CN113256647A - Image processing method, image processing apparatus, electronic apparatus, and storage medium - Google Patents
Image processing method, image processing apparatus, electronic apparatus, and storage medium Download PDFInfo
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Abstract
The application discloses an image processing method, an image processing apparatus, an electronic apparatus, and a storage medium. The image processing method comprises the following steps: the method comprises the steps of obtaining a target image of the breeding system shot by a shooting device, identifying a target area in the target image, and marking the target area based on epidemic prevention level according to an identification result to show the epidemic prevention level of the target area. According to the image processing method, the target image of the breeding system shot by the shooting device is obtained, the target area in the target image is identified, the target area is marked and processed to visually display the epidemic prevention level of the target area, each area of the breeding system can be clearly divided, the epidemic prevention level of each area can be visually shown through marking, and therefore workers can conveniently and effectively conduct epidemic prevention management and control on the breeding system.
Description
Technical Field
The present application relates to the field of electronic technologies, and in particular, to an image processing method, an image processing apparatus, an electronic apparatus, and a storage medium.
Background
Epidemic situations such as African swine fever become normalization, and due to the weak virus characteristic of a new round of African swine fever, a farmer is difficult to complete hundreds of non-pestilence purification to all pig farms in a short time, once a pig farm is infected with a new weak-virus African swine fever virus, the purification is very difficult to remove, so that the production of the pig farm is seriously influenced. Therefore, the control of epidemic prevention in pig farms is very important, and how to take convenient and effective measures to control the epidemic prevention in pig farms to prevent the swine fever virus from infecting the pig farms becomes a problem to be solved.
Disclosure of Invention
The application provides an image processing method, an image processing apparatus, an electronic apparatus, and a storage medium.
The application provides an image processing method for an electronic device, the image processing method comprising:
acquiring a target image of the breeding system shot by a shooting device;
identifying a target area in the target image;
and according to the identification result, marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area.
According to the image processing method, the target image of the breeding system shot by the shooting device can be obtained, the target area in the target image is identified, and the target area is marked and processed to visually display the epidemic prevention level of the target area, so that each area of the breeding system can be clearly divided through the image processing method, the epidemic prevention level of each area can be visually shown through marking, and workers can conveniently and effectively carry out epidemic prevention management and control on the breeding system.
In some embodiments, the identifying the target region in the target image comprises:
comparing the similarity of the pre-processing region and the predetermined region;
and under the condition that the similarity is larger than a preset value, determining the pretreatment area as a target area, wherein the target area comprises at least one of a living area, a breeding area and an environmental protection area.
In some embodiments, the identifying the target region in the target image comprises:
identifying a plurality of building images which are arranged in a matrix form in the target image;
and confirming areas of the plurality of buildings as cultivation areas, wherein the target area comprises the cultivation areas.
In some embodiments, the image processing method includes:
identifying a closed graph area connecting the plurality of buildings and a living area;
and confirming the closed graph area as a corridor structure area, wherein the target area comprises the corridor structure area.
In some embodiments, the identifying the target region in the target image comprises:
extracting a green land area in the pre-treatment region;
and under the condition that the green land area is larger than a preset area, determining that the pretreatment area is an environment-friendly area, wherein the target area comprises the environment-friendly area.
In some embodiments, the performing, according to the identification result, a marking process on the target area based on the epidemic prevention level to show the epidemic prevention level of the target area comprises:
numbering the target areas, wherein the number is in direct proportion to the epidemic prevention level.
In some embodiments, the performing, according to the identification result, a marking process on the target area based on the epidemic prevention level to show the epidemic prevention level of the target area comprises:
and carrying out color filling on the target area, wherein the larger the color temperature of the filled color is, the lower the epidemic prevention level is.
The application provides an image processing apparatus, the image processing apparatus includes:
the acquisition module is used for acquiring a target image of the breeding system shot by the shooting device;
the identification module is used for identifying a target area in the target image;
and the processing module is used for marking the target area based on the epidemic prevention level according to the identification result so as to show the epidemic prevention level of the target area.
The application provides an electronic device, the electronic device includes a processor, the processor is used for obtaining the target image of the farming systems that the shooting device was shot, and is used for discerning the target area in the target image to and be used for according to the recognition result, on the basis of epidemic prevention grade and to the mark processing is made to the target area in order to show the epidemic prevention grade in target area.
