Doing an adaptive thresholding to a grayscale image

asked 2016-12-25 04:27:09 -0600

Azy
1

I have a png image which is in grayscale 'test.png'. I need to do an adaptive thresholding to this image. I am using opencv2.

image = cv2.imread('test_big.png')
im = cv2.adaptiveThreshold(image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)

I am not able to do thresholding since the image is not in grayscale. So I tried to read the image as grayscale

image = cv2.imread('test_big.png',1)

Now I can do the thresholding but the output will be a blue and red image instead of black and white. Can anyone help Plsss

answered 2016-12-25 04:43:15 -0600

berak
32993 ●7 ●81 ●312

please use:

image = cv2.imread('test_big.png', cv2.IMREAD_GRAYSCALE)

(and both cv2.imread('test_big.png') and cv2.imread('test_big.png', 1) do the same thing - load an image in color)

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I am getting a blue illuminated image when I use this. The problem is the source image is already in grayscale (black & white). So Is there any hack to solve this.

Azy ( 2016-12-25 05:28:28 -0600 )edit

the source image is already in grayscale

even if so, if you use '1' for the flag (or none at all), imread will force it into a 3 channel image.

berak ( 2016-12-25 05:39:18 -0600 )edit

Ok thanks! Is there any way to solve my problem? pls

Azy ( 2016-12-25 05:42:04 -0600 )edit

cv2.IMREAD_GRAYSCALE = 0 just use berak solution

image = cv2.imread('test_big.png', cv2.IMREAD_GRAYSCALE)

image = cv2.imread('test_big.png', 0)

essamzaky ( 2016-12-25 07:16:40 -0600 )edit

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Doing an adaptive thresholding to a grayscale image

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