如何在Python中使用OpenCV裁剪图像的黑色背景？

Question

So I have an image processing task at hand which requires me to crop a certain portion of an image. I have no prior experience of OpenCV. I would like to know of a certain approach where I should be headed.

Sample Input Image:

Sample Output Image:

What I initially thought was to convert the image to a bitmap and remove pixels that are below or above a certain threshold. Since I am free to use OpenCV and Python, I would like to know of any automated algorithm that does so and if not, what should be the right approach for such a problem. Thank you.

Answer 1

Applying a simple threshold should get rid of the background, provided it's always darker than the foreground. If you use the Otsu thresholding algorithm, it should choose a good partition for you. Using your example as input, this gives:

Next you could compute the bounding box to select the region of the foreground. Provided the background is distinct enough and there are no holes, this gives you the resulting rect:

[619 x 96 from (0, 113)]

You can then use this rect to crop the original, to produce the desired result:

I wrote the code to solve this in C++. A rough translation into Python would look something like this:

import cv2 as cv

img = cv.imread(sys.argv[1])

grayscale = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

thresholded = cv.threshold(grayscale, 0, 255, cv.THRESH_OTSU)

imwrite("otsu.png", thresholded)

bbox = cv.boundingRect(thresholded)

x, y, w, h = bbox

print(bbox)

foreground = img[y:y+h, x:x+w]

imwrite("foreground.png", foreground)

This method is fast and simple. If you find you have some white holes in your background which enlarge the bounding box, try applying an erosion operator.

FWIW I very much doubt you would get results like this as predictably or reliably using NNs.

Answer 2

The thresholding seems like a good approach. An overkill would be a neural network but you probably don't have enough data to train (:D) anyways check out this link.

you should be able to do something like:

import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt
img = cv.imread('img.png')
gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
ret, thresh = cv.threshold(gray,0,255,cv.THRESH_BINARY_INV+cv.THRESH_OTSU

Answer 3

NN would be a overkill! You can do edge detection and get the extreme horizontal lines as boundaries. Then crop only the roi within these two lines.