In some embodiments, the present application provides a non-volatile computer-readable storage medium storing a computer program, which when executed by one or more processors implements the image processing method of any one of the above embodiments.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flowchart of an image processing method according to an embodiment of the present application;
FIG. 2 is a block diagram of an image processing apparatus according to an embodiment of the present application;
fig. 3 is a schematic perspective view of an electronic device according to an embodiment of the present application;
FIG. 4 is a flowchart illustrating an image processing method according to an embodiment of the present application
FIG. 5 is a schematic flow chart of an image processing method according to an embodiment of the present application;
FIG. 6 is a schematic flow chart of an image processing method according to an embodiment of the present application;
FIG. 7 is a schematic flow chart of an image processing method according to an embodiment of the present application;
FIG. 8 is a schematic flow chart of an image processing method according to an embodiment of the present application;
FIG. 9 is a schematic flow chart of an image processing method according to an embodiment of the present application;
fig. 10 is a schematic diagram of an image obtained by applying an image processing method according to an embodiment of the present application.
Description of the main elements and symbols:
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and are only for the purpose of explaining the present application and are not to be construed as limiting the present application.
The following disclosure provides many different embodiments or examples for implementing different features of the application. In order to simplify the disclosure of the present application, specific example components and arrangements are described below. Of course, they are merely examples and are not intended to limit the present application. Moreover, the present application may repeat reference numerals and/or letters in the various examples, such repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. In addition, examples of various specific processes and materials are provided herein, but one of ordinary skill in the art may recognize applications of other processes and/or use of other materials.
Referring to fig. 1, an embodiment of the present application provides an image processing method for an electronic device 100 (shown in fig. 3), where the image processing method includes:
step S10: acquiring a target image of the breeding system shot by a shooting device;
step S20: identifying a target area in a target image;
step S30: and according to the identification result, marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area.
Referring to fig. 2, an embodiment of the present application provides an image processing apparatus 200, where the image processing apparatus 200 includes an obtaining module 21, an identifying module 22, and a processing module 23. The image processing method according to the present embodiment can be realized by the image processing apparatus 200 according to the present embodiment. For example, step S10 may be implemented by the acquisition module 21 of the image processing apparatus 200, step S20 may be implemented by the recognition module 22 of the image processing apparatus 200, and step S30 may be implemented by the processing module 23 of the image processing apparatus 200.
In other words, the acquiring module 21 is configured to acquire a target image of the cultivation system captured by the capturing device, and the identifying module 22 is configured to identify a target area in the target image; the processing module 23 is configured to perform a marking process on the target area based on the epidemic prevention level according to the identification result to show the epidemic prevention level of the target area.
Referring to fig. 3, an embodiment of the present application further provides an electronic device 100, where the electronic device 100 includes a processor 11, where the processor 11 is configured to obtain a target image of a breeding system captured by a capturing device, identify a target area in the target image, and mark the target area based on an epidemic prevention level according to an identification result to show an epidemic prevention level of the target area. The electronic device 100 may further comprise a memory 12, the memory 12 may be used for storing computer programs.
It should be noted that, in a modern breeding system, a pig farm for raising pigs has a certain large scale, and in the case that epidemic situations such as african swine fever become normalized, because there is no effective vaccine or drug for prevention and treatment at present, in order to avoid that the pigs are infected with the african swine fever only, which causes serious influence on the production of the pig farm, strict epidemic prevention grades need to be classified for the breeding system, and a perfect monitoring scheme is established, which can be understood as requiring strict implementation by workers.
In order to more intuitively display the epidemic prevention level of each region of the breeding system and enable workers to conveniently and efficiently take corresponding epidemic prevention measures according to different levels so as to control the breeding system, the image processing method is provided in the application, the target image of the breeding system shot by the shooting device is obtained, then the target region in the target image is identified, and then the target region is marked to intuitively display the epidemic prevention level of the target region. Like this, alright clearly divide out each region of farming systems, then can show the epidemic prevention grade in each region directly perceivedly through the mark processing to let the staff can conveniently carry out the epidemic prevention management and control to farming systems effectively.
