CN111968096B - Method and system for detecting white spot syndrome virus of prawns based on surface features - Google Patents
Method and system for detecting white spot syndrome virus of prawns based on surface features Download PDFInfo
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- 241000238557 Decapoda Species 0.000 title claims abstract description 154
- 241000696962 White spot syndrome virus Species 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 25
- 241000700605 Viruses Species 0.000 claims description 25
- 238000012545 processing Methods 0.000 claims description 18
- 239000003086 colorant Substances 0.000 claims description 10
- 230000007613 environmental effect Effects 0.000 claims description 10
- 230000005059 dormancy Effects 0.000 claims description 8
- 208000011580 syndromic disease Diseases 0.000 claims description 5
- 230000010365 information processing Effects 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 208000015181 infectious disease Diseases 0.000 abstract description 3
- 241000519995 Stachys sylvatica Species 0.000 description 5
- 201000010099 disease Diseases 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 5
- 241000701447 unidentified baculovirus Species 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 230000034994 death Effects 0.000 description 2
- 241001124325 Marsupenaeus japonicus Species 0.000 description 1
- 241000318927 Shrimp white spot syndrome virus Species 0.000 description 1
- 230000001154 acute effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001684 chronic effect Effects 0.000 description 1
- 238000012258 culturing Methods 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003394 haemopoietic effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000017074 necrotic cell death Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000007920 subcutaneous administration Methods 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 230000009885 systemic effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
Abstract
The invention provides a method and a system for detecting white spot syndrome virus of prawns based on surface features, comprising the following steps: acquiring picture information in the culture pond through an underwater camera; selecting candidate points which are possibly shrimp by vertically scanning the image, and adding the candidate points into a candidate point queue; the shrimp position is obtained from the shrimp surface characteristic information in the candidate area corresponding to the candidate point; judging whether the shrimp is infected with white and non-white pixel proportion of the shrimp head and chest nail region. The invention can detect and find out whether the shrimp infects the white spot syndrome virus of the shrimp in the cultured shrimp. Reduce the possibility of infection of the white spot syndrome virus among cultured shrimps and minimize the harm caused by the white spot syndrome virus.
Description
Technical Field
The invention relates to the technical field of shrimp disease detection, in particular to a method and a system for detecting white spot syndrome virus of shrimps based on surface characteristics.
Background
The white spot syndrome virus disease of prawns is the virus disease which has the greatest harm to prawns in culture worldwide. The virus disease is not named uniformly, and comprises white spot baculovirus, subcutaneous and hematopoietic tissue necrosis baculovirus, penaeus japonicus baculovirus, systemic ectodermal and mesodermal baculovirus and the like. Since the outbreak of the disease in 1993, large-scale destructive death of the prawns occurs annually, and almost all the cultured prawns can be infected by the prawns. The mortality rate of infection reaches 100% within 3 to 10 days. In view of the fact that no effective treatment method is available, how to rapidly discover the white spot syndrome virus of the prawns is one of the focuses of research.
Currently, the discovery of the white spot syndrome virus of the prawns mainly depends on a direct observation method, and the direct observation method is used for judging typical symptoms of the white spot syndrome according to acute and chronic death conditions of the prawns in the culture process. For example, white spots appear on the chest armor, the crust becomes soft and is easy to peel, and the method is mainly judged according to practical experience and can be found only after the shrimp is infected with virus to be killed. Therefore, by adopting a direct observation method, repeated sampling observation is required for the prawns, the operation is complex, the judgment basis is not uniform, judgment conclusion cannot be made in advance in the cultivation process, and the early warning effect is achieved.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a method and a system for detecting the white spot syndrome virus of the prawns based on surface features, which detect and identify the white spot syndrome virus of the prawns by adopting a surface feature identification method. And judging whether the shrimp is infected with white spot syndrome virus by judging whether white spots appear on shrimp head chest nails through shrimp pictures shot by the camera. Wherein, the surface features refer to specific information of the surface of the object.
The invention aims to achieve the aim, and the aim is achieved by the following technical scheme: a method for detecting white spot syndrome virus of prawns based on surface features comprises the following steps:
s1, acquiring pictures in a shrimp culture pond through an underwater camera;
s2, vertically scanning the picture, obtaining candidate points of the cultured shrimps in the picture information, and adding the candidate points into a candidate point queue;
s3, adjusting a coordinate system of the picture information to enable the picture information to correspond to an actual environment;
s4, determining whether the cultured shrimps exist in the candidate area or not by scanning the candidate area corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp colors and the environmental colors of pixels in the candidate area, and if not, deleting the corresponding candidate points of the cultured shrimps from the candidate point queue;
s5, analyzing the white and non-white proportion of the shrimp shells of pixels in the candidate areas corresponding to the candidate points of each cultured shrimp, judging whether the corresponding cultured shrimp is infected with viruses, and if so, sending out alarm information; if not, returning to the step S1.
Further, the step S1 includes:
starting an underwater camera to collect pictures in the shrimp culture pond through a hardware instruction or a software instruction;
after the photo is acquired, the underwater camera uploads the acquired image to a preset processing system for reading and processing.
Further, the step S2 includes:
reading out the pictures in a file stream form;
scanning the picture from left to right by using a vertical scanning line to finish the scanning information processing of all pixels of the picture;
recording color information of pixel points on a scanning line, primarily screening an area formed by the pixel points with the same color, calculating the center point position of the area through the upper end and the lower end of the area with the same color and the left end and the right end of the area with the same color of the scanning line, and taking the center point position as a candidate point of the cultured shrimps;
and adding the selected candidate points of the cultured shrimps into a candidate point queue.
Further, the scanning the picture from left to right using the vertical scan line includes:
setting a scanning step length of a vertical scanning line;
the vertical scan lines scan the picture from left to right with a set scan step size.
Further, the step S3 includes:
and converting the picture information from an image coordinate system to a world coordinate system, so that the picture information corresponds to the actual environment.
Further, the step S4 includes:
dividing candidate areas by taking a candidate point of the cultured shrimps as a center and taking a preset scanning radius as a radius; the distance information of the scanning radius is obtained by acquiring coordinate information in a world coordinate system;
calculating the proportion of the shrimp color and the environmental color of the pixels in each candidate area as an image judgment value, and if the image judgment value is greater than or equal to a preset threshold value, the candidate area contains the image information of the cultured shrimps; if the image judgment value is smaller than the preset color proportion threshold value, the candidate area does not contain the image information of the cultured shrimps, and the candidate points of the cultured shrimps corresponding to the candidate area are deleted from the candidate point queue.
Further, the step S5 includes:
processing and analyzing candidate areas corresponding to the candidate points of the cultured shrimps reserved in the candidate point queues; calculating the ratio of pixel points of a white area to pixel points of a non-white area on the shrimp crustacean in the candidate area, and taking the ratio as a virus judgment value;
if the virus judgment value is greater than or equal to a preset pixel proportion threshold value, judging that the shrimp infects the white spot syndrome virus of the shrimp and sending out alarm information;
if the virus judgment value is smaller than the preset pixel proportion threshold value, detecting that shrimps infected with white-shift syndrome viruses exist in the candidate area, and sending a dormancy instruction to the underwater camera, so that the underwater camera executes dormancy operation to wait for the next instruction to wake up.
Correspondingly, the invention also discloses a prawn white spot syndrome virus detection system based on the surface characteristics, which comprises:
the acquisition unit is used for acquiring pictures in the shrimp culture pond through the underwater camera;
the first scanning unit is used for vertically scanning the picture and obtaining candidate points of the cultured shrimps in the picture information; the coordinate system adjusting unit is used for adjusting the coordinate system of the picture information to enable the picture information to correspond to the actual environment;
the second scanning unit is used for determining whether the cultured shrimps exist in the candidate areas by scanning the candidate areas corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp colors and the environmental colors of pixels in the candidate areas;
and the analysis unit is used for analyzing the proportion of the white pixels of the shrimp crust to the non-white pixels of the shrimp in the candidate area corresponding to the candidate point of each cultured shrimp and judging whether the corresponding cultured shrimp is infected with viruses.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a method and a system for detecting white spot syndrome virus of prawns based on surface characteristics, wherein image information of a culture pond is obtained through an underwater camera; selecting candidate points which are possibly shrimps through vertical scanning; the shrimp position is obtained through the shrimp surface characteristic information in the candidate points and the candidate radius; judging whether the shrimp infects the white spot syndrome virus of the shrimp or not by judging whether the white spot appears on the shrimp head and chest armor or not. The invention can detect and find out whether the shrimp infects the white spot syndrome virus of the shrimp in the cultured shrimp. Reduce the possibility of infection of the white spot syndrome virus among cultured shrimps and minimize the harm caused by the white spot syndrome virus.
It can be seen that the present invention has outstanding substantial features and significant advances over the prior art, as well as the benefits of its implementation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a system configuration diagram of the present invention.
Detailed Description
The following describes specific embodiments of the present invention with reference to the drawings.
The method for detecting the white spot syndrome virus of the prawns based on the surface features shown in the figure 1 comprises the following steps:
s1, acquiring pictures in the shrimp culture pond through an underwater camera.
Firstly, starting an underwater camera to collect pictures in a shrimp culture pond through a hardware instruction or a software instruction; after the photo is acquired, the underwater camera uploads the acquired image to a preset processing system for reading and processing. The hardware instruction is to manually press a physical switch, and the software instruction triggers the photographing function to collect the photos at regular time. After the photo collection work is carried out once, the underwater camera can upload the collected images to a local computer for reading and processing through a preset processing system.
And S2, vertically scanning the picture, obtaining candidate points of the cultured shrimps in the picture information, and adding the candidate points into a candidate point queue.
Firstly, reading out pictures stored by a local computer in a file stream mode; the preset processing system scans the picture from left to right by using a vertical scanning line to finish the scanning information processing of all pixels of the picture; in order to improve the efficiency of the system in processing pictures, a scanning operation is performed by setting the step length of a scanning line, and not every column of pixels from left to right is scanned. By setting the scan line step size and the scan line spacing, the processing speed of the system for pictures is increased but the accuracy of some picture processing is sacrificed because part of the pixel information is ignored. If the time cost is acceptable, the scanning step size can be set to be 1, and the system can process the scanning information on all pixels of the picture.
After the scanning is finished, the preset processing system records the color information of the pixel points on the scanning line, the area formed by the pixel points with the same color is subjected to preliminary screening, the center point position of the area is calculated through the upper end and the lower end of the area with the same color and the left end and the right end of the area with the same color of the scanning line, and the center point position is used as a candidate point for culturing shrimps. And finally, adding the candidate points of the selected cultured shrimps into a candidate point queue.
And S3, adjusting a coordinate system of the picture information to enable the picture information to correspond to the actual environment.
Specifically, the picture information is converted from an image coordinate system to a world coordinate system, so that the picture information corresponds to an actual environment.
S4, determining whether the cultured shrimps exist in the candidate area or not by scanning the candidate area corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp colors and the environmental colors of pixels in the candidate area, and if not, deleting the corresponding candidate points of the cultured shrimps from the candidate point queue.
The processing system divides the candidate areas by taking the candidate points of the cultured shrimps as the center and taking the scanning radius as the radius according to the preset scanning radius. The scanning radius information is affected by the distance between the target object and the camera, and the distance information is obtained by acquiring coordinate information in a world coordinate system. The scan radius should be larger when the candidate point is closer to the camera and smaller when the candidate point is farther from the camera. The scan radius is typically set to be 0.6 to 0.75 times the length of the target object. Then calculating the ratio of the shrimp color to the environmental color in each candidate area as an image judgment value, and if the image judgment value is greater than or equal to a preset threshold value, the candidate areas contain image information of the cultured shrimps; if the image judgment value is smaller than the preset color proportion threshold value, the candidate area does not contain the image information of the cultured shrimps, and the candidate points of the cultured shrimps corresponding to the candidate area are deleted from the candidate point queue.
S5, analyzing the white and non-white proportion of the shrimp shells of pixels in the candidate areas corresponding to the candidate points of each cultured shrimp, judging whether the corresponding cultured shrimp is infected with viruses, and if so, sending out alarm information; if not, returning to the step S1.
Firstly, processing and analyzing candidate areas corresponding to candidate points of the cultured shrimps reserved in the candidate point queues; and calculating the ratio of the pixel points of the white area to the pixel points of the non-white area on the shrimp crustacean shell in the candidate area, and taking the ratio as a virus judgment value. If the virus judgment value is greater than or equal to a preset pixel proportion threshold value, judging that the shrimp infects the white spot syndrome virus of the shrimp and sending out alarm information; if the virus judgment value is smaller than the preset pixel proportion threshold value, detecting that shrimps infected with white-shift syndrome viruses exist in the candidate area, and sending a dormancy instruction to the underwater camera, so that the underwater camera executes dormancy operation to wait for the next instruction to wake up.
In addition, on the basis of the method for detecting the white spot syndrome virus of the prawns based on the surface features, a cascading classifier mode can be used, and a shrimp picture infected with the white spot syndrome virus of the prawns is used as a training sample to train a recognition model of the shrimp infected with the white spot syndrome virus of the prawns. When the camera acquires the picture information of the cultured shrimps, the picture information is input into a model file for verification, and whether the shrimps are infected with the white spot syndrome virus or not in the image is judged.
Correspondingly, as shown in fig. 2, the invention also discloses a prawn white spot syndrome virus detection system based on surface features, which comprises:
the acquisition unit is used for acquiring pictures in the shrimp culture pond through the underwater camera.
And the first scanning unit is used for vertically scanning the picture and acquiring candidate points of the cultured shrimps in the picture information.
And the coordinate system adjusting unit is used for adjusting the coordinate system of the picture information so that the picture information corresponds to the actual environment.
And the second scanning unit is used for determining whether the cultured shrimps exist in the candidate area by scanning the candidate area corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp color and the environmental color of the pixels in the candidate area.
And the analysis unit is used for analyzing the proportion of the white pixels of the shrimp crust to the non-white pixels of the shrimp in the candidate area corresponding to the candidate point of each cultured shrimp and judging whether the corresponding cultured shrimp is infected with viruses.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems, and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted or not performed.
The invention will be further described with reference to the accompanying drawings and specific embodiments. It is to be understood that these examples are illustrative of the present invention and are not intended to limit the scope of the present invention. Further, it will be understood that various changes or modifications may be made by those skilled in the art after reading the teachings of the invention, and such equivalents are intended to fall within the scope of the invention as defined herein.
Claims (6)
1. The method for detecting the white spot syndrome virus of the prawns based on the surface features is characterized by comprising the following steps:
s1, acquiring pictures in a shrimp culture pond through an underwater camera;
s2, vertically scanning the picture, obtaining candidate points of the cultured shrimps in the picture information, and adding the candidate points into a candidate point queue;
s3, adjusting a coordinate system of the picture information to enable the picture information to correspond to an actual environment;
s4, determining whether the cultured shrimps exist in the candidate area or not by scanning the candidate area corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp colors and the environmental colors of pixels in the candidate area, and if not, deleting the corresponding candidate points of the cultured shrimps from the candidate point queue;
s5, analyzing the white and non-white proportion of the shrimp shells of pixels in the candidate areas corresponding to the candidate points of each cultured shrimp, judging whether the corresponding cultured shrimp is infected with viruses, and if so, sending out alarm information; if not, returning to the step S1;
the step S4 includes:
dividing candidate areas by taking a candidate point of the cultured shrimps as a center and taking a preset scanning radius as a radius; the distance information of the scanning radius is obtained by acquiring coordinate information in a world coordinate system;
calculating the proportion of the shrimp color and the environmental color of the pixels in each candidate area as an image judgment value, and if the image judgment value is greater than or equal to a preset threshold value, the candidate area contains the image information of the cultured shrimps; if the image judgment value is smaller than the preset color proportion threshold value, the candidate area does not contain the image information of the cultured shrimps, and the candidate points of the cultured shrimps corresponding to the candidate area are deleted from the candidate point queue;
the step S5 includes:
processing and analyzing candidate areas corresponding to the candidate points of the cultured shrimps reserved in the candidate point queues;
calculating the ratio of pixel points of a white area to pixel points of a non-white area on the shrimp crustacean in the candidate area, and taking the ratio as a virus judgment value;
if the virus judgment value is greater than or equal to a preset pixel proportion threshold value, judging that the shrimp infects the white spot syndrome virus of the shrimp and sending out alarm information;
if the virus judgment value is smaller than the preset pixel proportion threshold value, detecting that shrimps infected with white-shift syndrome viruses exist in the candidate area, and sending a dormancy instruction to the underwater camera, so that the underwater camera executes dormancy operation to wait for the next instruction to wake up.
