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Fruit color grading method based on compressive sensing

A color grading and compression sensing technology, applied in color measurement devices, color/spectral characteristic measurement, sorting, etc., can solve the problems of limited promotion and application, complex processing process, long execution time, etc., to promote economic development, Fast and accurate grading

Inactive Publication Date: 2014-03-12
SHAANXI UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The processing process of the method is complicated, the amount of information is large, and the execution time is long, which limits its practical promotion and application in the field of agricultural production to a certain extent.

Method used

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  • Fruit color grading method based on compressive sensing

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0020] The present invention is an apple color grading method based on compressed sensing, which takes first-class fruit (apples whose red component coloring ratio is above 85%) as the tested object, and includes the following steps:

[0021] Step 1, obtain the main view and two left and right side views of the tested apple through the CCD camera;

[0022] Step 2, respectively extracting the R component images corresponding to the RGB images of the left and right side views, and adopting a color image space mean filter to smooth and filter the R component images of the left and right views respectively, so as to reduce the noise of the image;

[0023] Step 3: Take the 3*3 area in the upper left corner of the R component image after the filtering process as a reference template, and use the reference template to slide and scan the entire R component image pixel by pixel. For gray values ​​greater than The area with the average value of the template above 10 is considered to con...

Embodiment 2

[0030] Taking the second-class fruit (apples whose red component coloring ratio is between 70% and 85%) as the tested object, the following steps are included:

[0031] Step 1, obtain the main view and two left and right side views of the tested apple through the CCD camera;

[0032] Step 2, respectively extracting the R component images corresponding to the RGB images of the left and right side views, and adopting a color image space mean filter to smooth and filter the R component images of the left and right views respectively, so as to reduce the noise of the image;

[0033] Step 3: Take the 3*3 area in the upper left corner of the R component image after the filtering process as a reference template, and use the reference template to slide and scan the entire R component image pixel by pixel. For gray values ​​greater than The area with the average value of the template above 10 is considered to contain the apple area, and the original gray value is retained; on the contr...

Embodiment 3

[0040] Taking the third-class fruit (apples whose red component coloring ratio is below 70%) as the test object, the following steps are included:

[0041] Step 1, obtain the main view and two left and right side views of the tested apple through the CCD camera;

[0042] Step 2, respectively extracting the R component images corresponding to the RGB images of the left and right side views, and adopting a color image space mean filter to smooth and filter the R component images of the left and right views respectively, so as to reduce the noise of the image;

[0043]Step 3: Take the 3*3 area in the upper left corner of the R component image after the filtering process as a reference template, and use the reference template to slide and scan the entire R component image pixel by pixel. For gray values ​​greater than The area with the average value of the template above 10 is considered to contain the apple area, and the original gray value is retained; on the contrary, the area ...

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Abstract

The invention provides a fruit color grading method based on compressive sensing. The fruit color grading method comprises the following steps of: extracting R (Red) component images corresponding to left and right side view images, namely RGB (Red, Green, Blue) images, of a fruit to be detected; carrying out smoothing filtering and noise reduction on the R component images; respectively carrying out sliding scanning on the R component images subjected to the filtering treatment to realize rough division; respectively carrying out dilute decomposition on the R component images of the left and right side view images subjected to the rough division to determine a demarcation point between important characteristic information and secondary information; weighting the important characteristic information and carrying out adding operation on coefficient vectors corresponding to the two weighted images to form a new coefficient vector; multiplying a signal encoding measuring matrix by the new coefficient vector and carrying out encoding measurement; obtaining a quadratic sum of non-zero coefficients of measured values to obtain a result which is the value of a superficial characteristic fruit color; and performing a large amount of sample trainings to obtain a threshold value for measuring the grade of the fruit color and outputting a fruit color grading result. The fruit color grading method based on the compressive sensing can be used for grading the fruit colors and has the characteristics of automation, no loss, small data amount, high grading speed and high accuracy.

Description

technical field [0001] The invention relates to a method for realizing automatic non-destructive detection of agricultural product quality by using digital image processing technology, in particular to a fruit color grading method based on compressed sensing. Background technique [0002] China is a large fruit producing country, and fast and accurate detection and grading of fruits is an important measure to improve the economic benefits of fruits and enhance the international competitiveness of the industry. [0003] The traditional manual grading method relies on the experience and visual inspection of skilled workers to judge the quality of fruits, which is difficult to guarantee the accuracy and effectiveness of the results and cannot meet the requirements of the market. The existing computer vision-based fruit grading method uses a conventional digital image processing algorithm to calculate the characteristic parameters such as the coloring area through preprocessing,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01J3/46G01N21/25G06T7/40B07C5/342
Inventor 党宏社田丽娜张芳杨小青姚勇张新院郭楚佳
Owner SHAANXI UNIV OF SCI & TECH