Specifically, the shooting device in this application embodiment can be the camera, and is corresponding, and electronic device 100 can be the unmanned aerial vehicle who has carried on the camera, has the function of taking photo by plane, because this type of electronic device 100's chip can also integrate image processing, functions such as video codec except that the shooting image for electronic device 100 can directly handle the image that the shooting device was taken, and the user can directly acquire the image that electronic device 100 handled and accomplished the output, and efficiency is higher.
However, in the present application, it is necessary to acquire a target image of the entire cultivation system and identify the target image, which requires the target image of the cultivation system photographed by the photographing device to be complete and clear, that is, the photographing device needs to photograph at a higher height as much as possible while ensuring its own performance.
At this time, since the aerial photography has a certain limit to the airspace, in order to ensure the quality of the acquired target image and the safety of the shooting approach, the target image of the breeding system shot by the shooting device installed on the artificial satellite can be downloaded and acquired by using the electronic device 100 such as a notebook computer, a desktop computer, a tablet computer, a mobile phone, and the like, and then the corresponding application program is run to identify and process the target image, so that the marked image is acquired.
That is, in step S10, the electronic device 100 may download the image including the cultivation system captured by the capturing device installed on the satellite according to the GPS coordinates of the location of the cultivation system, where the image captured by the capturing device may be a static photo or a dynamic video.
Further, after obtaining the image including the cultivation system, in order to obtain the target image, the downloaded image needs to be processed to extract the target image. At this time, since the culture system is a closed management system, when the culture system is built, a fence is built to enclose the area where the whole culture system is located into a closed area, and then the area outside the fence can be removed from the downloaded image, so that the target image of the culture system can be obtained.
In step S20, the target area may be a plurality of areas divided according to a set rule, that is, there may be a plurality of target areas. For example, the breeding system may be divided into a plurality of large target areas such as living areas, breeding areas, and eco-areas, and a plurality of small target areas may be subdivided into the respective target areas, for example, a plurality of small target areas such as bathing areas, sterilizing areas, and dining areas may be subdivided into the living areas. Wherein, the epidemic prevention grade of each large target area is different, and the epidemic prevention grade of each small target area contained under each large target area is the same.
It will be appreciated that the above examples of target areas are for illustrative purposes only and are not intended to be limiting in nature to demarcate specific target areas for inclusion in a farming system.
In step S30, the target area in the recognized target image can be obtained after the processing of step S20. Then, according to the set epidemic prevention level, the marking treatment can be carried out on the identified different target areas, and it can be understood that different target areas can obtain different marks, so that the corresponding epidemic prevention levels of different target areas can be conveniently and visually displayed.
Therefore, through the steps S10, S20 and S30, each region of the culture system can be clearly divided, and then the epidemic prevention level of each region can be visually shown through marking treatment on each region, so that workers can conveniently and effectively carry out epidemic prevention management and control on the culture system.
Referring to fig. 4, in some embodiments, identifying a target area in the target image (step S20) includes:
step S21: comparing the similarity of the pre-processing region and the predetermined region;
step S22: and under the condition that the similarity is greater than a preset value, determining the pretreatment area as a target area, wherein the target area comprises at least one of a living area, a breeding area and an environment-friendly area.
In certain embodiments, the identification module 22 is configured to compare the similarity of the pre-treated region to a predetermined region and to determine the pre-treated region as a target region if the similarity is greater than a predetermined value, the target region including at least one of a living region, a farming region, and an environmental region.
In some embodiments, the processor 11 is configured to compare the similarity of the pre-treated region with a predetermined region, and to determine the pre-treated region as a target region if the similarity is greater than a predetermined value, the target region including at least one of a living region, a farming region, and an environmental region.
Specifically, in steps S21 and S22, the preprocessing region is a region to be extracted from the target image for recognition and comparison, and the predetermined region may be set as a region that matches the contour of the target region. It is possible to determine whether the preprocessed region is the target region by comparing the similarity of the contours of the preprocessed region to be identified with the predetermined region.
For example, the breeding system may be simply divided into three target areas of a breeding area, a living area, and an eco-zone, and predetermined areas in conformity with their outlines are set according to the three target areas. When the target image is identified, a part of the area can be selected to be a preprocessing area, the outline of the preprocessing area is identified and compared with the outline shape of the preset area in similarity, the comparison sequence is not sequential, certainly, the comparison can be carried out simultaneously, and the preprocessing area can be determined to be the target area under the condition that the similarity is greater than the preset value. It can be easily understood that the predetermined value can be set according to the required precision, for example, can be set to 90% similarity or other values.
