Python OpenCV - cv.inRange() "sensitivity"?

Question

img = cv2.imread('/home/user/Documents/workspace/ImageProcessing/img.JPG');
image = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

#red, blue, yellow, and gray
boundaries = [
([17, 15, 100], [50, 56, 200]),
([86, 31, 4], [220, 88, 50]),
([25, 146, 190], [62, 174, 250]),
([103, 86, 65], [145, 133, 128])]


for i, (lower, upper) in enumerate(boundaries):

    lower = np.array(lower, dtype="uint8")
    upper = np.array(upper, dtype="uint8")

    mask = cv2.inRange(image, lower, upper)
    output = cv2.bitwise_and(image, image, mask=mask)

    cv2.imwrite(str(i) + 'image.jpg', output)

I am trying to isolate the colors red, blue, yellow and gray from an image (seperately). It is working so far, however the "sensitivity" is way to low. The algorithm is missing some smaller color spots. Is there a way to calibrate this? Thanks!

edit: input image

output

It would help us to understand the problem better if you can also add your input/output images. — ilke444
– ilke444, Commented Jan 16, 2017 at 20:25

ilke444 · Accepted Answer · 2017-01-16 21:42:00Z

4

inRange function does not have a built-in sensitivity. It only compares the values. inRange(x,10,20) will only give you {10,11,...,20}.

One way to overcome this is to introduce your own sensitivity measure.

s = 5 # for example sensitivity=5/256 color values in range [0,255]

for i, (lower, upper) in enumerate(boundaries):

    lower = np.array([color-s if color-s>-1 else 0 for color in lower], dtype="uint8")
    upper = np.array([color+s if color+s<256 else 255 for color in upper], dtype="uint8")

    mask = cv2.inRange(image, lower, upper)
    output = cv2.bitwise_and(image, image, mask=mask)

    cv2.imwrite(str(i) + 'image.jpg', output)

Or you can smooth the image beforehand to get rid of such noisy pixels. That will make the pixel values closer to each other, so that the ones out of the boundary might get values closer to the range.

edited Jan 16, 2017 at 21:42

answered Jan 16, 2017 at 21:08

ilke444

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3 Comments

cmplx96 Over a year ago

but i tried everything from sensitivity 0.01 to 200 and it doesn't get any better

cmplx96 Over a year ago

everything after sensitivity = 20 is black

ilke444 Over a year ago

Yes, because your boundaries go beyond 0 and/or 255 if you have high sensitivity. You can check if sensitivity is distorting the boundaries beyond the actual possible pixel values by adding conditionals. I am updating the code for that.

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