如何用opencv获取扫描图像的边缘坐标？

Question

我有一张图片，这是扫描硬拷贝文件的结果：

如你所见，每个角上都有一个空格和四个矩形。

我需要找到矩形每个边缘的坐标，所以我可以裁剪它。

我使用opencv，用opencv怎么做？

如何使用opencv获取扫描图像的边缘坐标？

这是我想要实现的结果

如果我有那个坐标，那么我可以用我从网上获得的代码来裁剪它：

# USAGE
# python transform_example.py --image images/example_01.png --coords "[(73, 239), (356, 117), (475, 265), (187, 443)]"
# python transform_example.py --image images/example_02.png --coords "[(101, 185), (393, 151), (479, 323), (187, 441)]"
# python transform_example.py --image images/example_03.png --coords "[(63, 242), (291, 110), (361, 252), (78, 386)]"

# import the necessary packages
from pyimagesearch.transform import four_point_transform
import numpy as np
import argparse
import cv2

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", help = "path to the image file")
ap.add_argument("-c", "--coords",
    help = "comma seperated list of source points")
args = vars(ap.parse_args())

# load the image and grab the source coordinates (i.e. the list of
# of (x, y) points)
# NOTE: using the 'eval' function is bad form, but for this example
# let's just roll with it -- in future posts I'll show you how to
# automatically determine the coordinates without pre-supplying them
image = cv2.imread(args["image"])
pts = np.array(eval(args["coords"]), dtype = "float32")

# apply the four point tranform to obtain a "birds eye view" of
# the image
warped = four_point_transform(image, pts)

# show the original and warped images
cv2.imshow("Original", image)
cv2.imshow("Warped", warped)
cv2.waitKey(0)

Answer 1

使用此代码，您可以根据需要直接裁剪图像。

import cv2
import numpy as np

new_image = cv2.imread('test.jpg', 0)

rows, cols = new_image.shape
vertical_histrogram = np.zeros(cols)
horizontal_histrogram = np.zeros(rows)
for col in range(cols):  # create vertical histrogram for each lines
    for row in range(rows):
        if new_image[row, col] == 0:
            vertical_histrogram[col] += 1

for row in range(rows):  # create horizontal histrogram for each lines
    for col in range(cols):
        if new_image[row, col] == 0:
            horizontal_histrogram[row] += 1

for row in range(rows - 1, -1, -1):
    if horizontal_histrogram[row] > 0:
        top = row;
        break

for row in range(0, rows):
    if horizontal_histrogram[row] > 0:
        bottom = row;
        break

for col in range(0, cols):
    if vertical_histrogram[col] > 0:
        left = col;
        break

for col in range(cols - 1, -1, -1):
    if vertical_histrogram[col] > 0:
        right = col;
        break

new_image = new_image[bottom :top , left :right ]

cv2.imwrite('output.jpg', new_image)