python - 改进 Canny 边缘检测

Question

当我在图纸上运行 cv.Canny 边缘检测器时，它会检测到数百个密集填充在阴影区域中的小边缘。我怎样才能让它停止这样做，同时仍然检测到眼睛和 Nose 等较轻的特征？我也试过模糊。

这是一个示例，与 online photo tool 相比.

Original image .
Output of online tool .
My python program

这是我的代码:

def outline(image, sigma = 5):
    image = cv.GaussianBlur(image, (11, 11), sigma)
    ratio = 2
    lower = .37 * 255
    upper = lower * ratio
    outlined = cv.Canny(image, lower, upper)

    return outlined

我该如何改进它？

Answer 1

这是在 Python/OpenCV 中执行此操作的一种方法。

形态边缘输出是蒙版和扩张蒙版之间的绝对差异

阅读输入

转为灰色

阈值(作为掩码)

扩大阈值图像

计算绝对差值

将其极性反转为边缘图像

保存结果

输入:

import cv2
import numpy as np

# read image
img = cv2.imread("cartoon.jpg")

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold
thresh = cv2.threshold(gray, 180, 255, cv2.THRESH_BINARY)[1]

# morphology edgeout = dilated_mask - mask
# morphology dilate
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5))
dilate = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel)

# get absolute difference between dilate and thresh
diff = cv2.absdiff(dilate, thresh)

# invert
edges = 255 - diff

# write result to disk
cv2.imwrite("cartoon_thresh.jpg", thresh)
cv2.imwrite("cartoon_dilate.jpg", dilate)
cv2.imwrite("cartoon_diff.jpg", diff)
cv2.imwrite("cartoon_edges.jpg", edges)

# display it
cv2.imshow("thresh", thresh)
cv2.imshow("dilate", dilate)
cv2.imshow("diff", diff)
cv2.imshow("edges", edges)
cv2.waitKey(0)

阈值图像:



扩张阈值图像:



差异图像:



边缘图像: