I defined annulus ROI selection function and i would like to find contours in this area. But contours pixel values are neighbors to the zero and out of masked areas equal to zero. Therefore contours couldn't be catch thresholded image.
How can i define annulus ROI or find the contours if function is ok
def annulusROI(img, center, innerR, outerR):
"""
img: Image matrix
center: ROI center point [px] (x,y tuple)
innerR: ROI inner radius [px]
outerR: ROI outer radius [px]
mode: Mask selection for white (255, 255, 255), for black (0, 0, 0) [BGR tuple]
return roi matrix and left-top start point coordinate
"""
outRoi, rectC = rectangleROI(img, center, outerR*2, outerR*2)
mask1 = np.zeros_like(outRoi)
mask2 = np.zeros_like(outRoi)
mask1 = cv2.circle(mask1, (round(outerR),round(outerR)), innerR, (255, 255, 255), -1)
mask2 = cv2.circle(mask2, (round(outerR),round(outerR)), outerR, (255, 255, 255), -1)
mask = cv2.subtract(mask2, mask1)
roi = cv2.bitwise_and(outRoi, mask)
return roi, (center[0]-outerR, center[1]-innerR)
After thresholding and before getting the contours you can separate the region of interest from the outer area. Or even better you can cut your region of interest after thresholding, not before. Finally you can filter out the releavant contours by area size.
import cv2
# get image threshold
img = cv2.imread("img.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_, thresh = cv2.threshold(gray, 64, 255, 0)
# separate annulus from outer area
h, w, _ = img.shape
center = (round(w / 2), round(h / 2))
innerR = 246
outerR = 306
cv2.circle(thresh, center, innerR, 255)
cv2.circle(thresh, center, outerR, 255)
# filter contours by relevant area size
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cc = [c for c in contours if 100 < cv2.contourArea(c) < 5000]
cv2.drawContours(img, cc, -1, (0, 0, 255))
cv2.imwrite("out.png", img)
Result: