A method and system for obtaining phenotypic parameters of edible fungi

Abstract

The present invention provides a method and system for obtaining phenotypic parameters of edible mushrooms. The method comprises obtaining an original picture of black-skinned Alpinia thunbergii to obtain a contour set, analyzing each contour of black-skinned Alpinia thunbergii in the contour set to distinguish and obtain an adhesion contour set and a non-adhesion contour set; processing the adhesion contour set to obtain a new contour set, and combining it with the non-adhesion contour set to obtain a final contour set; obtaining a single black-skinned Alpinia thunbergii contour from the final contour set, locating the stipe and cap of the black-skinned Alpinia thunbergii contour according to the average grayscale value of pixels in the left area and the average grayscale value of pixels in the right area of ​​the black-skinned Alpinia thunbergii contour; obtaining the plant height of the black-skinned Alpinia thunbergii according to the Euclidean distance between the cap vertex and the lowest point of the stipe, obtaining the cap diameter of the black-skinned Alpinia thunbergii according to the Euclidean distance between the highest point of the cap and the lowest point of the cap, and obtaining the maximum width of the stipe of the black-skinned Alpinia thunbergii according to the Euclidean distance between the highest point of the stipe and the lowest point of the stipe. The present application can identify and separate adherent bacteria to improve measurement efficiency and accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a method and system for acquiring phenotypic parameters of edible fungi. Background Art

[0002] In the process of edible fungi breeding, accurate and efficient evaluation of their phenotypic parameters is crucial for discovering new varieties. In practical applications, researchers usually measure multiple samples simultaneously to improve efficiency. However, multiple samples placed randomly are prone to adhesion. Adhering bacteria are not only difficult to count accurately, but also affect the subsequent accurate measurement of size and other morphological characteristics. Therefore, how to effectively identify and separate adherent bacteria has become the key to improving the efficiency and accuracy of current automated measurement methods. Summary of the invention

[0003] Based on this, the purpose of the present invention is to provide a method and system for obtaining phenotypic parameters of edible fungi, which are used to effectively identify and separate adherent bacteria to improve measurement efficiency and accuracy.

[0004] In one aspect, the present invention provides a method for obtaining phenotypic parameters of edible fungi, comprising:

[0005] Get the original image of edible mushrooms I , the edible fungi include Alpinia solani, the original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I o The corresponding contour set C o , contour set C o Includes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ;

[0006] From the final outline set Cσ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata C on Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn According to the profile of the black-skinned Alpinia fasciata after the rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average gray value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average grayscale value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia terrestris in the image is separated, a color image of each black-skinned Alpinia terrestris is obtained;

[0007] Traversing the contour of the black-skinned Alpinia fasciata after rotation C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem Prmax and the lowest point of the stipe P rmin ; According to the cap apex P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0008] The above-mentioned method for obtaining phenotypic parameters of edible mushrooms improves the measurement efficiency and accuracy of the phenotypic parameters of black-skinned Alpinia fasciata by identifying and separating the adhered bacteria and then measuring the phenotypic parameters. C o Each black-skinned Alpinia fasciata outline C on Distinguish and get the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; From the final contour set C σ Get the outline of a single black-skinned Alpinia thunbergii from the image, and according to the left area R' of the black-skinned Alpinia thunbergii outline A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to locate the stipe and cap of the black-skinned Alpinia fasciata outline; according to the top of the cap P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD, according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0009] In addition, the method for obtaining phenotypic parameters of edible fungi according to the present invention may also have the following additional technical features:

[0010] Furthermore, the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α The steps include:

[0011] Get the black-skinned Alpinia fasciata outline C on , determine the outline of the black-skinned Alpinia fasciata C on Whether all the judgment conditions are met at the same time, the judgment condition is the outline of the black skinned Alpinia fasciata C on Form Factor F Greater than the first threshold F max And the outline of the black-skinned Alpinia fasciata C on The minimum enclosing rectangle aspect ratio of the outline Ar Greater than the second threshold Ar max ;

[0012] If all the judgment conditions are met at the same time, the corresponding black skinned Alpinia fasciata outline C on Insert non-adhesive contour set C α ; If all the judgment conditions cannot be met at the same time, the corresponding black skin Alpinia albuminata outline C on Insert Adhesion Contour Set C γ ;

[0013] Among them, the shape factor F The calculation formula is: ;

[0014] In the formula, A Represents the outline of Alpinia fasciata C on area; C Represents the outline of Alpinia fasciata C on The perimeter is calculated using the nearest interpolation method.

[0015] Further, for the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ The steps include:

[0016] According to the preset training model, the original image I Perform training inference to obtain multiple contour images I β and the contour image I β The corresponding contour set C β ; Determine the contour set C according to the preset conditions β Whether each contour in belongs to the set of adhesion contours C γ A contour in , where the preset condition is the contour set C β The center coordinates of the contours in the adhesion contour set C γ within the scope of

[0017] If so, then the contour set C β The set of adhesion contours C γ The contours of a certain contour in constitute a new contour set C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ , the final contour set C σ Includes multiple Alpinia capillaris silhouettes C on , according to the final contour set C σ Generate the corresponding binary image I σ .

[0018] Furthermore, the calculation formula of the center coordinates is:

[0019] ; ;

[0020] In the formula, ( X cb , Y cb ) represents the contour C βb The center coordinates of the contour C βb For the contour set Cβ The bth contour in ; n Represents a set of scattered points on a contour; i Indicates the point number, x i It is i The horizontal coordinate of the point, y i It is i The vertical coordinate of a point.

[0021] Further, according to the connection l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn In the steps, connect l The angle is calculated as:

[0022] ;

[0023] In the formula, θ l Indicates connection l The angle of x m , y m )and( x n , y n ) represents the minimum fitting quadrilateral T f The coordinates of the two endpoints corresponding to the maximum Euclidean distance in .

[0024] Further, the left area R' of the original image of a single black-skinned Alpinia fasciata is calculated respectively. A Average grayscale value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average grayscale value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The steps of making the stipe and cap include:

[0025] According to the final outline set C σ Construct a mask map and compare it with the original image I After bitwise operation, the bounding rectangle R of each single original image of Alpinia fasciata is obtained. A , and obtain the enclosing rectangle R A The midpoint of the long side, connecting the two midpoints to enclose the rectangle R AIt is divided into two rectangular frames, the two rectangular frames are a left rectangular frame and a right rectangular frame, and the left rectangular frame is the left area R' A The right rectangular frame is the right area R'' A ;

[0026] Calculate the left area R' A Average grayscale value of pixels and right area R'' A Average gray value of pixels;

[0027] Compare the left area R' A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to obtain the smaller average gray value of pixels and the larger average gray value of pixels. The smaller average gray value of pixels corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular frame. C on The larger pixel average gray value corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular box. C on For the cap;

[0028] The left area R' A and the right area R'' A The sizes are M A × N A Pixel, the calculation formula for the average gray value of the pixel is:

[0029] ;

[0030] In the formula, Mean_Gray is the average gray value of pixels; I ( x , y ) is the gray value of the pixel with coordinates (x, y) in the rectangular frame; M A Indicates the number of pixels contained in the horizontal axis, N A Indicates the number of pixels contained in the vertical coordinate direction.

[0031] Another aspect of the present invention provides a system for acquiring phenotypic parameters of edible fungi, comprising:

[0032] Acquisition module, used to obtain the original image of edible fungi I , the edible fungi include Alpinia solani, the original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I oThe corresponding contour set C o , contour set C o Includes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ;

[0033] The pixel average gray value calculation module is used to calculate the average gray value of the pixel from the final contour set. C σ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata C on Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn According to the profile of the black-skinned Alpinia fasciata after the rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average grayscale value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average grayscale value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia terrestris in the image is separated, a color image of each black-skinned Alpinia terrestris is obtained;

[0034] Parameter calculation module, used to traverse the contour of the rotated black-skinned Alpinia fasciata C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem P rmax and the lowest point of the stipe P rmin ; According to the cap apex P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH . BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Flow chart of the method for obtaining phenotypic parameters of edible fungi according to an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram of the pretreatment process in an embodiment of the present invention;

[0037] Figure 3 is the adhesion contour set C in the embodiment of the present invention γ and the non-adhesive contour set C α Schematic diagram of the differentiation process;

[0038] Figure 4 In the embodiment of the present invention, the adhesion contour set C is replaced γ Schematic diagram of the process;

[0039] Figure 5 Schematic diagram of the process of determining the main direction of the black-skinned Alpinia fasciata and rotating the outline to the main direction in an embodiment of the present invention;

[0040] Figure 6 This is the image of the black-skinned Alpinia fasciata after root trimming;

[0041] Figure 7 The left area R' is rotated A and the right area R'' A And establish the process diagram of the coordinate system;

[0042] Figure 8 Schematic diagram for explaining the phenotypic parameters of each part of the black-skinned Alpinia fasciata in the embodiment of the present invention;

[0043] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0044] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0046] In order to effectively identify and separate the adherent bacteria to improve the measurement efficiency and accuracy, the present application provides a method and system for obtaining phenotypic parameters of edible mushrooms, which improves the measurement efficiency and accuracy of the phenotypic parameters of black-skinned Alpinia fasciata by identifying and separating the adherent bacteria and then measuring the phenotypic parameters; specifically, the profile set is analyzed C o Each black-skinned Alpinia fasciata outline C on Distinguish and get the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours Cδ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; From the final contour set C σ Get the outline of a single black-skinned Alpinia thunbergii from the image, and according to the left area R' of the black-skinned Alpinia thunbergii outline A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to locate the stipe and cap of the black-skinned Alpinia fasciata outline; according to the top of the cap P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0047] In order to facilitate understanding of the present invention, several embodiments of the present invention are provided below. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0048] Embodiment 1

[0049] See also Figure 1 , which shows a method for obtaining phenotypic parameters of edible fungi in a first embodiment of the present invention, and the method comprises steps S101 to S103:

[0050] S101. Obtaining the original image of edible fungi I , edible mushrooms including Alpinia solani, original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I o The corresponding contour set C o , contour set C oIncludes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ .

[0051] For the original image I The threshold segmentation algorithm is used to segment the foreground and background in the image, and the foreground is the black-skinned Alpinia fasciata. Threshold segmentation technology is one of the most classic image segmentation methods. The key to this technology is to find an appropriate grayscale threshold, which is usually selected based on the grayscale histogram of the image. If only one threshold is used in the entire image, this method is called the global threshold method, and the entire image is divided into two areas, namely the target object and the background object. For images with relatively obvious contrast between the foreground and background, their grayscale histogram is a bimodal shape. The pixel value corresponding to the trough between the two peaks can be selected as the global threshold to segment the image into the target object and the background object. The formula is as follows:

[0052] ;

[0053] in f ( x , y ) represents the point ( x , y ), g ( x , y ) is the segmented image, T is the global threshold. The biggest feature of this method is that it is simple to calculate and works very well for images with a large difference in background and foreground grayscale values. Through the threshold segmentation algorithm, a binary image can be obtained. I c .

[0054] like Figure 2 As shown, after obtaining the original picture I After that, the original image needs to be I Preprocessing is performed as follows: first, the original image I Perform threshold segmentation on the original image I After threshold segmentation, a binary image containing a lot of noise and interference is usually obtained.I c In order to eliminate these interferences and form an image containing only the contour of the black-skinned Alpinia fasciata, morphological operations need to be performed on it. As a specific example, the closing operation is a commonly used morphological operation, which includes two steps: dilation and erosion. The closing operation helps to connect small disconnected objects, fill small holes and elongated protrusions, while maintaining the integrity of large objects to obtain a complete closed contour image. I o .

