Image Filter gives varying results for similar images





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1















I am experimenting with custom kernels to extract border lines in given images.



The filter I am using is np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]]).
For the given set of images which are of a similar nature, the code generates results where sometimes the hatchings are present whereas absent for other images.



I am not able to figure out why this is happening. I have read about custom filters and how filters work but it does not solve my issue.



The code is as follows:



import cv2

import sys

import numpy as np 



im_name = sys.argv[1]#give path to the image



im = cv2.imread(im_name, 0)



im_copy = im.copy()



#create custom filter



my_filter = np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]])



dst = cv2.filter2D(im, -1, my_filter)



cv2.imshow("test", im)

cv2.imshow("check", dst)

cv2.waitKey(0)

cv2.destroyAllWindows()


Picture 1 and 2 show deviant result, rest of the pictures show expected
results






python opencv image-processing imagefilter







share|improve this question































    1















    I am experimenting with custom kernels to extract border lines in given images.



    The filter I am using is np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]]).
    For the given set of images which are of a similar nature, the code generates results where sometimes the hatchings are present whereas absent for other images.



    I am not able to figure out why this is happening. I have read about custom filters and how filters work but it does not solve my issue.



    The code is as follows:



    import cv2
    
import sys
    
import numpy as np 
    

    
im_name = sys.argv[1]#give path to the image
    

    
im = cv2.imread(im_name, 0)
    

    
im_copy = im.copy()
    

    
#create custom filter
    

    
my_filter = np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]])
    

    
dst = cv2.filter2D(im, -1, my_filter)
    

    
cv2.imshow("test", im)
    
cv2.imshow("check", dst)
    
cv2.waitKey(0)
    
cv2.destroyAllWindows()


    Picture 1 and 2 show deviant result, rest of the pictures show expected
    results






    python opencv image-processing imagefilter







    share|improve this question



























      1












      1








      1








      I am experimenting with custom kernels to extract border lines in given images.



      The filter I am using is np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]]).
      For the given set of images which are of a similar nature, the code generates results where sometimes the hatchings are present whereas absent for other images.



      I am not able to figure out why this is happening. I have read about custom filters and how filters work but it does not solve my issue.



      The code is as follows:



      import cv2
      
import sys
      
import numpy as np 
      

      
im_name = sys.argv[1]#give path to the image
      

      
im = cv2.imread(im_name, 0)
      

      
im_copy = im.copy()
      

      
#create custom filter
      

      
my_filter = np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]])
      

      
dst = cv2.filter2D(im, -1, my_filter)
      

      
cv2.imshow("test", im)
      
cv2.imshow("check", dst)
      
cv2.waitKey(0)
      
cv2.destroyAllWindows()


      Picture 1 and 2 show deviant result, rest of the pictures show expected
      results






      python opencv image-processing imagefilter







      share|improve this question
















      I am experimenting with custom kernels to extract border lines in given images.



      The filter I am using is np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]]).
      For the given set of images which are of a similar nature, the code generates results where sometimes the hatchings are present whereas absent for other images.



      I am not able to figure out why this is happening. I have read about custom filters and how filters work but it does not solve my issue.



      The code is as follows:



      import cv2
      
import sys
      
import numpy as np 
      

      
im_name = sys.argv[1]#give path to the image
      

      
im = cv2.imread(im_name, 0)
      

      
im_copy = im.copy()
      

      
#create custom filter
      

      
my_filter = np.array([[-2, -1, 0], [-1, 10, 1], [0, 1, 2]])
      

      
dst = cv2.filter2D(im, -1, my_filter)
      

      
cv2.imshow("test", im)
      
cv2.imshow("check", dst)
      
cv2.waitKey(0)
      
cv2.destroyAllWindows()


      Picture 1 and 2 show deviant result, rest of the pictures show expected
      results






      python opencv image-processing imagefilter




      python opencv image-processing imagefilter






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Jan 4 at 4:57







      BATspock

















      asked Jan 3 at 8:23









      BATspockBATspock

      829




      829
























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