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How to classify edges with enclosed boundaries or not in Matlab?



2019 Community Moderator ElectionHow to determine edges in an image optimally?How do I find Waldo with Mathematica?Representing and solving a maze given an imageSupposed easy edge detection in MATLABCreate mask from bwtraceboundary in MatlabMATLAB: adaptive sobel-like edge detectionHow to extend a set of points in MATLABHow to control the order of detected objects by regionprops in matlab?segmenting an object from background using MATLAB based on feature pointsFinding location of corner points at starting and ending of curvature(matlab)










0















I have the following image (replaced by the better image under EDIT):



If I use bwboundaries on the first object (the white blob), I would expect the boundary to traverse the outer part of that first white object



If I use bwboundaries on the second object (the horizontal white line), the boundary is just a horizontal line.



I was hoping there was a way that bwboundaries or some other method can somehow classify these 2 objects differently. That is, it could say the first object's boundary starts and ends at the same point, while for the second object, it starts at the left end and ends at the right end



However, if I look closely at how bwboundaries traverses these objects, I notice that for the first object, it traverses it once for 360 degrees. But for the second object, it actually starts at the left image border, goes to the right image border, AND THEN BACK towards the left image border.



How can I fix this problem for bwboundaries for the 2nd object AND correctly classify these as different objects (the 1st one's boundary should start and end at same point, the 2nd one's boundary SHOULD start and end at DIFFERENT points)?



EDIT:



This is a better image



enter image description here










share|improve this question
























  • As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

    – Luis Mendo
    2 days ago












  • If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

    – user5739619
    2 days ago











  • yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

    – user5739619
    2 days ago











  • Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

    – user5739619
    2 days ago











  • From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

    – HansHirse
    2 days ago
















0















I have the following image (replaced by the better image under EDIT):



If I use bwboundaries on the first object (the white blob), I would expect the boundary to traverse the outer part of that first white object



If I use bwboundaries on the second object (the horizontal white line), the boundary is just a horizontal line.



I was hoping there was a way that bwboundaries or some other method can somehow classify these 2 objects differently. That is, it could say the first object's boundary starts and ends at the same point, while for the second object, it starts at the left end and ends at the right end



However, if I look closely at how bwboundaries traverses these objects, I notice that for the first object, it traverses it once for 360 degrees. But for the second object, it actually starts at the left image border, goes to the right image border, AND THEN BACK towards the left image border.



How can I fix this problem for bwboundaries for the 2nd object AND correctly classify these as different objects (the 1st one's boundary should start and end at same point, the 2nd one's boundary SHOULD start and end at DIFFERENT points)?



EDIT:



This is a better image



enter image description here










share|improve this question
























  • As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

    – Luis Mendo
    2 days ago












  • If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

    – user5739619
    2 days ago











  • yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

    – user5739619
    2 days ago











  • Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

    – user5739619
    2 days ago











  • From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

    – HansHirse
    2 days ago














0












0








0








I have the following image (replaced by the better image under EDIT):



If I use bwboundaries on the first object (the white blob), I would expect the boundary to traverse the outer part of that first white object



If I use bwboundaries on the second object (the horizontal white line), the boundary is just a horizontal line.



I was hoping there was a way that bwboundaries or some other method can somehow classify these 2 objects differently. That is, it could say the first object's boundary starts and ends at the same point, while for the second object, it starts at the left end and ends at the right end



However, if I look closely at how bwboundaries traverses these objects, I notice that for the first object, it traverses it once for 360 degrees. But for the second object, it actually starts at the left image border, goes to the right image border, AND THEN BACK towards the left image border.



How can I fix this problem for bwboundaries for the 2nd object AND correctly classify these as different objects (the 1st one's boundary should start and end at same point, the 2nd one's boundary SHOULD start and end at DIFFERENT points)?



EDIT:



This is a better image



enter image description here










share|improve this question
















I have the following image (replaced by the better image under EDIT):



If I use bwboundaries on the first object (the white blob), I would expect the boundary to traverse the outer part of that first white object



If I use bwboundaries on the second object (the horizontal white line), the boundary is just a horizontal line.



I was hoping there was a way that bwboundaries or some other method can somehow classify these 2 objects differently. That is, it could say the first object's boundary starts and ends at the same point, while for the second object, it starts at the left end and ends at the right end



However, if I look closely at how bwboundaries traverses these objects, I notice that for the first object, it traverses it once for 360 degrees. But for the second object, it actually starts at the left image border, goes to the right image border, AND THEN BACK towards the left image border.



How can I fix this problem for bwboundaries for the 2nd object AND correctly classify these as different objects (the 1st one's boundary should start and end at same point, the 2nd one's boundary SHOULD start and end at DIFFERENT points)?



EDIT:



This is a better image



enter image description here







matlab image-processing edge-detection






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 2 days ago







user5739619

















asked 2 days ago









user5739619user5739619

4931919




4931919












  • As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

    – Luis Mendo
    2 days ago












  • If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

    – user5739619
    2 days ago











  • yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

    – user5739619
    2 days ago











  • Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

    – user5739619
    2 days ago











  • From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

    – HansHirse
    2 days ago


















  • As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

    – Luis Mendo
    2 days ago












  • If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

    – user5739619
    2 days ago











  • yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

    – user5739619
    2 days ago











  • Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

    – user5739619
    2 days ago











  • From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

    – HansHirse
    2 days ago

















As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

– Luis Mendo
2 days ago






As I see it, the distinction between those two classes of objects may not be well defined. If the line was two pixels wide, to what class would it belong to?

– Luis Mendo
2 days ago














If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

– user5739619
2 days ago





If the line is two pixels wide, it doesn't matter to me which class it belongs to. I just need a way to distinguish a line that is one pixel wide from general blobs/polygons

– user5739619
2 days ago













yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

– user5739619
2 days ago





yes, I already know about regionprops. I don't see how any of its properties would allow me to classify lines vs blobs

– user5739619
2 days ago













Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

– user5739619
2 days ago





Just to clarify, the one pixel wide object doesn't have to be a straight line. It could be a curve or bent line, like the updated image I placed under EDIT. This one-pixel wide object should still be classified differently than blobs/polygons

– user5739619
2 days ago













From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

– HansHirse
2 days ago






From here: B = bwboundaries(BW) traces the exterior boundaries of objects[...], and The bwboundaries function implements the Moore-Neighbor tracing algorithm [...]. Therefore, look wikipedia. In short: Contour is 3x3 neighbourhood by definition, thus even for 1-pixel wide objects you have a closed path.

– HansHirse
2 days ago













1 Answer
1






active

oldest

votes


















0














So, I came up with the following idea: For 2d objects, the boundary has most likely unique (x, y) coordinates. For 1d objects, most (if not all) (x, y) values should be present two times. So, for each boundary, we just determine the unique values, or to be more precise the unique rows, and check if the amount has significantly decreased, e.g. using a ratio (#unique rows) / (#all rows). A simple option would be to set up one or more thresholds for the ratio, e.g. ratio > 0.95 should be a 2d object since most values are unique, and ratio < 0.55 should be a 1d object as most values were present two times.



img = uint8(zeros(100));
img(10:20, 10:90) = 255;
img(80, 10:90) = 255;
imshow(img);

upperThr = 0.95;
lowerThr = 0.55;

B = bwboundaries(img);
for k = 1:numel(B)
b = Bk;
origLength = size(b, 1);
b = unique(b, 'rows');
uniqueLength = size(b, 1);
ratio = uniqueLength / origLength;
printf('Object %d: ', k);
if (ratio > upperThr)
printf('2d objectn');
elseif (ratio < lowerThr)
printf('1d objectn');
else
printf('No idean');
end
end


There's plenty of space for code improvements, I wanted to be keep it readable and easy to follow. One-liner fetishists are welcome to do what they like. ;-)






share|improve this answer
























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    1 Answer
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    1 Answer
    1






    active

    oldest

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    active

    oldest

    votes






    active

    oldest

    votes









    0














    So, I came up with the following idea: For 2d objects, the boundary has most likely unique (x, y) coordinates. For 1d objects, most (if not all) (x, y) values should be present two times. So, for each boundary, we just determine the unique values, or to be more precise the unique rows, and check if the amount has significantly decreased, e.g. using a ratio (#unique rows) / (#all rows). A simple option would be to set up one or more thresholds for the ratio, e.g. ratio > 0.95 should be a 2d object since most values are unique, and ratio < 0.55 should be a 1d object as most values were present two times.



    img = uint8(zeros(100));
    img(10:20, 10:90) = 255;
    img(80, 10:90) = 255;
    imshow(img);

    upperThr = 0.95;
    lowerThr = 0.55;

    B = bwboundaries(img);
    for k = 1:numel(B)
    b = Bk;
    origLength = size(b, 1);
    b = unique(b, 'rows');
    uniqueLength = size(b, 1);
    ratio = uniqueLength / origLength;
    printf('Object %d: ', k);
    if (ratio > upperThr)
    printf('2d objectn');
    elseif (ratio < lowerThr)
    printf('1d objectn');
    else
    printf('No idean');
    end
    end


    There's plenty of space for code improvements, I wanted to be keep it readable and easy to follow. One-liner fetishists are welcome to do what they like. ;-)






    share|improve this answer





























      0














      So, I came up with the following idea: For 2d objects, the boundary has most likely unique (x, y) coordinates. For 1d objects, most (if not all) (x, y) values should be present two times. So, for each boundary, we just determine the unique values, or to be more precise the unique rows, and check if the amount has significantly decreased, e.g. using a ratio (#unique rows) / (#all rows). A simple option would be to set up one or more thresholds for the ratio, e.g. ratio > 0.95 should be a 2d object since most values are unique, and ratio < 0.55 should be a 1d object as most values were present two times.



      img = uint8(zeros(100));
      img(10:20, 10:90) = 255;
      img(80, 10:90) = 255;
      imshow(img);

      upperThr = 0.95;
      lowerThr = 0.55;

      B = bwboundaries(img);
      for k = 1:numel(B)
      b = Bk;
      origLength = size(b, 1);
      b = unique(b, 'rows');
      uniqueLength = size(b, 1);
      ratio = uniqueLength / origLength;
      printf('Object %d: ', k);
      if (ratio > upperThr)
      printf('2d objectn');
      elseif (ratio < lowerThr)
      printf('1d objectn');
      else
      printf('No idean');
      end
      end


      There's plenty of space for code improvements, I wanted to be keep it readable and easy to follow. One-liner fetishists are welcome to do what they like. ;-)






      share|improve this answer



























        0












        0








        0







        So, I came up with the following idea: For 2d objects, the boundary has most likely unique (x, y) coordinates. For 1d objects, most (if not all) (x, y) values should be present two times. So, for each boundary, we just determine the unique values, or to be more precise the unique rows, and check if the amount has significantly decreased, e.g. using a ratio (#unique rows) / (#all rows). A simple option would be to set up one or more thresholds for the ratio, e.g. ratio > 0.95 should be a 2d object since most values are unique, and ratio < 0.55 should be a 1d object as most values were present two times.



        img = uint8(zeros(100));
        img(10:20, 10:90) = 255;
        img(80, 10:90) = 255;
        imshow(img);

        upperThr = 0.95;
        lowerThr = 0.55;

        B = bwboundaries(img);
        for k = 1:numel(B)
        b = Bk;
        origLength = size(b, 1);
        b = unique(b, 'rows');
        uniqueLength = size(b, 1);
        ratio = uniqueLength / origLength;
        printf('Object %d: ', k);
        if (ratio > upperThr)
        printf('2d objectn');
        elseif (ratio < lowerThr)
        printf('1d objectn');
        else
        printf('No idean');
        end
        end


        There's plenty of space for code improvements, I wanted to be keep it readable and easy to follow. One-liner fetishists are welcome to do what they like. ;-)






        share|improve this answer















        So, I came up with the following idea: For 2d objects, the boundary has most likely unique (x, y) coordinates. For 1d objects, most (if not all) (x, y) values should be present two times. So, for each boundary, we just determine the unique values, or to be more precise the unique rows, and check if the amount has significantly decreased, e.g. using a ratio (#unique rows) / (#all rows). A simple option would be to set up one or more thresholds for the ratio, e.g. ratio > 0.95 should be a 2d object since most values are unique, and ratio < 0.55 should be a 1d object as most values were present two times.



        img = uint8(zeros(100));
        img(10:20, 10:90) = 255;
        img(80, 10:90) = 255;
        imshow(img);

        upperThr = 0.95;
        lowerThr = 0.55;

        B = bwboundaries(img);
        for k = 1:numel(B)
        b = Bk;
        origLength = size(b, 1);
        b = unique(b, 'rows');
        uniqueLength = size(b, 1);
        ratio = uniqueLength / origLength;
        printf('Object %d: ', k);
        if (ratio > upperThr)
        printf('2d objectn');
        elseif (ratio < lowerThr)
        printf('1d objectn');
        else
        printf('No idean');
        end
        end


        There's plenty of space for code improvements, I wanted to be keep it readable and easy to follow. One-liner fetishists are welcome to do what they like. ;-)







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited 2 days ago

























        answered 2 days ago









        HansHirseHansHirse

        54513




        54513





























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