[0055] By analyzing the closed contour image I o , in which the black-skinned Alpinia fasciata region is marked as foreground, and the background region is marked as background, to create a mask image. The mask image is then applied to the original image, and the mask image and the original image are bitwise operated to separate the mushroom from the background. Not only is it highly accurate, but it can also effectively extract the black-skinned Alpinia fasciata region, thereby enabling subsequent analysis and processing.

[0056] like Figure 3 As shown in the figure, due to the existence of adherent black-skinned Alpinia thunbergii individuals, it is necessary to segment the adherent black-skinned Alpinia thunbergii individuals. Specifically, the contour set is analyzed. C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α The steps include:

[0057] Get the black-skinned Alpinia fasciata outline C on , determine the outline of the black-skinned Alpinia fasciata C on Whether all the judgment conditions are met at the same time, the judgment condition is the outline of the black skinned Alpinia fasciata C on Form Factor F Greater than the first threshold F max And the outline of the black-skinned Alpinia fasciata C on The minimum enclosing rectangle aspect ratio of the outline Ar Greater than the second threshold Ar max ; If all the judgment conditions are met at the same time, the corresponding black skinned Alpinia albuminata outline C on Insert non-adhesive contour set C α ; If all the judgment conditions cannot be met at the same time, the corresponding black skin Alpinia albuminata outline C on Insert Adhesion Contour Set C γ ;

[0058] Among them, the shape factor F The calculation formula is: ;

[0059] In the formula, A Represents the outline of Alpinia fasciata C on The area can be obtained by existing calculation methods; C Represents the outline of Alpinia fasciata C on The perimeter is calculated using the nearest interpolation method.

[0060] Further, after obtaining the adhesion contour set C γ and the non-adhesive contour set C α After that, for the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ , specifically:

[0061] According to the preset training model, the original image I Perform training inference to obtain multiple contour images I β As well as the contour image I β The corresponding contour set C β ; Determine the contour set C according to the preset conditions β Whether each contour in belongs to the set of adhesion contours C γ A contour in , where the preset condition is the contour set C β The center coordinates of the contours in the adhesion contour set C γ within the scope of

[0062] If so, then the contour set C β The set of adhesion contours C γ The contours of a certain contour in constitute a new contour set C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ , the final contour set C σ Includes multiple Alpinia capillaris silhouettes C on , according to the final contour set C σGenerate the corresponding binary image I σ .

[0063] The calculation formula of the center coordinates is:

[0064] ; ;

[0065] In the formula, ( X cb , Y cb ) represents the contour C βb The center coordinates of the contour C βb For the contour set C β The bth contour in ; n Represents a set of scattered points on a contour; i Indicates the point number, x i It is i The horizontal coordinate of the point, y i It is i The vertical coordinate of a point.

[0066] Specifically, after obtaining the adhesion contour set C γ Then, according to the contour set C β Traverse all the contours, where the contour set C β ={C β1 , C β2 , …, C βb}, contour C βb For the contour set C β The bth contour in the figure, find contour C respectively β1 , C β2 , …, C βb The corresponding center coordinates P c1 ( X c1 , Y c1 ), P c2 ( X c2 , Y c2 ), …, P cb ( X cb , Y cb ), if the center coordinates P cb ( X cb , Ycb ) in the adhesion contour set C γ If the current contour C is within the area enclosed by any contour above, βb The result of threshold segmentation is in the set of cohesive contours C. γ Therefore, the current contour C βb Place in New Profile Set C δ After the traversal is completed, the contour results of the non-adhesive black-skinned Alpinia thunbergii in the segmentation result are eliminated, and only the contour results of the adherent black-skinned Alpinia thunbergii are retained, that is, the new contour set C δ Specific examples: Figure 4 As shown, Figure 4 (a) is the extracted contour set C β The center coordinates of all contours in ; Figure 4 (b) is based on whether the center is in the adhesion contour set C γ In the area enclosed by any contour, select the contour that meets the conditions; Figure 4 (c) in the figure is the contour that meets the conditions. Figure 4 (d) in the figure is the non-adhesive contour set C α ; Figure 4 (e) in the figure is the new contour set after replacement. C δ and non-adhesive contour set C α Combine to get the final contour set C σ .

[0067] Finally, the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ .

[0068] It should be further explained that, in this embodiment, the trained YOLOv8 instance segmentation model is used to segment the original image. I Perform training inference to obtain a complete contour image I β and the full outline image I β The corresponding contour set C β . Then traverse the contour set C o , for the contour set C o Each contour in is analyzed to distinguish it into a set of adhesion contours C γ and the non-adhesive contour set C α .

[0069] S102. From the final contour setC σ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata C on Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn ; According to the profile of the black-skinned Alpinia fasciata after rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average grayscale value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average grayscale value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia ternata is separated, a color image of each black-skinned Alpinia ternata is obtained.

[0070] Since mushrooms (i.e., black-skinned Alpinia fasciata) have complex morphologies, the sizes and orientations of individual mushrooms are inconsistent, which poses a challenge to accurately measuring phenotypic parameters. In order to more accurately obtain the phenotypic parameters of each mushroom, in this embodiment, first, each mushroom outline is extracted separately and rotated to the correct horizontal position for separate calculations.

[0071] As a specific example, take the final contour set C σ 10 individual mushroom silhouettes in the final silhouette set C σ ={C σ1 , C σ2 , …, C σ10}, through careful observation of the outline of a single mushroom, six key points are extracted as feature points for extracting the phenotypic parameters of the mushroom corresponding to the outline. σ10 Take the example to introduce the key point extraction method, specifically:

[0072] like Figure 5 As shown, first determine the main direction of the mushroom, the direction of the mushroom stem is the main direction of the mushroom. Specifically: draw the outline C σ10 The minimum fitting quadrilateral T f , the four points of the quadrilateral are P 1( x 1, y 1) P 2( x 2, y 2) P 3( x 3. y 3) P 4( x 4. y 4). Calculate the Euclidean distance between the four points. D mn , and find the maximum Euclidean distance D mn_max Corresponding two points, get the line between these two points l , connection l The direction of the mushroom is the main direction.

[0073] Secondly, rotate the outline to reposition the outline data. Specifically: rotate the entire mushroom outline along the connecting line l The angle is rotated to the horizontal position to obtain the contour C σ10 The rotated contour C’ σ10 Among them, the connection l The angle is calculated as:

[0074] ;

[0075] In the formula, θ l Indicates connection l The angle of x m , y m )and( x n , y n ) represents the minimum fitting quadrilateral T f Maximum Euclidean distance D mn_max The corresponding two endpoints coordinates.

[0076] Although the rotated contour is obtained C’ σ10 However, due to unclear connection l The direction of the rotation will affect the judgment of the stem and the cap.C’ σn The cap direction is to the left, and the contour C’ σn When the cap of the pileus is facing right, the entire rotated outline C’ σn Rotate 180° to correctly position. Specifically, determine the contour after rotation C’ σn The method to check whether it is in the positive direction is as follows:

[0077] like Figure 6 As shown in the figure, the stem of the mushroom has been shaved and its color is white-gray, which is quite different from the dark brown color of the entire mushroom body. Therefore, the outline after rotation is C’ σn The circumscribed rectangle R A ,like Figure 7 As shown, specifically, according to the final contour set C σ , construct a mask map, that is, fill the inside of each black-skinned Alpinia fasciata in the contour set with white and the outside with black, which is different from the original image I After bitwise operation, the bounding rectangle R of each single image of Alpinia fasciata is obtained. A , and obtain the enclosing rectangle R A The midpoint of the long side, connecting the two midpoints to enclose the rectangle R A It is divided into two rectangular boxes, the left rectangular box and the right rectangular box. The left rectangular box is the left area R' A , the right rectangular box is the right area R'' A ;

[0078] Calculate the left area R' A Average grayscale value of pixels and right area R'' A Average gray value of pixels; where the left area R' A and the right area R'' A The sizes are M A × N A Pixel, the calculation formula for the average gray value of the pixel is:

[0079] ;

[0080] In the formula, Mean_Gray is the average gray value of pixels; I ( x , y ) is the gray value of the pixel with coordinates (x, y) in the rectangular frame; M A Indicates the number of pixels contained in the horizontal axis, N AIndicates the number of pixels contained in the vertical coordinate direction.

