OpenCV官方教程中文版 —— Hough 圆环变换-Toy模板网

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前言

目标

• 学习使用霍夫变换在图像中找圆形（环）

• 学习函数：cv2.HoughCircles()

Hough 圆环变换

OpenCV官方教程中文版 —— Hough 圆环变换,opencv,人工智能,计算机视觉
opencv_logo.png：

# -*- coding: utf-8 -*-
import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('opencv_logo.png', 0)
img = cv2.medianBlur(img, 5)
cimg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
circles = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT, 1, 20,
                           param1=50, param2=40, minRadius=0, maxRadius=0)
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
    # draw the outer circle
    cv2.circle(cimg, (i[0], i[1]), i[2], (0, 255, 0), 2)
    # draw the center of the circle
    cv2.circle(cimg, (i[0], i[1]), 2, (0, 0, 255), 3)

plt.figure()
plt.subplot(121)
plt.imshow(img, cmap='gray')
plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
plt.subplot(122)
plt.imshow(cimg, cmap='gray')
plt.xticks([]), plt.yticks([])  # to hide tick values on X and Y axis
plt.show()
# Python: cv2.HoughCircles(image, method, dp, minDist, circles, param1, param2, minRadius, maxRadius)
# Parameters:
# image – 8-bit, single-channel, grayscale input image.
# 返回结果为 Output vector of found circles. Each vector is encoded as a
# 3-element floating-point vector (x, y, radius) .
# circle_storage – In C function this is a memory storage that will contain
# the output sequence of found circles.
# method – Detection method to use. Currently, the only implemented method is
# CV_HOUGH_GRADIENT , which is basically 21HT , described in [Yuen90].
# dp – Inverse ratio of the accumulator resolution to the image resolution.
# For example, if dp=1 , the accumulator has the same resolution as the input image.
# If dp=2 , the accumulator has half as big width and height.
# minDist – Minimum distance between the centers of the detected circles.
# If the parameter is too small, multiple neighbor circles may be falsely
# detected in addition to a true one. If it is too large, some circles may be missed.
# param1 – First method-specific parameter. In case of CV_HOUGH_GRADIENT ,
# it is the higher threshold of the two passed to the Canny() edge detector
# (the lower one is twice smaller).
# param2 – Second method-specific parameter. In case of CV_HOUGH_GRADIENT ,
# it is the accumulator threshold for the circle centers at the detection stage.
# The smaller it is, the more false circles may be detected. Circles,
# corresponding to the larger accumulator values, will be returned first.
# minRadius – Minimum circle radius.
# maxRadius – Maximum circle radius.