如何使用OTSU阈值取阈值仅图像的一部分？

Question

I'm using OTSU threshold on a dilated and eroded image as shown below:

k = np.ones((5,5),np.float32)/1
        d = cv2.dilate(self.img, k, iterations=10)
        e = cv2.erode(d, k, iterations=10)
        self.thresh = cv2.threshold(e, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

This is the eroded and dilated image, and the one that gets thresholded:

I only want the circular bright region in the middle to be obtained from thresholding, but instead I'm getting this result:

How do I go about thresholding such that I only get the circular region in the middle, which also seems like the brightest (visually) part of the image?

Note: To avoid playing around with different values, I want to stick to OTSU thresholding, but I'm open to ideas.

Answer 1

You can use Dilate and Erode filters to this image, but in another order: Erode first and then Dialte. It will suppress bright areas from upper side of the image and threshold method will provide better result

Answer 2

You can try a gradient based approach. Below I've used the morphological gradient. I apply Otsu thresholding to this gradient image, followed by a similar amount of morphological closing (10 iterations), then take the morphological gradient of the resulting image.

Now the regions are easy to detect. You can filter the circular region from the contours, for example, using an area based approach: using bounding box dimensions of the contour, you can get an estimate of the radius, then compare the calculated area to the contour area.

Don't know how generic this approach would be for your collection.

Gradient image: intensity values scaled for visualization

Binarized gradient image

Closed image

Gradient

im = cv2.imread('LDxOj.jpg', 0)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
morph = cv2.morphologyEx(im, cv2.MORPH_GRADIENT, kernel)
_, bw = cv2.threshold(morph, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
morph2 = cv2.morphologyEx(bw, cv2.MORPH_CLOSE, kernel, anchor = (-1, -1), iterations = 10)
morph3 = cv2.morphologyEx(morph2, cv2.MORPH_GRADIENT, kernel)