[0081] Compare the left area R' A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to obtain the smaller average gray value of pixels and the larger average gray value of pixels. The smaller average gray value of pixels corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular frame. C on The larger pixel average gray value corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular box. C on For the cap.

[0082] In this embodiment, the cap part faces right, therefore, the whole outline is rotated 180° to make the cap part face left, and a coordinate system is established with the lower left corner of the image as the origin for correct positioning.

[0083] S103, traversing the contour of the black-skinned Alpinia fasciata after rotation C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem P rmax and the lowest point of the stipe P rmin ; According to the cap apex P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe Prmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0084] After rotation C’ σ10 For example, find the top of the cap P top ( x top , y top ) and the lowest point of the stipe P bottom ( x bottom , y bottom ), which should meet the following conditions:

[0085] ;

[0086] Then the top of the cap P top ( x top , y top ) and the lowest point of the stipe P bottom ( x bottom , y bottom ) is bounded by the average value of the horizontal axis, and the rotated contour C’ σ10 Cap contour C’ σ10_left and the outline of the stem C’ σ10_right Two parts. y top and y bottom For the outline x top and x bottom Similarly, find the highest point of the left side contour (i.e. the cap part) P lmax ( x lmax , y lmax ) and the lowest point P lmin ( x lmin , y lmin ), the highest point of the right side contour (i.e. the stem part)P rmax ( x rmax , y rmax ) and the lowest point P rmin ( x rmin , y rmin ).by P top and P bottom The Euclidean distance between two points is used as the height of the mushroom MH ;by P lmax and P lmin Euclidean distance between two points D mn As the diameter of the mushroom cap MWD ;by P rmax and P rmin The Euclidean distance between two points is the maximum width of the mushroom stem MSH Specific examples: Figure 8 shown.

[0087] In summary, the method for obtaining phenotypic parameters of edible mushrooms in the above embodiment of the present invention improves the measurement efficiency and accuracy of the phenotypic parameters of black-skinned Alpinia fasciata by identifying and separating the adhered bacteria and then measuring the phenotypic parameters; specifically, the profile set is analyzed. C o Each black-skinned Alpinia fasciata outline C on Distinguish and get the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; From the final contour set C σ Get the outline of a single black-skinned Alpinia thunbergii from the image, and according to the left area R' of the black-skinned Alpinia thunbergii outline A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to locate the stipe and cap of the black-skinned Alpinia fasciata outline; according to the top of the cap P top The lowest point of the stemP bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0088] Embodiment 2

[0089] The second embodiment of the present invention provides a system for obtaining phenotypic parameters of edible mushrooms, comprising:

[0090] Acquisition module, used to obtain the original image of edible fungi I , the edible fungi include Alpinia solani, the original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I o The corresponding contour set C o , contour set C o Includes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ;

[0091] The pixel average gray value calculation module is used to calculate the average gray value of the pixel from the final contour set. C σ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata Con Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn According to the profile of the black-skinned Alpinia fasciata after the rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average grayscale value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average grayscale value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia terrestris in the image is separated, a color image of each black-skinned Alpinia terrestris is obtained;

[0092] Parameter calculation module, used to traverse the contour of the rotated black-skinned Alpinia fasciata C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem P rmax and the lowest point of the stipe P rmin ; According to the cap apex Ptop The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0093] In summary, the edible mushroom phenotypic parameter acquisition system in the above embodiment of the present invention improves the measurement efficiency and accuracy of the phenotypic parameters of the black-skinned Alpinia fasciata by identifying and separating the adhered bacteria and then measuring the phenotypic parameters; specifically, the profile set is analyzed. C o Each black-skinned Alpinia fasciata outline C on Distinguish and get the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; From the final contour set C σ Get the outline of a single black-skinned Alpinia thunbergii from the image, and according to the left area R' of the black-skinned Alpinia thunbergii outline A Average grayscale value of pixels and right area R'' A The average gray value of pixels is used to locate the stipe and cap of the black-skinned Alpinia fasciata outline; according to the top of the cap P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe Prmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

[0094] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0095] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or processing in another suitable manner as necessary, and then stored in a computer memory.

