这是在 Python/OpenCV 中执行此操作的一种方法。
- 读取输入
- 转换为灰色
- 阈值
- 将底部两排白排变黑
- 查找所有白色像素在图像中的位置
- 获取这些像素的边界
- 在边界处裁剪图像
- 保存结果
输入:
import cv2
import numpy as np
# load image as grayscale
img = cv2.imread('xray_chest.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
hh, ww = thresh.shape
# make bottom 2 rows black where they are white the full width of the image
thresh[hh-3:hh, 0:ww] = 0
# get bounds of white pixels
white = np.where(thresh==255)
xmin, ymin, xmax, ymax = np.min(white[1]), np.min(white[0]), np.max(white[1]), np.max(white[0])
print(xmin,xmax,ymin,ymax)
# crop the image at the bounds adding back the two blackened rows at the bottom
crop = img[ymin:ymax+3, xmin:xmax]
# save resulting masked image
cv2.imwrite('xray_chest_thresh.jpg', thresh)
cv2.imwrite('xray_chest_crop.jpg', crop)
# display result
cv2.imshow("thresh", thresh)
cv2.imshow("crop", crop)
cv2.waitKey(0)
cv2.destroyAllWindows()
底部两行变黑的阈值图像:
裁剪输入:
另一种方法是从阈值图像中获取白色区域的外部轮廓。获取轮廓的边界。然后裁剪到这些边界。