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？
最佳答案
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
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:
关于python - 改进 Canny 边缘检测，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/61643039/