[0096] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0097] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0098] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for obtaining phenotypic parameters of edible fungi, characterized in that: include: Get the original image of edible mushrooms I , the edible fungi include Alpinia solani, the original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I o The corresponding contour set C o , contour set C o Includes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; From the final outline set C σ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata C on Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn According to the profile of the black-skinned Alpinia fasciata after the rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average gray value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average gray value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia terrestris in the image is separated, a color image of each black-skinned Alpinia terrestris is obtained; Traversing the contour of the black-skinned Alpinia fasciata after rotation C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem P rmax and the lowest point of the stipe P rmin ; According to the cap apex P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

2. The method for obtaining phenotypic parameters of edible fungi according to claim 1, characterized in that: Analyze profile sets C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α The steps include: Get the black-skinned Alpinia fasciata outline C on , determine the outline of the black-skinned Alpinia fasciata C on Whether all the judgment conditions are met at the same time, the judgment condition is the outline of the black skinned Alpinia fasciata C on Form Factor F Greater than the first threshold F max And the outline of the black-skinned Alpinia fasciata C on The minimum enclosing rectangle aspect ratio of the outline Ar Greater than the second threshold Ar max ; If all the judgment conditions are met at the same time, the corresponding black skinned Alpinia fasciata outline C on Insert non-adhesive contour set C α ; If all the judgment conditions cannot be met at the same time, the corresponding black skin Alpinia albuminata outline C on Insert Adhesion Contour Set C γ ; Among them, the shape factor F The calculation formula is: ; In the formula, A Represents the outline of Alpinia fasciata C on area; C Represents the outline of Alpinia fasciata C on The perimeter is calculated using the nearest interpolation method.

3. The method for obtaining phenotypic parameters of edible fungi according to claim 2, characterized in that: For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ The steps include: According to the preset training model, the original image I Perform training inference to obtain multiple contour images I β and the contour image I β The corresponding contour set C β ; Determine the contour set C according to the preset conditions β Whether each contour in belongs to the set of adhesion contours C γ A contour in , where the preset condition is the contour set C β The center coordinates of the contours in the adhesion contour set C γ within the scope of If so, then the contour set C β The set of adhesion contours C γ The contours of a certain contour in constitute a new contour set C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ , the final contour set C σ Includes multiple Alpinia capillaris silhouettes C on , according to the final contour set C σ Generate the corresponding binary image I σ .

4. The method for obtaining phenotypic parameters of edible fungi according to claim 3, characterized in that: The calculation formula of the center coordinates is: ； ； In the formula, ( X cb , Y cb ) represents the contour C βb The center coordinates of the contour C βb The contour set C β The bth contour in ; n Represents a set of scattered points on a contour; i Indicates the point number, x i It is i The horizontal coordinate of the point, y i It is i The vertical coordinate of a point.

5. The method for obtaining phenotypic parameters of edible fungi according to claim 1, characterized in that: Follow the connection l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn In the steps, connect l The angle is calculated as: ； In the formula, θ l Indicates connection l The angle of x m , y m )and( x n , y n ) represents the minimum fitting quadrilateral T f The coordinates of the two endpoints corresponding to the maximum Euclidean distance in .

6. The method for obtaining phenotypic parameters of edible fungi according to claim 1, characterized in that: Calculate the left area R' of the original image of a single black-skinned Alpinia fasciata A Average gray value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average gray value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The steps of making the stipe and cap include: According to the final outline set C σ Construct a mask map and compare it with the original image I After bitwise operation, the bounding rectangle R of each single original image of Alpinia fasciata is obtained. A , and obtain the enclosing rectangle R A The midpoint of the long side, connecting the two midpoints to enclose the rectangle R A It is divided into two rectangular frames, the two rectangular frames are a left rectangular frame and a right rectangular frame, and the left rectangular frame is the left area R' A The right rectangular frame is the right area R'' A ; Calculate the left area R' A Average gray value of pixels and right area R'' A Average gray value of pixels; Compare the left area R' A Average gray value of pixels and right area R'' A The average gray value of pixels is used to obtain the smaller average gray value of pixels and the larger average gray value of pixels. The smaller average gray value of pixels corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular frame. C on The larger pixel average gray value corresponds to the outline of the black-skinned Alpinia fasciata in the rectangular box. C on For the cap; The left area R' A and the right area R'' A The sizes are M A × N A Pixel, the calculation formula for the average gray value of the pixel is: ； In the formula, Mean_Gray is the average gray value of pixels; I ( x , y ) is the gray value of the pixel with coordinates (x, y) in the rectangular frame; M A Indicates the number of pixels contained in the horizontal axis, N A Indicates the number of pixels contained in the vertical coordinate direction.

7. A system for acquiring phenotypic parameters of edible fungi, characterized in that: include: Acquisition module, used to obtain the original image of edible fungi I , the edible fungi include Alpinia solani, the original image I Including background and black-skinned Alpinia fasciata, according to the original picture I Get a complete closed contour image I o As well as closed contour images I o The corresponding contour set C o , contour set C o Includes multiple Alpinia capillaris silhouettes C on , analyze the contour set C o Each closed contour area in is distinguished to obtain the adhesion contour set C γ and the non-adhesive contour set C α ; For the adhesion contour set C γ Processing to obtain a new set of contours C δ , and then the non-adhesive contour set C α With new outline set C δ Combined into the final outline set C σ ; The pixel average gray value calculation module is used to calculate the average gray value of the pixel from the final contour set. C σ Get the outline of a single black-skinned Alpinia fasciata C on , according to the outline of the black-skinned Alpinia fasciata C on Get a minimum fitting quadrilateral T f , according to the minimum fitting quadrilateral T f The connecting line corresponding to the two endpoints with the largest distance l Determine the main direction of the black-skinned Alpinia fasciata and follow the connecting line l The angle of the black skinned Alpinia fasciata outline C on Rotate to a horizontal position to obtain the outline of the black-skinned Alpinia fasciata after rotation C’ σn According to the profile of the black-skinned Alpinia fasciata after the rotation C’ σn Get the corresponding original image I The original image of a single black-skinned Alpinia thunbergii isolated from the image is used to calculate the left area R' of the original image of a single black-skinned Alpinia thunbergii. A Average gray value of pixels and right area R'' A The average gray value of the pixel, according to the left area R' A Average gray value of pixels and right area R'' A The outline of the black-skinned Alpinia fasciata is obtained by locating the average gray value of pixels C on The stem and cap of the mushroom, where the original image is the original image according to the contour I After each black-skinned Alpinia terrestris in the image is separated, a color image of each black-skinned Alpinia terrestris is obtained; Parameter calculation module, used to traverse the contour of the rotated black-skinned Alpinia fasciata C’ σn Each discrete point of the cap is obtained P top and the lowest point of the stipe P bottom , according to the cap apex P top and the lowest point of the stipe P bottom Get the cap outline C’ σn_left and the outline of the stem C’ σn_right , according to the cap contour C’ σn_left Get the highest point of the cap P lmax and the lowest point of the cap P lmin , according to the stipe contour C’ σn_right Get the highest point of the stem P rmax and the lowest point of the stipe P rmin ; According to the cap apex P top The lowest point of the stem P bottom The plant height of Alternaria albuminosa was obtained by using the Euclidean distance MH , according to the highest point of the cap P lmax The lowest point of the cap P lmin The Euclidean distance is used to obtain the cap diameter of the black-skinned Alpinia fasciata MWD , according to the highest point of the stipe P rmax and the lowest point of the stipe P rmin The maximum width of the stipe of Alternaria albuminosa is obtained by using the Euclidean distance MSH .

Images