted.

8. An automatic identification device based on the golden body color of large yellow croaker, characterized in that: The device is applied to the method described in any one of claims 1 to 7, and the device comprises a packaging module, a transmission module, a lighting module, a shooting module, a processing module and a screening module; each module except the packaging module is arranged in the packaging module, the lighting module is fixed above the transmission module, one end of the screening module is fixed on the transmission module, and the other end of the screening module is fixed on the processing module, wherein: The packaging module is used to serve as a basic frame of the device to fix the device; The transmission module is used to move the large yellow croaker to be tested to a position where the shooting module can collect reflected light; The lighting module is used to provide light to illuminate the large yellow croaker to be tested; The shooting module is used to capture the target reflected light of the large yellow croaker to be tested; The processing module is used to filter the target reflected light to obtain a yellow photoelectric signal, and calculate the target color parameter according to the yellow photoelectric signal; The screening module is connected to a plurality of quality channels; the screening module is used to determine the quality information of the large yellow croaker to be tested based on the target color parameter and the yellow degree recognition threshold, and to place the large yellow croaker to be tested into different quality channels based on the quality information.

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