2. The method for detecting white spot syndrome virus based on surface features as claimed in claim 1, wherein the step S1 comprises:
starting an underwater camera to collect pictures in the shrimp culture pond through a hardware instruction or a software instruction;
after the photo is acquired, the underwater camera uploads the acquired image to a preset processing system for reading and processing.
3. The method for detecting white spot syndrome virus based on surface features as claimed in claim 1, wherein said step S2 comprises:
reading out the pictures in a file stream form;
scanning the picture from left to right by using a vertical scanning line to finish the scanning information processing of all pixels of the picture;
recording color information of pixel points on a scanning line, primarily screening an area formed by the pixel points with the same color, calculating the center point position of the area through the upper end and the lower end of the area with the same color and the left end and the right end of the area with the same color of the scanning line, and taking the center point position as a candidate point of the cultured shrimps;
and adding the selected candidate points of the cultured shrimps into a candidate point queue.
4. The method for detecting white spot syndrome virus based on surface features according to claim 3, wherein scanning the picture from left to right using the vertical scan line comprises:
setting a scanning step length of a vertical scanning line;
the vertical scan lines scan the picture from left to right with a set scan step size.
5. The method for detecting white spot syndrome virus based on surface features according to claim 3, wherein the step S3 comprises:
and converting the picture information from an image coordinate system to a world coordinate system, so that the picture information corresponds to the actual environment.
6. A surface feature-based system for detecting white spot syndrome virus in prawns, comprising:
the acquisition unit is used for acquiring pictures in the shrimp culture pond through the underwater camera;
the first scanning unit is used for vertically scanning the picture and obtaining candidate points of the cultured shrimps in the picture information;
the coordinate system adjusting unit is used for adjusting the coordinate system of the picture information to enable the picture information to correspond to the actual environment;
the second scanning unit is used for determining whether the cultured shrimps exist in the candidate areas by scanning the candidate areas corresponding to the candidate points of the cultured shrimps and calculating the proportion of the shrimp colors and the environmental colors of pixels in the candidate areas;
the analysis unit is used for analyzing the proportion of the white pixels of the shrimp crust to the non-white pixels of the crust in the candidate area corresponding to the candidate point of each cultured shrimp and judging whether the corresponding cultured shrimp is infected with viruses or not;
the second scanning unit is specifically configured to: dividing candidate areas by taking a candidate point of the cultured shrimps as a center and taking a preset scanning radius as a radius; the distance information of the scanning radius is obtained by acquiring coordinate information in a world coordinate system;
calculating the proportion of the shrimp color and the environmental color of the pixels in each candidate area as an image judgment value, and if the image judgment value is greater than or equal to a preset threshold value, the candidate area contains the image information of the cultured shrimps; if the image judgment value is smaller than the preset color proportion threshold value, the candidate area does not contain the image information of the cultured shrimps, and the candidate points of the cultured shrimps corresponding to the candidate area are deleted from the candidate point queue;
the analysis unit is specifically configured to: processing and analyzing candidate areas corresponding to the candidate points of the cultured shrimps reserved in the candidate point queues;
calculating the ratio of pixel points of a white area to pixel points of a non-white area on the shrimp crustacean in the candidate area, and taking the ratio as a virus judgment value;
if the virus judgment value is greater than or equal to a preset pixel proportion threshold value, judging that the shrimp infects the white spot syndrome virus of the shrimp and sending out alarm information;
if the virus judgment value is smaller than the preset pixel proportion threshold value, detecting that shrimps infected with white-shift syndrome viruses exist in the candidate area, and sending a dormancy instruction to the underwater camera, so that the underwater camera executes dormancy operation to wait for the next instruction to wake up.
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| CN112907566A (en) * | 2021-03-19 | 2021-06-04 | 东营市阔海水产科技有限公司 | Prawn eye disease detection method, terminal device and storage medium |
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