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Kernel Segmentation Method of Corn Ear Image

A corn ear and image technology, which is applied in the field of computer image processing, can solve the problems of not considering the characteristics of pixels, the segmentation and recognition accuracy and poor precision of corn kernels, and achieve the effect of improving accuracy and precision

Active Publication Date: 2016-03-30
BEIJING RES CENT FOR INFORMATION TECH & AGRI
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

The existing image processing methods generally use the pixels in the image as the basic features, without considering the characteristics of the target itself represented by the pixels, which makes the existing image segmentation methods poor in the accuracy and precision of the segmentation and recognition of corn kernels

Method used

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  • Kernel Segmentation Method of Corn Ear Image
  • Kernel Segmentation Method of Corn Ear Image

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Embodiment Construction

[0049] The specific implementation manner of the invention will be further described below in conjunction with the accompanying drawings and embodiments. The following examples are only used to illustrate the present invention, but not to limit the scope of the present invention.

[0050] In the prior art, the image processing method is used to test the varieties of corn ears, which is generally carried out for a single image of corn ears, using limited information to derive as many characteristic parameters of corn ears as possible, which has the advantages of simplicity, convenience and speed. The invention mainly aims at improving the grain segmentation method of a single corn ear image, so as to improve the accuracy and precision of the detection of the character characteristic parameters of the corn ear.

[0051] Flowchart such as figure 1 A corn ear image grain segmentation method shown in , mainly includes steps:

[0052] S1. Under certain lighting conditions, the cen...

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Abstract

The invention relates to the technical field of computer image processing, in particular to a corn ear image grain segmentation method. The method includes the steps: S1, combining the morphology algorithm to preprocess a corn ear image; S2, utilizing a radial distortion correction method for processing the image obtained in the step S1; and S3, according to a hierarchical threshold segmentation algorithm, segmenting the image obtained in the step S2, and generating a final segmentation result of the corn ear image. Firstly, the radial distortion correction algorithm is used for eliminating radial distortion of the corn ear image to enable grain shape information on the corn ear image to be restored to the utmost extent, and secondly, the hierarchical threshold segmentation method is used for segmenting the processing corn ear image so that the problem that grains in different color and of different types are different to segment is solved. Therefore, accuracy and precision of corn ear image grain segmentation are improved greatly, and a strong technical support is provided for statistics and analysis of corn variety characteristics and morphological characteristics.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to a method for segmenting corn ear images and grains. Background technique [0002] The traditional test of corn ear varieties requires manual measurement and calculation of various index parameters of corn ears, and then statistics and analysis of the characteristics and morphological characteristics of corn varieties. The traditional test process is repetitive, time-consuming, and laborious. The measurement of index parameters is heavily dependent on the subjective judgment of the staff. There are large errors in the obtained data, and the standardization of the test process is low. With the in-depth penetration and application of computer and information technology in the agricultural field, it has become a trend to use computer image processing technology for automatic seed testing. The image-based automatic seed test method can greatly reduce labor costs, im...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 杜建军郭新宇王传宇肖伯祥吴升
Owner BEIJING RES CENT FOR INFORMATION TECH & AGRI
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