大津法自动阈值变化检测python伪代码
时间: 2023-10-12 10:15:34 浏览: 52
以下是大津法自动阈值变化检测的Python伪代码:
```
# 导入必要的库
import cv2
import numpy as np
# 读取图像
image = cv2.imread("image.jpg", 0)
# 计算图像的直方图
hist, bins = np.histogram(image.flatten(), 256, [0, 256])
# 计算总像素数
pixels = np.sum(hist)
# 初始化变量
sumB = 0
wB = 0
maximum = 0
threshold1 = 0
threshold2 = 0
# 遍历灰度级
for i in range(256):
wF = pixels - wB
if wB != 0 and wF != 0:
sumF = np.sum(np.arange(i) * hist[:i])
meanB = sumB / wB
meanF = (sumF - sumB) / wF
between = wB * wF * (meanB - meanF) ** 2
if between > maximum:
maximum = between
threshold1 = i
wB += hist[i]
sumB += i * hist[i]
# 计算第二个阈值
threshold2 = np.mean(image)
# 应用阈值
ret, thresh1 = cv2.threshold(image, threshold1, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(image, threshold2, 255, cv2.THRESH_BINARY)
# 显示结果
cv2.imshow("Original Image", image)
cv2.imshow("Otsu Thresholding", thresh1)
cv2.imshow("Mean Thresholding", thresh2)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
以上代码使用OpenCV库实现了大津法自动阈值变化检测。首先,读取图像并计算直方图。然后,遍历灰度级并计算两个阈值。最后,应用阈值并显示结果。