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Garlic classifying method based on machine vision and unitary linear recursive analysis

A linear regression analysis and machine vision technology, applied in instruments, measuring devices, optical devices, etc., can solve problems such as mesh extrusion or scratching, and achieve the effect of fast speed, saving classification time and simple method.

Inactive Publication Date: 2013-12-25
QILU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] (2) Machine vision detection is a non-contact detection process
The traditional mechanical grading method is easy to squeeze or scratch the edge of the mesh

Method used

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  • Garlic classifying method based on machine vision and unitary linear recursive analysis
  • Garlic classifying method based on machine vision and unitary linear recursive analysis
  • Garlic classifying method based on machine vision and unitary linear recursive analysis

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Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] Concrete method of the present invention is as follows:

[0050] (1) Select a few heads of each of the three grades of garlic, and use the same sensor CCD to take pictures of the garlic, requiring the shooting height to be consistent with the camera pixels. And measure the size of the transverse diameter of the garlic, recorded as , obtain its garlic cross-sectional area by image, denote as: , substitute the data into the formula

[0051] (1)

[0052] (2)

[0053] Will and substitute , that is, the linear equation fitted by the least squares method.

[0054] (2) The predicted image is taken with the same sensor, and the shooting height is required to be consistent with the camera pixels. The resulting image area Substitute into the linear equation Get the size of the transverse diameter of the garlic, recorded as .

[0055] (3) Compare the obtained transverse diameter of garlic with the three grading standa...

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Abstract

The invention relates to the field of garlic classifying techniques, in particular to a garlic classifying method based on machine vision and unitary linear recursive analysis. The garlic classifying method based on machine vision and unitary linear recursive analysis is characterized by including the steps of carrying out image acquisition on garlic, then carrying out acute binarization processing on acquired images, labeling communicated zones in binary images, indicating the area of the communicated zones in the images according to image pixels, carrying out mathematical modeling through unitary linear recursive analysis according to the area of the acquired garlic images and garlic transverse diameter data, and classifying the pre-classified garlic according to a fitted linear equation. According to the method, the image extraction method is adopted, a CCD is high in accuracy when used for measuring length, the garlic is not damaged because the images are acquired through scanning, and meanwhile the method is simple, high in speed and capable of saving classifying time because modeling is carried out through the unitary linear recursive analysis.

Description

(1) Technical field [0001] The invention relates to the technical field of garlic classification, in particular to a garlic classification method based on machine vision and linear regression analysis. (2) Background technology [0002] At present, the export volume of garlic in our country is increasing, but the increase in foreign exchange income is not as good as the increase in export volume. The main reason for this phenomenon is that the post-harvest processing methods of garlic are backward, resulting in mixed grades and uneven quality of garlic. The quality is mixed, resulting in low value, unable to meet the international export standards, and thus unable to enter the international market. With the increase of import and export trade volume, this loss is still increasing year by year. Traditional mechanical grading methods are prone to crushing or scratching at the edge of the mesh. [0003] Intelligent recognition based on machine vision instead of human visu...

Claims

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Application Information

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IPC IPC(8): G01B11/08G01B11/28
Inventor 张楠
Owner QILU UNIV OF TECH
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