How can I crop the image so that only the text is included in the image using OpenCV?
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问题:
回答1:
Approach
- Dilating the image in in the vertical and horizontal direction
- Finding the bounding rectangle
- Cropping the image
Code
# reading the input image in grayscale image image = cv2.imread('image2.png',cv2.IMREAD_GRAYSCALE) image /= 255 if image is None: print 'Can not find/read the image data' # Defining ver and hor kernel N = 5 kernel = np.zeros((N,N), dtype=np.uint8) kernel[2,:] = 1 dilated_image = cv2.dilate(image, kernel, iterations=2) kernel = np.zeros((N,N), dtype=np.uint8) kernel[:,2] = 1 dilated_image = cv2.dilate(dilated_image, kernel, iterations=2) image *= 255 # finding contours in the dilated image contours,a = cv2.findContours(dilated_image,cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # finding bounding rectangle using contours data points rect = cv2.boundingRect(contours[0]) pt1 = (rect[0],rect[1]) pt2 = (rect[0]+rect[2],rect[1]+rect[3]) cv2.rectangle(image,pt1,pt2,(100,100,100),thickness=2) # extracting the rectangle text = image[rect[1]:rect[1]+rect[3],rect[0]:rect[0]+rect[2]] plt.subplot(1,2,1), plt.imshow(image,'gray') plt.subplot(1,2,2), plt.imshow(text,'gray') plt.show() Output
回答2:
Assuming that you have pixel information you could draw a convex hull around the white text. Once that you have the hull, you can get the lowest and highest x and y coordinate and use those as your rectangle coordinates so that you could crop the rest of the image.
An example of how to obtain a convex hull in Open_CV (C++) is available here.
It might be a good idea to apply some filter on the image (maybe use the erosion filter) so that you can remove any false positives.
回答3:
Take projection of white pixels in x-direction and y-direction. The lowest and highest values in x and y direction are bound of your rectangle's y and x co-ordinates respectively. This solution is for simple situations with low processing and in-place calculation.