请给我使用Hough变换找到图像中文档边界四点的代码
时间: 2024-01-24 12:20:16 浏览: 31
好的,以下是使用Hough变换找到图像中文档边界四点的Python代码:
```python
import cv2
import numpy as np
# 读取图像并进行灰度处理
img = cv2.imread('document.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 对图像进行高斯模糊处理
blur = cv2.GaussianBlur(gray, (3, 3), 0)
# 进行边缘检测
edges = cv2.Canny(blur, 50, 150, apertureSize=3)
# 进行霍夫直线检测
lines = cv2.HoughLines(edges, 1, np.pi/180, 200)
# 将直线转换为端点坐标
points = []
for line in lines:
rho, theta = line[0]
a = np.cos(theta)
b = np.sin(theta)
x0 = a * rho
y0 = b * rho
x1 = int(x0 + 1000 * (-b))
y1 = int(y0 + 1000 * (a))
x2 = int(x0 - 1000 * (-b))
y2 = int(y0 - 1000 * (a))
points.append((x1, y1, x2, y2))
# 根据直线位置找到四个角点
corners = []
for i in range(len(points)):
for j in range(i+1, len(points)):
x1, y1, x2, y2 = points[i]
x3, y3, x4, y4 = points[j]
d = (x1-x2)*(y3-y4) - (y1-y2)*(x3-x4)
if d != 0:
x = int(((x1*y2-y1*x2)*(x3-x4)-(x1-x2)*(x3*y4-y3*x4)) / d)
y = int(((x1*y2-y1*x2)*(y3-y4)-(y1-y2)*(x3*y4-y3*x4)) / d)
corners.append((x, y))
# 绘制角点并显示图像
for corner in corners:
cv2.circle(img, corner, 5, (0, 0, 255), -1)
cv2.imshow('document', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
上述代码中,我们首先读取图像并进行灰度处理,然后对图像进行高斯模糊和边缘检测。接着,我们使用`cv2.HoughLines`函数进行霍夫直线检测,并将直线转换为端点坐标。最后,我们根据直线位置找到四个角点,并绘制角点。运行以上代码即可得到找到图像中文档边界四点的结果。