I'm trying to calculate the size of a wound. For that, I am capturing an image with a coin that serves as a basis to know the scale of the image and calculate the size of the region of the wound. I'm using the watershed algorithm for segmentation, but the currency is being covered by the tracking. Can someone help me get around the coin and detach it from the image along with the wound area.
Input
Exit:
import numpy as np
import cv2
# Read the image and perfrom an OTSU threshold
img = cv2.imread('feridatest.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# Remove hair with opening
kernel = np.ones((6,6),np.uint8)
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)
# Combine surrounding noise with ROI
kernel = np.ones((6,6),np.uint8)
dilate = cv2.dilate(opening,kernel,iterations=3)
# Blur the image for smoother ROI
blur = cv2.blur(dilate,(5,5))
# Perform another OTSU threshold and search for biggest contour
ret, thresh = cv2.threshold(blur,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE)
cnt = max(contours, key=cv2.contourArea)
# Create a new mask for the result image
h, w = img.shape[:2]
mask = np.zeros((h, w), np.uint8)
# Draw the contour on the new mask and perform the bitwise operation
cv2.drawContours(mask, [cnt],-1, 255, -1)
res = cv2.bitwise_and(img, img, mask=mask)
# Display the result
cv2.imshow('img', res)
cv2.waitKey(0)
cv2.destroyAllWindows()
Input
[![enter image description here][1]][1]
Exit:
[![enter image description here][2]][2]