现在,我正在使用以下程序,但我无法获得所需的图像时刻、质心等。
代码:
import cv2
import numpy
from matplotlib.pyplot import imread
from numpy import mgrid, sum
image = imread('imagemoment.png')
def moments2e(image):
assert len(image.shape) == 2 # only for grayscale images
x, y = mgrid[:image.shape[0], :image.shape[1]]
moments = {}
moments['mean_x'] = sum(x * image) / sum(image)
moments['mean_y'] = sum(y * image) / sum(image)
# raw or spatial moments
moments['m00'] = sum(image)
moments['m01'] = sum(x * image)
moments['m10'] = sum(y * image)
moments['m11'] = sum(y * x * image)
moments['m02'] = sum(x ** 2 * image)
moments['m20'] = sum(y ** 2 * image)
moments['m12'] = sum(x * y ** 2 * image)
moments['m21'] = sum(x ** 2 * y * image)
moments['m03'] = sum(x ** 3 * image)
moments['m30'] = sum(y ** 3 * image)
# central moments
moments['mu01']= sum((y-moments['mean_y'])*image) # should be 0
moments['mu10']= sum((x-moments['mean_x'])*image) # should be 0
moments['mu11'] = sum((x - moments['mean_x']) * (y - moments['mean_y']) * image)
moments['mu02'] = sum((y - moments['mean_y']) ** 2 * image) # variance
moments['mu20'] = sum((x - moments['mean_x']) ** 2 * image) # variance
moments['mu12'] = sum((x - moments['mean_x']) * (y - moments['mean_y']) ** 2 * image)
moments['mu21'] = sum((x - moments['mean_x']) ** 2 * (y - moments['mean_y']) * image)
moments['mu03'] = sum((y - moments['mean_y']) ** 3 * image)
moments['mu30'] = sum((x - moments['mean_x']) ** 3 * image)
# opencv versions
# moments['mu02'] = sum(image*(x-m01/m00)**2)
# moments['mu02'] = sum(image*(x-y)**2)
# wiki variations
# moments['mu02'] = m20 - mean_y*m10
# moments['mu20'] = m02 - mean_x*m01
你能帮我解决这个问题吗?非常感谢。
紫衣仙女
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