I try to replace the turquoise part (words) from the image with white background to have a clear source for tesseract-ocr. The picture is loaded ok, image mask is created ok. My question is how to calculate (bidwise_and/or/xor) the right way, to have the turquoise part replaced with white. My code replace best case the turquoise part with black. Any idea is welcome and thank you for looking into. import cv2 import numpy as np # Read image image = cv2.imread('pic1.png') # Show Image cv2.imshow('Pic1', image) cv2.waitKey(0) cv2.destroyAllWindows() # Create white image whtimg = np.zeros([image.shape[0],image.shape[1],image.shape[2]],dtype=np.uint8) whtimg.fill(255) # Convert to HSV hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) whtimg = cv2.cvtColor(whtimg, cv2.COLOR_BGR2HSV) # Color Range - turquoise (color pick HSV: 165/77/87) lower_color = np.array([int(165/360*255-100), int(77/100*255*0.1), int(87/100*255-10)]) upper_color = np.array([int(165/360*255+100), int(77/100*255*3.0) , int(87/100*255+10)]) # Create mask to only select white mask1 = cv2.inRange(hsv, lower_color, upper_color) # mask1 = 255 - mask1 # invert mask # Show Mask cv2.imshow('Mask', mask1) cv2.waitKey(0) cv2.destroyAllWindows() # replace with white res = cv2.bitwise_or(hsv,whtimg,mask=mask1) # or bitwise_and, bitwise_xor # Convert to BGR res = cv2.cvtColor(res, cv2.COLOR_HSV2BGR) # Show Result cv2.imshow('Result', res) cv2.waitKey(0) cv2.destroyAllWindows() Continue reading...
