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Agaricus bisporus grading judgment method

A technology of Agaricus bisporus and mushroom, applied in image analysis, image data processing, instrument and other directions, can solve the problems of low efficiency and large error of Agaricus bisporus

Active Publication Date: 2020-02-07
SHENYANG AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention provides a method for judging the classification of Agaricus bisporus, which can solve the problems of large errors and low efficiency in the classification of Agaricus bisporus in the prior art

Method used

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  • Agaricus bisporus grading judgment method
  • Agaricus bisporus grading judgment method

Examples

Experimental program
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Effect test

Embodiment 1

[0069] When making a specific judgment, the system uses the size of Agaricus bisporus as a characteristic parameter, and divides it into four grades: A grade, B grade, C grade and D grade.

[0070] Grading judgments include the following steps:

[0071] S1, acquiring mushroom image information through a camera;

[0072] S2, extract the region of interest: according to the shooting environment of the mushroom image, set the parameters and intercept the mushroom image with a single background color to obtain the image to be extracted; calculate the coordinate value of the upper left point of the minimum circumscribing rectangle of the mushroom outline, and the minimum circumscribing The width W and height H of the rectangle.

[0073] Specifically, in this embodiment, the camera resolution is 96 as an example. The mushroom image acquired by the system includes the conveyor belt and its edge. In order to accurately obtain the characteristic parameters of Agaricus bisporus, it is ...

Embodiment 2

[0089] The SURF (Speeded-up Robust Features) algorithm is an improved algorithm based on the SIFT (Scale-invariant feature transform) algorithm. It was proposed by Herbert Bay at the European International Conference on Computer Vision in 2006. The algorithm does not depend on pixel values ​​and is occluded, angled etc. The shooting effect is less affected, and it has the characteristics of fast calculation speed and high stability. The SURF algorithm mainly includes two parts: feature point extraction and feature point description.

[0090] On the basis of Example 1, as Figure 14 with Figure 15 As shown, this embodiment also includes S41, which includes:

[0091] S411, extracting feature points: constructing a Hessian matrix, the Hessian matrix H(X, σ) of any pixel point X=(x, y) in the image to be extracted is as follows:

[0092]

[0093] Among them, σ is the scale, Lxx(X,σ), Lxy(X,σ), and Lyy(X,σ) are the second derivatives of the image to be extracted in each dire...

Embodiment 3

[0106] On the basis of embodiment one or two, the step of screening according to browning is also included. Such as Figure 16 As shown, the L value in the Lab format image can better reflect the brightness of the mushroom, thereby reflecting the degree of mushroom browning, so the RGB format image acquired by the camera is converted into a Lab format image. L=0 means black, L=100 means white, large L value means white, small L value means black; L value 86 and above is good quality mushroom, L value between 80-85 is better Mushrooms, L value between 70-79 are poor mushrooms, and mushrooms with L value lower than 69 have no edible value, corresponding to four grades of 1, 2, 3, and 4 respectively. Traverse each pixel of the cap, count the number of pixels corresponding to each level, and calculate the number of pixels corresponding to the four levels of 1, 2, 3, and 4 according to the number of pixels of the cap obtained by the watershed algorithm The ratio of the number to ...

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Abstract

The invention discloses an agaricus bisporus grading judgment method, and belongs to the field of agaricus bisporus production. The device comprises the following steps: S1, acquiring mushroom image information; S2, extracting a region of interest S3, segmenting images, wherein S31, converting a to-be-extracted image into a grayscale image; S32, adopting an OSTU threshold segmentation algorithm for processing; S33, carrying out morphological transformation; S34, performing expansion operation on a morphological transformation diagram; S35, transforming distance; S36, binarizing fixed threshold by taking the distance as a threshold to determine a foreground image; S37, subtracting the foreground image from the background image, and extracting an image contour; s38, finally obtaining the boundary of the original image according to the watershed change of the uncertain area in the markers; S4, calculating the number m of pixels of the foreground image according to the obtained foregroundimage; and S5, judging the grade according to a preset rule and the area of the mushroom pileus. The classification judgment accuracy of the agaricus bisporus can be improved, and errors caused by manual classification are reduced.

Description

technical field [0001] The invention relates to the field of Agaricus bisporus production, in particular to a method for judging the classification of Agaricus bisporus. Background technique [0002] Agaricus bisporus is also known as white mushroom, mushroom, and sea mushroom, and producers and operators in European and American countries often call it common cultivated mushroom or button mushroom. Agaricus bisporus is a mushroom that is cultivated and consumed worldwide. It is known as the "World Mushroom" and can be sold fresh, canned, or salted. The mycelium of Agaricus bisporus is also used as a raw material for medicine. China's Agaricus bisporus is most cultivated in Fujian, Shandong, Henan, Zhejiang and other provinces. Cultivation methods include mushroom house cultivation, greenhouse frame cultivation and greenhouse border cultivation. Different regions, different climatic conditions and different seasons can adopt their own cultivation methods. It is widely di...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/12G06T5/30G06T7/136G06T7/194
CPCG06T7/12G06T7/136G06T7/194G06T5/30G06T2207/10004
Inventor 姜凤利杨鑫孙炳新柳想马诗博沈殿昭王馨瑶
Owner SHENYANG AGRI UNIV
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