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Blade structure detection method and system based on machine vision, medium and equipment

A technology of machine vision and blade structure, applied in the direction of instrumentation, image data processing, calculation, etc., can solve the problems of inability to obtain blade structure data, low accuracy rate, and low efficiency of blade structure detection

Active Publication Date: 2019-05-31
SHANGHAI TOBACCO GRP CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] In view of the shortcomings of the prior art described above, the object of the present invention is to provide a machine vision-based blade structure detection method, system, medium and equipment for Solve the problem that the detection efficiency of the leaf structure in the threshing and redrying link of the existing technology is low, the accuracy is not high, and a large amount of effective leaf structure data cannot be obtained

Method used

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  • Blade structure detection method and system based on machine vision, medium and equipment
  • Blade structure detection method and system based on machine vision, medium and equipment
  • Blade structure detection method and system based on machine vision, medium and equipment

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Embodiment 1

[0047] This embodiment provides a blade structure detection method based on machine vision, including:

[0048] Obtain the original tobacco leaf image of the tobacco leaf sample;

[0049] performing binarization processing on the original tobacco leaf image to form a binarized tobacco leaf image;

[0050] By calculating the area information of the connected area in the binarized tobacco leaf image, the tobacco leaf pixel area vector corresponding to the machine vision measurement of the tobacco leaf sample is obtained;

[0051] Based on the tobacco leaf pixel area vector measured by the machine vision corresponding to the tobacco leaf sample and the large piece rate data, medium piece rate data and small piece rate data corresponding to the tobacco leaf samples obtained by the vibrating sieve screen respectively detected and weighed in advance, the definition and the described large piece rate data A corresponding first threshold set, a second threshold set corresponding to t...

Embodiment 2

[0119] This embodiment provides a blade structure detection system based on machine vision, including:

[0120] The first acquisition module is used to acquire the original tobacco leaf image of the tobacco leaf sample;

[0121] A binarization processing module, configured to perform binarization processing on the original tobacco leaf image to form a binarized tobacco leaf image;

[0122] The second acquisition module is used to obtain the tobacco leaf pixel area vector measured by machine vision corresponding to the tobacco leaf sample by calculating the area information of the connected area in the binarized tobacco leaf image;

[0123] The threshold set definition module is used to measure the tobacco leaf pixel area vector based on the machine vision corresponding to the tobacco leaf sample and the large slice rate data, medium slice rate data and small slice rate data corresponding to the tobacco leaf samples obtained by the vibrating sieve screen respectively detected a...

Embodiment 3

[0151] This embodiment provides a device, the device includes: a processor, a memory, a transceiver, a communication interface or / and a system bus; the memory and the communication interface are connected to the processor and the transceiver through the system bus and complete mutual communication, The memory is used to store computer programs, the communication interface is used to communicate with other devices, and the processor and transceiver are used to run the computer programs, so that the devices can execute the steps of the blade structure detection method based on machine vision.

[0152] The system bus mentioned above may be a Peripheral Component Interconnect (PCI for short) bus or an Extended Industry Standard Architecture (EISA for short) bus or the like. The system bus can be divided into address bus, data bus, control bus and so on. The communication interface is used to realize the communication between the database access device and other devices (such as cl...

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Abstract

The invention provides a leaf structure detection method and system based on machine vision, a medium and equipment. The detection method comprises: acquiring an original tobacco leaf image of a tobacco leaf sample; Binarizing the original tobacco leaf image to form a binarized tobacco leaf image; Obtaining a tobacco leaf pixel area vector measured by machine vision corresponding to the tobacco leaves by calculating area information of a communication area in the binarized tobacco leaf image; Defining a first threshold set corresponding to the large piece rate data, a second threshold set corresponding to the medium piece rate data and a third threshold set corresponding to the small piece rate data; Calculating a large sheet rate predicted value, a medium sheet rate predicted value and asmall sheet rate predicted value, and calculating a large sheet rate error, a medium sheet rate error and a small sheet rate error; And judging the type of the tobacco leaf sample according to the characteristic area of the tobacco leaf image, the characteristic area threshold value of the large sheet, the characteristic area threshold value of the middle sheet and the characteristic area threshold value of the small sheet. The leaf structure of the threshing and redrying link can be rapidly and accurately detected, and a large amount of effective leaf structure data can be obtained.

Description

technical field [0001] The invention belongs to the technical field of tobacco leaf image processing, and relates to a detection method and system, in particular to a machine vision-based leaf structure detection method, system, medium and equipment. Background technique [0002] The leaf structure mainly refers to the weight ratio of the tobacco leaves on each layer of the sieve after the semi-finished product produced in the threshing and redrying process passes through the four-layer vibrating screen of 2.36mm, 6.35mm, 12.7mm, and 25.4mm. rate and fragmentation rate. The threshing and redrying process includes three main links: pretreatment, leaf threshing and redrying, which jointly determine the product quality. The research on pretreatment and threshing air classification focuses on the large and medium slice rate, debris rate and stalk content rate, indicating that pretreatment and threshing air classification are very important for the physical quality of threshing ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/62G06T7/136G06T7/00G06T5/00G06T7/194
Inventor 徐玮杰杨凯张军薛庆逾
Owner SHANGHAI TOBACCO GRP CO LTD
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