使用python检测边缘后如何将图像裁剪成碎片

Question

我正在研究一个残缺的文档重建项目。首先，我尝试检测包含撕裂的文档碎片的图像边缘，然后尝试使用示例代码通过检测到的边缘将图像裁剪为碎片，

import cv2
import numpy as np
img = cv2.imread("test.png")
img = cv2.imread("d:/test.jpeg")

cv2.imshow('Original Image',img)

new_img = cv2.Canny(img, 0, 505)
cv2.imshow('new image', new_img)

blurred = cv2.blur(new_img, (3,3))
canny = cv2.Canny(blurred, 50, 200)

## find the non-zero min-max coords of canny
pts = np.argwhere(canny>0)
y1,x1 = pts.min(axis=0)
y2,x2 = pts.max(axis=0)

## crop the region
cropped = new_img[y1:y2, x1:x2]
cv2.imwrite("cropped.png", cropped)

tagged = cv2.rectangle(new_img.copy(), (x1,y1), (x2,y2), (0,255,0), 3, cv2.LINE_AA)
cv2.imshow("tagged", tagged)
cv2.waitKey()

我的输入图像是

运行上面的代码后，我得到类似的输出

有人可以帮助我裁剪破损的文档并将其分配给变量

Answer 1

我的工作流程的开始与您的相似。第一步：模糊图像。

blurred = cv2.GaussianBlur(gray, (5, 5), 0) # Blur

第二步：获取精明的图片...

canny = cv2.Canny(blurred, 30, 150) # Canny

第三步：在canny图像上绘制轮廓。这样就关闭了碎片。

# Find contours
_, contours, _ = cv2.findContours(canny,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
# Draw contours on canny (this connects the contours
cv2.drawContours(canny, contours, -1, 255, 2)
canny = 255 - canny

第四步：充水（充水区为灰色）

# Get mask for floodfill
h, w = thresh.shape[:2]
mask = np.zeros((h+2, w+2), np.uint8)
# Floodfill from point (0, 0)
cv2.floodFill(thresh, mask, (0,0), 123);

第五步：摆脱很小的轮廓和很大的轮廓

# Create a blank image to draw on
res = np.zeros_like(src_img)
# Create a list for unconnected contours
unconnectedContours = []
for contour in contours:
    area = cv2.contourArea(contour)
    # If the contour is not really small, or really big
    if area > 123 and area < 760000:
        cv2.drawContours(res, [contour], 0, (255,255,255), cv2.FILLED)
        unconnectedContours.append(contour)

最后，将片段分割后，即可将其嵌套。