In addition, the similarity comparison may be performed by comparing the pre-processed region with other region characteristics such as the number of buildings in the predetermined region, and the specific comparison characteristics are not limited to the specific characteristics.
In this way, by setting the predetermined region and performing similarity comparison with the preprocessing region, it is made possible to easily and conveniently determine the predetermined region as the target region in the case where the similarity is larger than the predetermined value.
Referring to fig. 5, in some embodiments, identifying a target area in the target image (step S20) includes:
step S23: identifying a plurality of building images which are arranged in a matrix form in a target image;
step S24: areas of a plurality of buildings are confirmed as cultivation areas, and the target area comprises the cultivation areas.
In some embodiments, the identification module 22 is configured to identify a plurality of building images arranged in a matrix in the target image and identify an area of the plurality of buildings as the cultivation area, and the target area includes the cultivation area.
In some embodiments, the processor 11 is configured to identify a plurality of building images arranged in a matrix in the target image, and to identify an area of the plurality of buildings as the breeding area, the target area including the breeding area.
Specifically, in steps S23 and S24, it is demonstrated that the specific location of the target area in the target image is determined by some obvious architectural features contained in the target area. In the breeding system, in order to facilitate breeding management of a large number of pigs, pigsties are often regularly arranged, for example, the pigsties can be arranged in a matrix, so that images of a plurality of buildings arranged in the matrix in a target image can be identified, and after the images are identified, areas of the plurality of buildings are confirmed as breeding areas in a target area.
In addition, when the culture system is designed, the culture area is designed at the middle position of the culture system in consideration of convenience for workers in the culture area or an environment-friendly area for treating pollutants in the culture area, so that the time from the workers in different target areas to the culture area is saved. Then, the specific position of the culture area in the target image can be confirmed by setting the building area of the center position of the target image.
In this way, the specific location of the target area in the target image is determined by some obvious architectural features contained in the target area, so that the efficiency and accuracy of identifying the target area by the processor 11 can be improved.
Referring to fig. 6, in some embodiments, an image processing method includes:
step S25: identifying a closed graph area connecting a plurality of buildings and a living area;
step S26: and confirming the closed graph area as a corridor structure area, wherein the target area comprises the corridor structure area.
In some embodiments, the identification module 22 is configured to identify a closed graphical area connecting a plurality of buildings and connecting living areas, and to identify the closed graphical area as a vestibule structure area, the target area including the vestibule structure area.
In some embodiments, the processor 11 is configured to identify a closed graphical area connecting a plurality of buildings and connecting living areas, and to identify the closed graphical area as a vestibule area, the target area including the vestibule area.
Specifically, in the design of a breeding system, in order to effectively prevent non-plague, a closed corridor connecting a breeding area and a living area and connecting each pigsty in the breeding area is often required to be constructed, so that the propagation path of non-plague and other animal plagues is effectively cut off.
Then, in steps S25 and S26, since the specific location of the living area in the target image can be confirmed by comparing the similarity between steps S21 and S22, the enclosed graphic areas connecting the buildings and the cultivation area with the living area can be further identified after the images of the buildings are identified in steps S23 and S24.
At the moment, the closed graph area can be confirmed as the corridor structure area by combining the design of the culture system, so that the position confirmation of the target area, namely the corridor structure area, in the target image is completed.
So, through after discerning the breed district in the target image, many buildings in the further discernment connection breed district to and connect the closed figure district of breed district and living area, thereby confirm the closed figure district as vestibule structure district, with the further perfect discernment to the target image, reach the subregion that refines the farming systems, supplementary staff conveniently manages and controls the farming systems effectively.
Referring to fig. 7, in some embodiments, identifying a target area in the target image (step S20) includes:
step S27: extracting a green land area in the pre-treatment region;
step S28: and under the condition that the green area is larger than the preset area, determining the pretreatment area as an environment-friendly area, wherein the target area comprises the environment-friendly area.
In some embodiments, the identification module 22 is configured to extract the greenfield area in the pre-processing region and to determine that the pre-processing region is an eco-zone and the target region comprises an eco-zone if the greenfield area is greater than a preset area.
In some embodiments, the processor 11 is configured to extract the greenfield area in the pre-processing region, and to determine the pre-processing region as the eco-zone and the target region as the eco-zone if the greenfield area is greater than a preset area.
