Method and device for performing high-precision determination of corn ear variety based on images

A corn ear and image realization technology, applied in the fields of seed and rhizome processing, application, agriculture, etc., can solve the problems of long test process cycle, automatic detection error, lack of test test accuracy, accuracy improvement, etc.

Active Publication Date: 2013-04-17
BEIJING RES CENT FOR INFORMATION TECH & AGRI
View PDF4 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] 1. The manual operation is cumbersome and the workload is large
[0005] 2. It is difficult to improve work efficiency, and the test process cycle is long
[0006] 3. Manual operation in the test process affects the accuracy of the test
[0007] 4. The measurement method of a single workflow is difficult to guarantee the accuracy of the obtained parameters
Due to the inherent limitations of the technology, there are certain errors in the automatic detection of indicators such as the number of rows of ears and grain

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and device for performing high-precision determination of corn ear variety based on images
  • Method and device for performing high-precision determination of corn ear variety based on images
  • Method and device for performing high-precision determination of corn ear variety based on images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048] Embodiment 1 provides a high-precision method for testing corn ears based on images, and the steps are as follows: figure 1 and figure 2 As shown, it specifically includes the following steps:

[0049] S1: Obtain the peripheral view with the cob of the corn ear as the central axis, apply the image processing algorithm to process the image of the peripheral view, and obtain the morphological index of the corn ear, the number of rows of kernels and the number of rows of kernels. The total number of grains per ear was calculated from the number of grains.

[0050] Among them, the morphological indicators include the length of the ear and the diameter of the ear.

[0051] Specifically, there are many ways to realize the peripheral view with the cob of the corn ear as the central axis, three ways are listed in this embodiment, but not limited to these three ways.

[0052] The first method: place the corn ear and the camera vertically or horizontally relative to each othe...

Embodiment 2

[0067] In order to achieve the above object, the second embodiment of the present invention also provides a high-precision corn ear seed testing device based on images, and the seed testing device includes:

[0068] Box 401 , camera 402 , light source 403 , weighing device 404 , and stepping motor 405 , wherein the camera 402 , light source 403 , weighing device 404 and stepping motor 405 are located inside the box body 401 .

[0069] The light source 403 provides light for the camera 402 to take pictures, and the camera 402 is used to obtain a peripheral view with the cob of the corn ear as the central axis.

[0070] The weighing device 404 is used for weighing the weight of corn ears, the weight of cobs or grains after threshing.

[0071] The stepper motor 405 provides power for the corn ear to rotate.

[0072] The placement method of camera 402 and corn ear specifically includes:

[0073] The ear of corn and the camera 402 are placed vertically or horizontally relative to...

Embodiment 3

[0078] In order to achieve the above object, the third embodiment of the present invention also provides a high-precision corn ear seed testing device based on images, and the seed testing device includes:

[0079] Cabinet 501, N cameras, light source 503, weighing device 504, the number of N in this embodiment is selected as 4, then the first camera 5021, the second camera 5022, the third camera 5023, the fourth camera 5024, the light source 503 And the weighing device 504 is located inside the box body 501 .

[0080] Wherein the light source 503 provides light for the camera to take pictures, and the first camera 5021, the second camera 5022, the third camera 5023, and the fourth camera 5024 are placed upright or horizontally at the same time, surrounding the ear of corn for a week, and the four cameras are distributed relative to the ear of corn in the center The included angles are 90 degrees.

[0081] The weighing device 504 is used to weigh the weight of the ear of corn...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method and a device for performing high-precision determination of corn ear variety based on images. A corn ear week view using cob as central axis is established and the week view is processed by image processing algorithms to obtain data of morphological index, ear grain row number and per row grain number, and the total grain number of ear grains is calculated based on the ear grain row numbers and the per row grain numbers; the corn ears are threshed to produce a cob and ear grains; the total weight of the ear grains or the weight of the cob is measured, and the total weight of the ear grains is calculated based on the weight of the corn ear and the weight of the cob; and the mean grain weight and the 100-grain weight are calculated based on the total weight of the ear grains and the total number of the ear grains. Before thresh of the corn ears, the weight of the corn ears is measured by a weighing sensor. With the digital image processing and sensor techniques, after obtaining the one-week ear grain distribution diagram of the corn ears, and the parameters of all the corn ear grains are calculated, including morphological index, ear grain row number, per row grain number, mean grain weight and so on. The precision of determining the variety of the corn ears is improved.

Description

technical field [0001] The invention relates to the technical field of corn ear seed testing, in particular to a high-precision corn ear seed test method and device based on images. Background technique [0002] Corn is an important food crop in my country's agricultural production. Corn breeding plays an important role in the fields of scientific research and production in my country's seed industry. One of the core issues in the corn seed industry is corn seed testing. Traditional seed testing methods mostly rely on Manual operation takes up a lot of human resources, and the work efficiency is low, which has become a technical bottleneck restricting the development of the corn seed industry. [0003] The main morphological parameters of maize seed testing include the number of grains per ear, the number of rows of grains per ear, the number of grains per row, and the weight of 100 kernels. The traditional method of seed testing mainly has the following technical defects: ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): A01C1/00
Inventor 郭新宇王传宇肖伯祥吴升杜建军
Owner BEIJING RES CENT FOR INFORMATION TECH & AGRI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products