Python - OpenCV - Binarize To Isolate Object Which is Same Color as Background











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I need to isolate the cardboard target in the image below and binarize it, so that the target is white and the background black. Normally, this is not a problem, but the background is almost the exact same color as the target.



Attempts:



# LOAD IMAGE

img_filepath = 'real_6.png'

img = cv2.imread( img_filepath )

rgb_img = img[:,:,::-1]

plt.imshow( rgb_img )

plt.title('ORIGINAL')

plt.show()



img_gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )



# SMOOTH

blur_kernel = np.ones((5,5),np.float32)/30

blur_img = cv2.filter2D( rgb_img, -1, blur_kernel )



# THRESHOLD 

lower_color_rng = np.array( [100,50,100] )

upper_color_rng = np.array( [255,255,255] )

target_keyholes_img = cv2.inRange( blur_img, lower_color_rng, upper_color_rng )

plt.imshow( target_keyholes_img, cmap='gray' )

plt.title( 'THRESHOLD' )

plt.show()


Attempted Image Extraction



How can I use OpenCV in Python 3 to binarize this image?



Original Image






python-3.x image opencv signal-processing







share|improve this question






















  • you can try grabcut opencv algorithm for foreground extraction
    – Devashish Prasad
    Nov 5 at 7:44










  • If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
    – T A
    Nov 5 at 16:05

















up vote
1
down vote

favorite












I need to isolate the cardboard target in the image below and binarize it, so that the target is white and the background black. Normally, this is not a problem, but the background is almost the exact same color as the target.



Attempts:



# LOAD IMAGE

img_filepath = 'real_6.png'

img = cv2.imread( img_filepath )

rgb_img = img[:,:,::-1]

plt.imshow( rgb_img )

plt.title('ORIGINAL')

plt.show()



img_gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )



# SMOOTH

blur_kernel = np.ones((5,5),np.float32)/30

blur_img = cv2.filter2D( rgb_img, -1, blur_kernel )



# THRESHOLD 

lower_color_rng = np.array( [100,50,100] )

upper_color_rng = np.array( [255,255,255] )

target_keyholes_img = cv2.inRange( blur_img, lower_color_rng, upper_color_rng )

plt.imshow( target_keyholes_img, cmap='gray' )

plt.title( 'THRESHOLD' )

plt.show()


Attempted Image Extraction



How can I use OpenCV in Python 3 to binarize this image?



Original Image






python-3.x image opencv signal-processing







share|improve this question






















  • you can try grabcut opencv algorithm for foreground extraction
    – Devashish Prasad
    Nov 5 at 7:44










  • If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
    – T A
    Nov 5 at 16:05















up vote
1
down vote

favorite









up vote
1
down vote

favorite











I need to isolate the cardboard target in the image below and binarize it, so that the target is white and the background black. Normally, this is not a problem, but the background is almost the exact same color as the target.



Attempts:



# LOAD IMAGE

img_filepath = 'real_6.png'

img = cv2.imread( img_filepath )

rgb_img = img[:,:,::-1]

plt.imshow( rgb_img )

plt.title('ORIGINAL')

plt.show()



img_gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )



# SMOOTH

blur_kernel = np.ones((5,5),np.float32)/30

blur_img = cv2.filter2D( rgb_img, -1, blur_kernel )



# THRESHOLD 

lower_color_rng = np.array( [100,50,100] )

upper_color_rng = np.array( [255,255,255] )

target_keyholes_img = cv2.inRange( blur_img, lower_color_rng, upper_color_rng )

plt.imshow( target_keyholes_img, cmap='gray' )

plt.title( 'THRESHOLD' )

plt.show()


Attempted Image Extraction



How can I use OpenCV in Python 3 to binarize this image?



Original Image






python-3.x image opencv signal-processing







share|improve this question













I need to isolate the cardboard target in the image below and binarize it, so that the target is white and the background black. Normally, this is not a problem, but the background is almost the exact same color as the target.



Attempts:



# LOAD IMAGE

img_filepath = 'real_6.png'

img = cv2.imread( img_filepath )

rgb_img = img[:,:,::-1]

plt.imshow( rgb_img )

plt.title('ORIGINAL')

plt.show()



img_gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )



# SMOOTH

blur_kernel = np.ones((5,5),np.float32)/30

blur_img = cv2.filter2D( rgb_img, -1, blur_kernel )



# THRESHOLD 

lower_color_rng = np.array( [100,50,100] )

upper_color_rng = np.array( [255,255,255] )

target_keyholes_img = cv2.inRange( blur_img, lower_color_rng, upper_color_rng )

plt.imshow( target_keyholes_img, cmap='gray' )

plt.title( 'THRESHOLD' )

plt.show()


Attempted Image Extraction



How can I use OpenCV in Python 3 to binarize this image?



Original Image






python-3.x image opencv signal-processing




python-3.x image opencv signal-processing






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 5 at 1:49









Alexander Falinsky

134




134












  • you can try grabcut opencv algorithm for foreground extraction
    – Devashish Prasad
    Nov 5 at 7:44










  • If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
    – T A
    Nov 5 at 16:05




















  • you can try grabcut opencv algorithm for foreground extraction
    – Devashish Prasad
    Nov 5 at 7:44










  • If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
    – T A
    Nov 5 at 16:05


















you can try grabcut opencv algorithm for foreground extraction
– Devashish Prasad
Nov 5 at 7:44




you can try grabcut opencv algorithm for foreground extraction
– Devashish Prasad
Nov 5 at 7:44












If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
– T A
Nov 5 at 16:05






If the color of your object is slightly different (as in the example image you provided), you can try to find the correct threshold that divides it from the background. If the color is in fact the same as your background, there is no way to isolate it.
– T A
Nov 5 at 16:05



















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