9×9Zernike矩的检测算法代码
时间: 2023-10-03 14:04:03 浏览: 41
以下是一个简单的基于Python的9×9 Zernike矩检测算法的示例代码:
```python
import cv2
import numpy as np
from skimage.measure import moments_central, moments_normalized, moments_central, moments_hu
def calculate_zernike_moments(image):
# 将图像转换为灰度图像
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# 计算二值化图像
_, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
# 获取图像的中心点坐标
M = cv2.moments(binary)
cX = int(M["m10"] / M["m00"])
cY = int(M["m01"] / M["m00"])
# 将图像中心化
centered = np.zeros_like(binary)
rows, cols = binary.shape[:2]
shiftX = int(cols / 2 - cX)
shiftY = int(rows / 2 - cY)
M = np.float32([[1, 0, shiftX], [0, 1, shiftY]])
centered = cv2.warpAffine(binary, M, (cols, rows))
# 计算Zernike矩
zernike_moments = []
for n in range(9):
for m in range(n + 1):
if (n - m) % 2 == 0:
p = n - m
q = n + m
moment = cv2.moments(centered * np.exp(1j * np.pi / 4))
cm = moments_central(moment, p, q)
nm = moments_normalized(cm, p, q)
zm = moments_hu(nm)
zernike_moments.append(zm[0])
return zernike_moments
# 在此处加载图像
image = cv2.imread('image.jpg')
# 计算Zernike矩
zernike_moments = calculate_zernike_moments(image)
# 打印Zernike矩
print("Zernike Moments:", zernike_moments)
```
请注意,这只是一个简单的示例代码,实际上还可以根据具体需求进行更多的处理和优化。