How to delete (noisy and short) lines?











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0
down vote

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Using OpenCV with Python, I'm trying to find horizontal and vertical lines in my image.



This is my output :



vertical_lines





horizontal_lines





Well, I'm trying to detect only the long lines and delete the short (noisy) lines.



I hope that my output looks like this modified image:



Final_Horizontal_lines





I can provide you with my code if needed.










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  • I used HoughlinesP (minLineLength ) but still nothing -_-
    – Capito
    Nov 21 at 15:09






  • 1




    Yes, show your code. also show the input image.
    – Cris Luengo
    Nov 21 at 16:40















up vote
0
down vote

favorite












Using OpenCV with Python, I'm trying to find horizontal and vertical lines in my image.



This is my output :



vertical_lines





horizontal_lines





Well, I'm trying to detect only the long lines and delete the short (noisy) lines.



I hope that my output looks like this modified image:



Final_Horizontal_lines





I can provide you with my code if needed.










share|improve this question
























  • I used HoughlinesP (minLineLength ) but still nothing -_-
    – Capito
    Nov 21 at 15:09






  • 1




    Yes, show your code. also show the input image.
    – Cris Luengo
    Nov 21 at 16:40













up vote
0
down vote

favorite









up vote
0
down vote

favorite











Using OpenCV with Python, I'm trying to find horizontal and vertical lines in my image.



This is my output :



vertical_lines





horizontal_lines





Well, I'm trying to detect only the long lines and delete the short (noisy) lines.



I hope that my output looks like this modified image:



Final_Horizontal_lines





I can provide you with my code if needed.










share|improve this question















Using OpenCV with Python, I'm trying to find horizontal and vertical lines in my image.



This is my output :



vertical_lines





horizontal_lines





Well, I'm trying to detect only the long lines and delete the short (noisy) lines.



I hope that my output looks like this modified image:



Final_Horizontal_lines





I can provide you with my code if needed.







python opencv image-processing line noise






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 21 at 16:03









eyllanesc

70.4k93052




70.4k93052










asked Nov 21 at 15:07









Capito

33




33












  • I used HoughlinesP (minLineLength ) but still nothing -_-
    – Capito
    Nov 21 at 15:09






  • 1




    Yes, show your code. also show the input image.
    – Cris Luengo
    Nov 21 at 16:40


















  • I used HoughlinesP (minLineLength ) but still nothing -_-
    – Capito
    Nov 21 at 15:09






  • 1




    Yes, show your code. also show the input image.
    – Cris Luengo
    Nov 21 at 16:40
















I used HoughlinesP (minLineLength ) but still nothing -_-
– Capito
Nov 21 at 15:09




I used HoughlinesP (minLineLength ) but still nothing -_-
– Capito
Nov 21 at 15:09




1




1




Yes, show your code. also show the input image.
– Cris Luengo
Nov 21 at 16:40




Yes, show your code. also show the input image.
– Cris Luengo
Nov 21 at 16:40












1 Answer
1






active

oldest

votes

















up vote
0
down vote



accepted










You can solve that problem by using contours.



im2, contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for contour in contours:
(x, y, w, h) = cv2.boundingRect(contour)
# if h<500: # check the length of verical lines
if w<500: # check the length of horizontal lines
cv2.fillConvexPoly(gray,contour,0) #fill the contour with black color


enter image description here






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    active

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    up vote
    0
    down vote



    accepted










    You can solve that problem by using contours.



    im2, contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    for contour in contours:
    (x, y, w, h) = cv2.boundingRect(contour)
    # if h<500: # check the length of verical lines
    if w<500: # check the length of horizontal lines
    cv2.fillConvexPoly(gray,contour,0) #fill the contour with black color


    enter image description here






    share|improve this answer

























      up vote
      0
      down vote



      accepted










      You can solve that problem by using contours.



      im2, contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
      for contour in contours:
      (x, y, w, h) = cv2.boundingRect(contour)
      # if h<500: # check the length of verical lines
      if w<500: # check the length of horizontal lines
      cv2.fillConvexPoly(gray,contour,0) #fill the contour with black color


      enter image description here






      share|improve this answer























        up vote
        0
        down vote



        accepted







        up vote
        0
        down vote



        accepted






        You can solve that problem by using contours.



        im2, contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        for contour in contours:
        (x, y, w, h) = cv2.boundingRect(contour)
        # if h<500: # check the length of verical lines
        if w<500: # check the length of horizontal lines
        cv2.fillConvexPoly(gray,contour,0) #fill the contour with black color


        enter image description here






        share|improve this answer












        You can solve that problem by using contours.



        im2, contours, hierarchy = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        for contour in contours:
        (x, y, w, h) = cv2.boundingRect(contour)
        # if h<500: # check the length of verical lines
        if w<500: # check the length of horizontal lines
        cv2.fillConvexPoly(gray,contour,0) #fill the contour with black color


        enter image description here







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 22 at 1:59









        Ha Bom

        1




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