MATLAB 的 Canny 滤波器的 Python 实现

Question

在 MATLAB 中调用以下函数将 Canny 滤波器应用于图像:

edges = edge(image, 'Canny');

我知道有两个 Python 函数实现了 Canny 过滤器:

import cv2

edges = cv2.Canny(image)

和

from skimage import feature

edges = feature.canny(image)

但是，这些 Python 函数都不能像 MATLAB 那样计算过滤器的高阈值和低阈值。根据this neuroimaging paper ,

. . . the default MATLAB algorithm [generates] the two thresholds such that the high threshold is calculated to be the lowest value at which no more than 30% of the pixels are detected as edges, and the low threshold is defined as 40% of the high threshold.

是否有可以执行此操作的 Python 实现？

Answer 1

您应该首先将 Canny 参数传递给 canny()，然后在您的 Python 代码中运行它

im: 图片名称
下限:
上限:

import cv2
import matplotlib.pyplot as plt

img = cv2.imread('lena.png')
edges = cv2.Canny(img,....,....,L2gradient=False/True)

plt.imshow(edges,cmap='gray')
plt.show()