I have a bunch of image I would like to uniformise by removing black borders. Usually I use the Trim function of Imagemagick with the fuzz parameters but in the case the image have some watermark the result is not here.
Actually I'm making some tests with opencv and morphological transform to try to identify watermark and image and then select the bigger element but I'm really new with opencv and I struggle.
Watermark can be everywhere, from bottom left to upper right.
I would prefer a Python code but using some app like Imagemagick or similar is welcome.
Actually using opencv only I get this result:
import copy
import cv2
from matplotlib import pyplot as plt
IMG_IN = '/data/black_borders/island.jpg'
# keep a copy of original image
original = cv2.imread(IMG_IN)
# Read the image, convert it into grayscale, and make in binary image for threshold value of 1.
img = cv2.imread(IMG_IN,0)
# use binary threshold, all pixel that are beyond 3 are made white
_, thresh_original = cv2.threshold(img, 3, 255, cv2.THRESH_BINARY)
# Now find contours in it.
thresh = copy.copy(thresh_original)
contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
# get contours with highest height
lst_contours = []
for cnt in contours:
ctr = cv2.boundingRect(cnt)
lst_contours.append(ctr)
x,y,w,h = sorted(lst_contours, key=lambda coef: coef[3])[-1]
# draw contours
ctr = copy.copy(original)
cv2.rectangle(ctr, (x,y),(x+w,y+h),(0,255,0),2)
# display results with matplotlib
# original
original = original[:,:,::-1] # flip color for maptolib display
plt.subplot(221), plt.imshow(original)
plt.title('Original Image'), plt.xticks([]),plt.yticks([])
# Threshold
plt.subplot(222), plt.imshow(thresh_original, cmap='gray')
plt.title('threshold binary'), plt.xticks([]),plt.yticks([])
# selected area for future crop
ctr = ctr[:,:,::-1] # flip color for maptolib display
plt.subplot(223), plt.imshow(ctr)
plt.title('Selected area'), plt.xticks([]),plt.yticks([])
plt.show()
results: