CN112801931B - Intelligent large-yield data identification system and method based on visual analysis - Google Patents
Intelligent large-yield data identification system and method based on visual analysis Download PDFInfo
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Abstract
The invention relates to an intelligent output big data identification system based on visual analysis, which comprises: the image capturing device is arranged in front of the live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed; the signal conversion equipment is used for converting the real-time live pig area into corresponding meat production volume, bone volume and blood production dosage; and the liquid crystal display device is connected with the signal conversion device and is used for receiving and displaying the corresponding meat production volume, the bone volume and the blood production dosage. The invention also relates to an intelligent large-yield data identification method based on visual analysis. The intelligent output big data identification system and method based on visual analysis are intelligent in principle and orderly in control. Because the corresponding meat production volume, bone volume and blood production dose can be effectively judged before the live pigs are processed, the cultivation strategy can be conveniently determined by farmers.
Description
Technical Field
The invention relates to the field of visual analysis, in particular to an intelligent large-yield data identification system and method based on visual analysis.
Background
Horizontal field analysis studies the lateral width of the facility and the depth distance of the space. And scientifically determining that the central visual angle within 10 degrees of the horizontal visual area is the optimal visual area. Human eyes are instantaneous visual zones within the range of 20 degrees of the central visual angle, and can identify objects in a very short time. Human eyes have an effective visual area within 30 degrees of a central visual angle, and can distinguish the image of an object by focusing attention. Human eyes have a maximum visual area within 120 degrees of a central visual angle, and a great deal of effort is required to identify an object. If the head is rotated, the maximum viewing range of the person can be up to 220 °.
The objects of the vertical field of view analysis study are the height of the object and the depth of penetration of the overall planar configuration. According to scientific determination, the optimal visual area of the human eyes in the visual area in the vertical direction is 10 degrees below the visual plane, the good visual area is from 10 degrees above the visual plane to 30 degrees below the visual plane, and the maximum visual area is from 60 degrees above the visual plane to 70 degrees below the visual plane.
Disclosure of Invention
In order to solve the related problems in the prior art, the invention provides an intelligent large-yield data identification system and method based on visual analysis, which can obtain the real-time live pig area of the current live pig to be processed on site, and convert the real-time live pig area into the corresponding meat production volume, bone volume and blood production dosage, thereby providing effective reference data for evaluating yield for farm workers; and on the basis of customized image processing, identifying a pig body area and the real-time depth of field of a pig body target in the pig body area from the processed image based on the appearance characteristics of the pig body, and further calculating the real-time live pig area of the current live pig to be processed.
According to an aspect of the present invention, there is provided an intelligent production big data recognition system based on visual analysis, the system comprising:
the image capturing device is arranged in front of the live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
the signal conversion equipment is used for receiving the real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, a bone volume and a blood production dose, wherein the corresponding meat production volume, the bone volume and the blood production dose are positively correlated with the real-time live pig area;
the liquid crystal display device is connected with the signal conversion device and is used for receiving and displaying the corresponding meat production volume, the bone volume and the blood production dosage;
the content segmentation device is connected with the image capture device and is used for receiving the to-be-processed environment image and segmenting the to-be-processed environment image into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
the duplication degree detection device is connected with the content segmentation device and used for detecting the duplication degree of the pixel value of each pixel point of each column of subimages;
the contrast lifting equipment is respectively connected with the content segmentation equipment and the repeatability detection equipment and is used for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of all the pixel points of each column of subimages;
the signal merging equipment is connected with the contrast improvement equipment and used for receiving the subimages of each row subjected to the contrast improvement operation and splicing the image data to obtain a signal merging image corresponding to the to-be-processed environment image;
the pig body identification device is used for receiving the processed image and identifying a pig body area and the real-time depth of field of a pig body target in the pig body area from the processed image based on the appearance characteristics of the pig body;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and is used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
and the SD storage device is connected with the pig body identification device and is used for pre-storing the appearance characteristics of the pig body.
According to another aspect of the present invention, there is also provided an intelligent production big data identification method based on visual analysis, the method comprising:
the method comprises the steps that an image capturing device is used and arranged in front of a live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
using a signal conversion device for receiving a real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, bone volume and blood production dose, wherein the corresponding meat production volume, bone volume and blood production dose are positively correlated with the real-time live pig area;
using a liquid crystal display device connected with the signal conversion device and used for receiving and displaying the corresponding meat production volume, bone volume and blood production dosage;
the content segmentation equipment is connected with the image capture equipment and used for receiving the environment image to be processed and segmenting the environment image to be processed into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
using a repeatability detection device, connected with the content segmentation device, for detecting the repeatability of the pixel value of each pixel point of each column of subimages;
using contrast lifting equipment, respectively connected to the content segmentation equipment and the repeatability detection equipment, for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of each pixel point of each column of subimages;
using signal merging equipment, connecting with the contrast improvement equipment, and receiving the subimages of each row subjected to the contrast improvement operation and performing image data splicing to obtain a signal merging image corresponding to the to-be-processed environment image;
using a pig body identification device for receiving the processed image and identifying a pig body region and a real-time depth of field of a pig body target in the pig body region from the processed image based on the pig body appearance characteristics;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
and using an SD storage device connected with the pig body identification device and used for pre-storing the appearance characteristics of the pig body.
The intelligent output big data identification system and method based on visual analysis are intelligent in principle and orderly in control. Because the corresponding meat production volume, bone volume and blood production dose can be effectively judged before the live pigs are processed, the cultivation strategy can be conveniently determined by farmers.
Therefore, the invention needs to have the following three important points:
(1) performing corresponding contrast improvement operation on each column of subimages based on the repeatability of the pixel value of each pixel point of each column of subimages in the image, thereby realizing directional processing on image signals and improving the precision and effect of image processing;
(2) the method comprises the steps of obtaining the real-time live pig area of a current live pig to be processed on site, and converting the real-time live pig area into a corresponding meat production volume, a bone volume and a blood production dose, so that effective reference data for evaluating yield are provided for farm workers;
(3) on the basis of customized image processing, identifying a pig body area and the real-time depth of field of a pig body target in the pig body area from the processed image based on the appearance characteristics of the pig body, and further calculating the real-time live pig area of the current live pig to be processed.
Detailed Description
Embodiments of the vision analysis-based intelligent production big data identification system and method of the present invention will be described in detail below.
The animal husbandry mainly used for house feeding in the farming area is called farming area breeding. The farming industry in agricultural areas is characterized in that: (1) mainly used in the grain consumption type breeding industry. The domestic animals mainly comprise pigs, poultry, work animals, goats and the like which consume more food, the feed sources comprise agricultural products, feed grains, straws, weeds, wild vegetables and the like, and the domestic animals are grazed on hillsides and sporadic grasslands. (2) The dual-purpose breeding industry is developed, such as cattle industry, horse industry, donkey industry and the like which are used for both milk and meat. (3) Mainly comprises barn feeding. The artificial raising is carried out in the animal house for the rest of the time except for the short-term stubble field grazing after the crops are harvested. (4) The feed cost accounts for a higher proportion, and generally accounts for more than 65% of the livestock cost. Can fully realize the combination of agriculture and pasturing, and has more careful management and higher production level.
In grassland and desert areas, the breeding industry mainly using grazing is called the pasture area breeding industry. Livestock are primarily herbivores. Extensive management, non-close combination of farming and pasturing, large seasonal fluctuation of forage grass supply, easy threat of disastrous weather, and low and unbalanced livestock productivity.
Currently, since the living pigs are bred in a complicated environment and in a long breeding period, farmers are particularly cautious in customizing breeding strategies, for example, in selecting the number of the live pigs to be bred. The direct data determining the breeding economic benefit of farmers are the yields of various pig parts, however, the direct data cannot be accurately acquired in the live pig state.
In order to overcome the defects, the invention builds the intelligent high-yield data identification system and method based on visual analysis, and can effectively solve the corresponding technical problems.
An intelligent production big data identification system based on visual analysis according to an embodiment of the invention comprises:
the image capturing device is arranged in front of the live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
the signal conversion equipment is used for receiving the real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, a bone volume and a blood production dose, wherein the corresponding meat production volume, the bone volume and the blood production dose are positively correlated with the real-time live pig area;
the liquid crystal display device is connected with the signal conversion device and is used for receiving and displaying the corresponding meat production volume, the bone volume and the blood production dosage;
the content segmentation device is connected with the image capture device and is used for receiving the to-be-processed environment image and segmenting the to-be-processed environment image into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
the duplication degree detection device is connected with the content segmentation device and used for detecting the duplication degree of the pixel value of each pixel point of each column of subimages;
the contrast lifting equipment is respectively connected with the content segmentation equipment and the repeatability detection equipment and is used for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of all the pixel points of each column of subimages;
the signal merging equipment is connected with the contrast improvement equipment and used for receiving the subimages of each row subjected to the contrast improvement operation and splicing the image data to obtain a signal merging image corresponding to the to-be-processed environment image;
the pig body identification device is used for receiving the processed image and identifying a pig body area and the real-time depth of field of a pig body target in the pig body area from the processed image based on the appearance characteristics of the pig body;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and is used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
the SD storage device is connected with the pig body identification device and is used for pre-storing the appearance characteristics of the pig body;
in the contrast lifting device, performing corresponding contrast lifting operation on each column of sub-images based on the repetition degree of the pixel value of each pixel point of the column of sub-images includes: the lower the repetition degree of the pixel values of the pixels of each column of sub-images is, the lower the intensity of the corresponding contrast lifting operation performed on the column of sub-images is.
Next, the detailed structure of the intelligent production big data recognition system based on visual analysis of the present invention will be further described.
In the intelligent output big data recognition system based on visual analysis:
the pig body identification equipment is internally provided with a storage unit which is used for storing input data and output data of the pig body identification equipment;
the area analysis equipment is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
The intelligent yield big data identification system based on the visual analysis can further comprise:
the pig body identification equipment is also connected with a clock generator and is used for receiving a time sequence signal customized by the clock generator for the pig body identification equipment.
In the intelligent output big data recognition system based on visual analysis:
the area analysis device is implemented using an ASIC chip that includes an online programming interface.
In the intelligent output big data recognition system based on visual analysis:
the pig body identification device and the area analysis device are located on the same printed circuit board and share the same circuit supply device.
The intelligent yield big data identification method based on the visual analysis comprises the following steps:
the method comprises the steps that an image capturing device is used and arranged in front of a live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
using a signal conversion device for receiving a real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, bone volume and blood production dose, wherein the corresponding meat production volume, bone volume and blood production dose are positively correlated with the real-time live pig area;
using a liquid crystal display device connected with the signal conversion device and used for receiving and displaying the corresponding meat production volume, bone volume and blood production dosage;
the content segmentation equipment is connected with the image capture equipment and used for receiving the environment image to be processed and segmenting the environment image to be processed into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
using a repeatability detection device, connected with the content segmentation device, for detecting the repeatability of the pixel value of each pixel point of each column of subimages;
using contrast lifting equipment, respectively connected to the content segmentation equipment and the repeatability detection equipment, for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of each pixel point of each column of subimages;
using signal merging equipment, connecting with the contrast improvement equipment, and receiving the subimages of each row subjected to the contrast improvement operation and performing image data splicing to obtain a signal merging image corresponding to the to-be-processed environment image;
using a pig body identification device for receiving the processed image and identifying a pig body region and a real-time depth of field of a pig body target in the pig body region from the processed image based on the pig body appearance characteristics;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
using an SD storage device connected with the pig body identification device and used for pre-storing the appearance characteristics of the pig body;
in the contrast lifting device, performing corresponding contrast lifting operation on each column of sub-images based on the repetition degree of the pixel value of each pixel point of the column of sub-images includes: the lower the repetition degree of the pixel values of the pixels of each column of sub-images is, the lower the intensity of the corresponding contrast lifting operation performed on the column of sub-images is.
Next, the detailed steps of the intelligent production capacity big data identification method based on visual analysis according to the present invention will be further described.
In the intelligent yield big data identification method based on visual analysis:
the pig body identification equipment is internally provided with a storage unit which is used for storing input data and output data of the pig body identification equipment;
the area analysis equipment is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
In the intelligent yield big data identification method based on visual analysis:
the pig body identification equipment is also connected with a clock generator and is used for receiving a time sequence signal customized by the clock generator for the pig body identification equipment.
In the intelligent yield big data identification method based on visual analysis:
the area analysis device is implemented using an ASIC chip that includes an online programming interface.
In the intelligent yield big data identification method based on visual analysis:
the pig body identification device and the area analysis device are located on the same printed circuit board and share the same circuit supply device.
An ASIC, i.e., an application specific integrated circuit, refers to an integrated circuit designed and manufactured according to the requirements of a particular user and the needs of a particular electronic system. At present, one of the most popular ways to design an ASIC is to use a CPLD (complex programmable logic device) and an FPGA (field programmable logic array), which have common characteristics of field programmability of users and support the boundary scan technology, but have respective characteristics in terms of integration level, speed and programming mode.
Currently, in the integrated circuit world, an ASIC is considered to be a purpose-built integrated circuit. Refers to integrated circuits designed and manufactured to meet the needs of a particular user and the needs of a particular electronic system. The ASIC is characterized by facing the requirements of specific users, and compared with a general integrated circuit, the ASIC has the advantages of smaller volume, lower power consumption, improved reliability, improved performance, enhanced confidentiality, reduced cost and the like during batch production.
An integrated circuit is a microelectronic device or component. The elements such as transistor, resistor, capacitor and inductor and wiring required in a circuit are interconnected together by adopting a certain process, manufactured on one or a plurality of small semiconductor wafers or medium substrates, and then packaged in a tube shell to form a micro structure with the required circuit function; all the elements are structurally integrated, so that the electronic elements are greatly miniaturized, low in power consumption, intelligent and high in reliability.
The larger the scale of the integrated circuit, the more difficult it is to build a system to change to address these issues for specific requirements. Therefore, an Application Specific Integrated Circuit (ASIC) featuring user-added design has emerged, which can achieve an optimized design of the entire system, with superior performance and high security. The application specific integrated circuit can integrate the functions of a plurality of, dozens of or even hundreds of universal medium and small integrated circuits which respectively bear some functions on one chip, and further integrate the whole system on one chip to realize the needs of the system. The circuit of the whole machine is optimized, the number of elements is reduced, wiring is shortened, the volume and the weight are reduced, and the reliability of the system is improved.
Finally, it should be noted that each functional device in the embodiments of the present invention may be integrated into one processing device, or each device may exist alone physically, or two or more devices may be integrated into one device.
The functions, if implemented in the form of software-enabled devices and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An intelligent production big data identification system based on visual analysis, the system comprising:
the image capturing device is arranged in front of the live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
the signal conversion equipment is used for receiving the real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, a bone volume and a blood production dose, wherein the corresponding meat production volume, the bone volume and the blood production dose are positively correlated with the real-time live pig area;
the liquid crystal display device is connected with the signal conversion device and is used for receiving and displaying the corresponding meat production volume, the bone volume and the blood production dosage;
the content segmentation device is connected with the image capture device and is used for receiving the to-be-processed environment image and segmenting the to-be-processed environment image into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
the duplication degree detection device is connected with the content segmentation device and used for detecting the duplication degree of the pixel value of each pixel point of each column of subimages;
the contrast lifting equipment is respectively connected with the content segmentation equipment and the repeatability detection equipment and is used for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of all the pixel points of each column of subimages;
the signal merging equipment is connected with the contrast improvement equipment and used for receiving the subimages of each row subjected to the contrast improvement operation and splicing the image data to obtain a signal merging image corresponding to the to-be-processed environment image;
the pig body identification device is used for receiving the signal combination image and identifying a pig body area and the real-time depth of field of a pig body target in the pig body area from the signal combination image based on the appearance characteristics of the pig body;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and is used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
the SD storage device is connected with the pig body identification device and is used for pre-storing the appearance characteristics of the pig body;
in the contrast lifting device, performing corresponding contrast lifting operation on each column of sub-images based on the repetition degree of the pixel value of each pixel point of the column of sub-images includes: the lower the repetition degree of the pixel values of the pixels of each column of sub-images is, the lower the intensity of the corresponding contrast lifting operation performed on the column of sub-images is.
2. The intelligent production big data recognition system based on visual analysis of claim 1, wherein:
the pig body identification equipment is internally provided with a storage unit which is used for storing input data and output data of the pig body identification equipment;
the area analysis equipment is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
3. The intelligent production big data recognition system based on visual analysis of claim 2, wherein:
the pig body identification equipment is also connected with a clock generator and is used for receiving a time sequence signal customized by the clock generator for the pig body identification equipment.
4. The intelligent production big data recognition system based on visual analysis of claim 3, wherein:
the area analysis device is implemented using an ASIC chip that includes an online programming interface.
5. The intelligent production big data recognition system based on visual analysis of claim 4, wherein:
the pig body identification device and the area analysis device are located on the same printed circuit board and share the same circuit supply device.
6. An intelligent production capacity big data identification method based on visual analysis is characterized by comprising the following steps:
the method comprises the steps that an image capturing device is used and arranged in front of a live pig to be processed and used for executing image capturing action on the environment where the live pig is located so as to obtain and output a corresponding environment image to be processed;
using a signal conversion device for receiving a real-time live pig area and converting the real-time live pig area into a corresponding meat production volume, bone volume and blood production dose, wherein the corresponding meat production volume, bone volume and blood production dose are positively correlated with the real-time live pig area;
using a liquid crystal display device connected with the signal conversion device and used for receiving and displaying the corresponding meat production volume, bone volume and blood production dosage;
the content segmentation equipment is connected with the image capture equipment and used for receiving the environment image to be processed and segmenting the environment image to be processed into sub-images in each row, and each sub-image only comprises each pixel point corresponding to the row;
using a repeatability detection device, connected with the content segmentation device, for detecting the repeatability of the pixel value of each pixel point of each column of subimages;
using contrast lifting equipment, respectively connected to the content segmentation equipment and the repeatability detection equipment, for executing corresponding contrast lifting operation on each column of subimages based on the repeatability of the pixel values of each pixel point of each column of subimages;
using signal merging equipment, connecting with the contrast improvement equipment, and receiving the subimages of each row subjected to the contrast improvement operation and performing image data splicing to obtain a signal merging image corresponding to the to-be-processed environment image;
using a pig body identification device for receiving the signal combination image and identifying a pig body region and a real-time depth of field of a pig body target in the pig body region from the signal combination image based on the pig body appearance characteristics;
the area analysis device is respectively connected with the signal conversion device and the pig body identification device and used for calculating the cross section area of the pig body target in the pig body area based on the obtained pig body area and the real-time depth of field of the pig body target to serve as the real-time live pig area to be output;
using an SD storage device connected with the pig body identification device and used for pre-storing the appearance characteristics of the pig body;
in the contrast lifting device, performing corresponding contrast lifting operation on each column of sub-images based on the repetition degree of the pixel value of each pixel point of the column of sub-images includes: the lower the repetition degree of the pixel values of the pixels of each column of sub-images is, the lower the intensity of the corresponding contrast lifting operation performed on the column of sub-images is.
7. The intelligent visual-analysis-based yield big data recognition method of claim 6, wherein:
the pig body identification equipment is internally provided with a storage unit which is used for storing input data and output data of the pig body identification equipment;
the area analysis equipment is connected with the IIC control bus and used for receiving various control instructions sent by the IIC control bus.
8. The intelligent visual-analysis-based yield big data recognition method of claim 7, wherein:
the pig body identification equipment is also connected with a clock generator and is used for receiving a time sequence signal customized by the clock generator for the pig body identification equipment.
9. The intelligent visual-analysis-based yield big data recognition method of claim 8, wherein:
the area analysis device is implemented using an ASIC chip that includes an online programming interface.
10. The intelligent visual-analysis-based yield big data recognition method of claim 9, wherein:
the pig body identification device and the area analysis device are located on the same printed circuit board and share the same circuit supply device.
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