Question

我有多个圆圈的图像，圆圈内有热点区域，强度高（高像素值），而区域有冷点（低像素值）。我想用Python中的OpenCV计算每个圆的加权质心。我正在使用这段代码：

im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
     # calculate moments for each contour
     M = cv2.moments(c)

     # calculate x,y coordinate of center
     if M["m00"] != 0:
         cX = int(M["m10"] / M["m00"])
         cY = int(M["m01"] / M["m00"])
      else:
         cX, cY = 0, 0

好，因此此代码仅获取二进制图像，提取所有圆并找到每个圆的轮廓。

问题是我需要找到RGB /灰度图像（考虑像素强度）而不是二进制图像的加权质心。我怎样才能做到这一点？

谢谢！

Answer 1

这是您问题的一种python伪代码解决方案。该代码旨在计算质心的加权中心。图像的强度级别在计算中用作权重。因此，强度越高，重量越大。

为简化计算过程，我们需要使x坐标和y坐标的网格大小与原始图像的大小相同。 x和y的加权平均坐标将为您提供加权质心

import numpy as np
import cv2

# create a meshgrid for coordinate calculation
r,c = np.shape(ori_img)
r_ = np.linspace(0,r,r+1)
c_ = np.linspace(0,c,c+1)
x_m, y_m = np.meshgrid(c_, r_, sparse=False, indexing='ij')


im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)


for c in contours:
     # Get the boundingbox
     x,y,w,h = cv2.boundingRect(c)

     # calculate x,y coordinate of center
     # Get the corresponding roi for calculation
     weights = ori_img[y:y+h,x:x+w]
     roi_grid_x = x_m[y:y+h,x:x+w]
     roi_grid_y = y_m[y:y+h,x:x+w]

     # get the weighted sum
     weighted_x = weights * roi_grid_x
     weighted_y = weights * roi_grid_y

     cx = np.sum(weighted_x) / np.sum(weights)
     cy = np.sum(roi_grid_y) / np.sum(weights)

Answer 2

对@ yapws87的答案进行了一些修复，但是我不确定代码是否有效。

import numpy as np
import cv2

# create a meshgrid for coordinate calculation
r,c = np.shape(ori_img)
r_ = np.linspace(0,r,r+1)
c_ = np.linspace(0,c,c+1)
x_m, y_m = np.meshgrid(r_, c_, sparse=False, indexing='ij')


im2, contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)


for c in contours:
     # Get the boundingbox
     x,y,w,h = cv2.boundingRect(c)

     # calculate x,y coordinate of center
     # Get the corresponding roi for calculation
     weights = ori_img[y:y+h,x:x+w]
     roi_grid_x = x_m[y:y+h,x:x+w]
     roi_grid_y = y_m[y:y+h,x:x+w]
     
     # get the weighted sum
     weighted_x = weights * roi_grid_x
     weighted_y = weights * roi_grid_y
     
     cy = np.sum(weighted_x) / np.sum(weights)
     cx = np.sum(weighted_y) / np.sum(weights)

用opencv计算一个质心

2 个答案: