如何在 Python 中使用分水岭算法分离图像

Question

如何使用Python中的分水岭算法在图像分割后在多张图像中分离单个图像附加图像由4张图像组成，我们需要从中应用图像分割并将单个图像从这4张图像中分离出来

Answer 1

我们会先把它洪水填满

import cv2;
import numpy as np;

# Read image
im_in = cv2.imread("2SNAT.jpg", cv2.IMREAD_GRAYSCALE);

# Threshold.
# Set values equal to or above 220 to 0.
# Set values below 220 to 255.

th, im_th = cv2.threshold(im_in, 220, 255, cv2.THRESH_BINARY_INV);

# Copy the thresholded image.
im_floodfill = im_th.copy()

# Mask used to flood filling.
# Notice the size needs to be 2 pixels than the image.
h, w = im_th.shape[:2]
mask = np.zeros((h+2, w+2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(im_floodfill, mask, (0,0), 255);

# Invert floodfilled image
im_floodfill_inv = cv2.bitwise_not(im_floodfill)

# Combine the two images to get the foreground.
im_out = im_th | im_floodfill_inv

然后找到轮廓并裁剪掉

im, contours, hierarchy = cv2.findContours(im_out.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

final_contours = []
for contour in contours:
    area = cv2.contourArea(contour)
    if area > 1000:
        final_contours.append(contour)

裁剪步骤，也在原始图像上绘制矩形

counter = 0        
for c in final_contours:
    counter = counter + 1
# for c in [final_contours[0]]:
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.01 * peri, True)
    x,y,w,h = cv2.boundingRect(approx)
    print(x, y, w, h)
    aspect_ratio = w / float(h)

    if (aspect_ratio >= 0.8 and aspect_ratio <= 4):
        cv2.rectangle(im_in,(x,y),(x+w,y+h),(0,255,0),2)
        cv2.imwrite('splitted_{}.jpg'.format(counter), im_in[y:y+h, x:x+w])
cv2.imwrite('rectangled_split.jpg', im_in)