In particular, in the above statements on image processing methods, it is mentioned that the specific location of the target area in the target imagery may be determined jointly by some obvious architectural features contained in the target area; then, in addition to the step of confirming the eco-zone by comparing the similarity with the preset area, the specific location of the eco-zone in the target image can be confirmed by calculating and comparing the green area according to the steps S27 and S28.
Can understand easily, in the farming systems of ecological environmental protection nature, in order to handle the waste material in farming district, often set up the environmental protection district, the environmental protection district is in order to handle discarded object such as pig manure, placenta and dead pig, including areas such as useless dirty collecting pit, fermentation workshop, considers cyclic utilization's ecological theory, can also be equipped with fruit vegetables farming district, can decompose fermentation pig manure urine through the disinfection like this, the output fertilizer is used for fruit vegetables farming district. Thus, the green land area of the environmental protection area is obviously increased, which is different from the cultivation area and the living area.
Then, when identifying the target image, the processor 11 may determine the green area by analyzing the green area of the pre-processed area in the target image, and then compare the green area with the preset area, and in case that the green area is larger than the preset area, may determine the pre-processed area as the eco-friendly area. Similarly, the predetermined area can be calculated according to actual data.
In this way, the specific location of the eco-zone in the target image is determined by calculating the greenfield area of the pre-processing area and comparing the greenfield area with the preset area, so that the efficiency and accuracy of the processor 11 in identifying the eco-zone can be improved.
Referring to fig. 8, in some embodiments, the marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area according to the recognition result (step S30) includes:
step S31: the target areas are numbered, wherein the number is in direct proportion to the epidemic prevention level.
In some embodiments, the processing module 23 is configured to number the target area, wherein the number is proportional to the epidemic prevention level.
In some embodiments, the processor 11 is configured to number the target area, wherein the number is proportional to the size of the epidemic prevention level.
Specifically, after the processing of step S20, the specific position of the target area in the target image has been determined, and then in order to visually represent the epidemic prevention level of the target area in the breeding system, the target area may be marked according to a certain rule in step S30, for example, in step S31, the target area may be numbered to represent the epidemic prevention level, wherein the greater the number, the higher the epidemic prevention level.
It should be noted that epidemic prevention levels corresponding to different target areas are established according to the management rules of the aquaculture system, and the corresponding relationship between the target areas and the epidemic prevention levels can be input into the processor 11 as an input parameter, so that the processor 11 can number the target areas based on the epidemic prevention levels after identifying the target areas. In one embodiment, knowing that the epidemic prevention level of the breeding area contained in the target area is highest, the corridor structure area is next to the living area and finally to the environmental protection area, the environmental protection area can be marked as No. 1, the living area is No. 2, the corridor structure area is No. 3 and the breeding area is No. 4.
In addition, it can be understood that a plurality of pig houses and other areas are also included in the cultivation area, so that auxiliary numbers can be continued after the numbers for the convenience of staff management, and the auxiliary numbers do not have the significance of showing the epidemic prevention level. For example, in one embodiment, the first pigsty is numbered 4-1, the second pigsty is numbered 4-2, and so on.
Therefore, the epidemic prevention grades of the target areas can be visually shown by numbering different target areas according to preset different epidemic prevention grades, so that workers can conveniently and effectively carry out epidemic prevention management and control on the culture system.
Referring to fig. 9, in some embodiments, the marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area according to the recognition result (step S30) includes:
step S32: and filling colors into the target area, wherein the larger the color temperature of the filled color is, the lower the epidemic prevention level is.
In some embodiments, the processing module 23 is configured to perform color filling on the target area, wherein the larger the color temperature of the color is, the lower the epidemic prevention level is.
In some embodiments, the processor 11 is configured to color fill the target area, wherein the greater the color temperature of the fill, the lower the epidemic prevention rating.
Specifically, in addition to the epidemic prevention level of the target area being shown by number, the epidemic prevention level may be shown by color-filling the target area through step S32. In this case, the rule may be set such that the larger the color temperature of the color to be filled, the lower the epidemic prevention level.
It can be understood that compared with numbering the target area in the forms of numbers, letters and the like, the color filling in the target area has stronger visual impact force, so that the workers can feel the epidemic prevention level difference of different target areas more intuitively under the condition of large enough filling area.
In one embodiment, it is known that the epidemic prevention level of the breeding area contained in the target area is the highest, the corridor structure area is the second, then the living area, and finally the epidemic prevention level is the lowest, then based on the rule that the filling color temperature is larger, the epidemic prevention level is lower, the environmental protection area can be filled with blue, the living area is green, the corridor structure area is yellow, and the breeding area is red.
So, carry out the colour based on the epidemic prevention level and fill in the target area who discerns, can more audio-visually let the staff experience different target area's epidemic prevention level difference to let the staff can conveniently carry out the epidemic prevention management and control to farming systems effectively.
Referring to fig. 10, in an embodiment, fig. 10 shows an image including a cultivation system acquired by the processor 11 in the electronic device 100, wherein, through step S10, a target image of the cultivation system, i.e. an irregular figure in the image, can be acquired.
Then, via step S20, the processor 11 may identify the target region in the target image, wherein in step S20, the pre-processed region may be determined as the target region by comparing the similarity of the shape of the pre-processed region with the predetermined region through steps S21 and S22, for example, after comparing the similarity of the outlines of the regions, the right irregular part in the figure may be identified as the living region, the left side as the environmental region, and the center as the breeding region.
Furthermore, through steps S23 and S24, a plurality of building areas can be identified as the cultivation area by identifying some specific building features in the target image, such as a plurality of building images arranged in a matrix. At this time, the closed figure region connecting the plurality of buildings and the living region is further identified through the steps S25 and S26, so that the closed figure region can be identified as the corridor structure region.
Meanwhile, by using the green land area (the green land is indicated by the diagonal line in fig. 10) of the extracted pre-processed region through steps S27 and S28, in the case where it is confirmed that the green land area is larger than the preset area, the pre-processed region is confirmed as the eco-friendly region, for example, as is apparent from fig. 10, the green land area of the left region is significantly larger than the remaining regions, and then the left irregular region may be confirmed as the eco-friendly region.
Then, in step S30, according to the above recognition result, based on the preset epidemic prevention level, the target area is marked to show the epidemic prevention level of the target area, wherein the marking method may be to number the target area in step S31, wherein the number is proportional to the epidemic prevention level, for example, the environmental protection area is marked as number 1, the living area is number 2, the corridor structure area is number 3, the breeding area is number 4, and the first pigsty is numbered as 4-1, the second pigsty is numbered as 4-2, and so on.
Or the target area may be color-filled (not shown in fig. 10) in step S32, wherein the larger the color temperature of the filled color, the lower the epidemic prevention level.
Therefore, the areas of the culture system are clearly divided by the image processing method, and the epidemic prevention grade of each area can be visually shown by marking each area, so that the workers can conveniently and effectively carry out epidemic prevention management and control on the culture system.
The present embodiments provide a non-transitory computer-readable storage medium storing a computer program, which, when executed by one or more processors 11, causes the processors 11 to execute the image processing method of any one of the above embodiments.
For example, when the computer program is executed by the processor 11, the processor 11 may perform the steps of:
step S10: acquiring a target image of the breeding system shot by a shooting device;
step S20: identifying a target area in a target image;
wherein, the step S20 may include:
step S21: comparing the similarity of the pre-processing region and the predetermined region;
step S22: under the condition that the similarity is greater than a preset value, determining the pretreatment area as a target area, wherein the target area comprises at least one of a living area, a breeding area and an environment-friendly area;
step S23: identifying a plurality of building images which are arranged in a matrix form in a target image;
step S24: confirming areas of a plurality of buildings as cultivation areas, wherein the target area comprises the cultivation areas;
step S25: identifying a closed graph area connecting a plurality of buildings and a living area;
step S26: confirming the closed graph area as a corridor structure area, wherein the target area comprises the corridor structure area;
step S27: extracting a green land area in the pre-treatment region;
step S28: under the condition that the area of the green land is larger than the preset area, determining that the pretreatment area is an environment-friendly area, and determining that the target area comprises the environment-friendly area;
step S30: according to the identification result, marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area;
step S30 may include:
step S31: numbering the target areas, wherein the number is in direct proportion to the epidemic prevention level;
step S32: and filling colors into the target area, wherein the larger the color temperature of the filled color is, the lower the epidemic prevention level is.
Specifically, in the image processing method provided by the present application, via step S10, the processor 11 may acquire a target image of the cultivation system captured by the capturing device.
The processor 11 may identify a target region in the target picture via step S20, wherein in step S20, the pre-processed region may be determined as the target region, for example, to confirm the living region, the eco-zone and the farming zone, by comparing the similarity of the pre-processed region with the predetermined region through steps S21 and S22, in case the similarity is greater than the predetermined value; the closed graph area can be identified as the corridor structure area by identifying specific building features in the target image, such as a plurality of building images arranged in a matrix form through steps S23 and S24, so as to identify a plurality of building areas as the cultivation area, and further identifying the closed graph area connecting the plurality of buildings and the living area through steps S25 and S26; it is also possible to confirm that the pre-treated region is the eco-friendly region by using the green space area of the extracted pre-treated region through steps S27 and S28 in the case of confirming that the green space area is greater than the preset area.
Then, in step S30, according to the above recognition result, the target area is marked to show the epidemic prevention level of the target area based on the preset epidemic prevention level, wherein the marking method may be to number the target area in step S31, wherein the number is proportional to the epidemic prevention level, or may be to fill the target area with color in step S32, wherein the larger the color temperature of the filling, the lower the epidemic prevention level.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program instructing associated hardware. The computer program may be stored in a non-transitory computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), or the like.
In the description herein, references to the description of the terms "one embodiment," "certain embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that: numerous changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the application, the scope of which is defined by the claims and their equivalents.
Claims (10)
1. An image processing method, characterized in that the image processing method comprises:
acquiring a target image of the breeding system shot by a shooting device;
identifying a target area in the target image;
and according to the identification result, marking the target area based on the epidemic prevention level to show the epidemic prevention level of the target area.
2. The image processing method of claim 1, wherein the identifying the target region in the target image comprises:
comparing the similarity of the pre-processing region and the predetermined region;
and under the condition that the similarity is larger than a preset value, determining the pretreatment area as a target area, wherein the target area comprises at least one of a living area, a breeding area and an environmental protection area.
3. The image processing method of claim 1, wherein the identifying the target region in the target image comprises:
identifying a plurality of building images which are arranged in a matrix form in the target image;
and confirming areas of the plurality of buildings as cultivation areas, wherein the target area comprises the cultivation areas.
4. The image processing method according to claim 3, characterized in that the image processing method comprises:
identifying a closed graph area connecting the plurality of buildings and a living area;
and confirming the closed graph area as a corridor structure area, wherein the target area comprises the corridor structure area.
5. The image processing method of claim 1, wherein the identifying the target region in the target imagery comprises:
extracting a green land area in the pre-treatment region;
and under the condition that the green land area is larger than a preset area, determining that the pretreatment area is an environment-friendly area, wherein the target area comprises the environment-friendly area.
6. The image processing method according to claim 1, wherein the performing, according to the recognition result, a marking process on the target area based on an epidemic prevention level to show the epidemic prevention level of the target area comprises:
numbering the target areas, wherein the number is in direct proportion to the epidemic prevention level.
7. The image processing method according to claim 1, wherein the performing, according to the recognition result, a marking process on the target area based on an epidemic prevention level to show the epidemic prevention level of the target area comprises:
and carrying out color filling on the target area, wherein the larger the color temperature of the filled color is, the lower the epidemic prevention level is.
8. An image processing apparatus characterized by comprising:
the acquisition module is used for acquiring a target image of the breeding system shot by the shooting device;
the identification module is used for identifying a target area in the target image;
and the processing module is used for marking the target area based on the epidemic prevention level according to the identification result so as to show the epidemic prevention level of the target area.
9. An electronic device is characterized by comprising a processor, wherein the processor is used for acquiring a target image of a breeding system shot by a shooting device, identifying a target area in the target image, and marking the target area based on an epidemic prevention level according to an identification result to show the epidemic prevention level of the target area.
10. A non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by one or more processors, implements the image processing method of any one of claims 1-7.
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| CN114474091A (en) * | 2022-01-26 | 2022-05-13 | 北京声智科技有限公司 | Robot killing method, robot, device and storage medium |
| CN114474091B (en) * | 2022-01-26 | 2024-02-27 | 北京声智科技有限公司 | Robot killing method, killing robot, killing device and storage medium |
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