请用python语言给我提取图中文档四个点坐标的算法
时间: 2024-01-15 10:04:29 浏览: 28
可以使用Python的OpenCV库来实现提取文档四个点的算法。具体步骤如下:
1. 读入图片,将图片转换为灰度图像。
```python
import cv2
img = cv2.imread("document.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
```
2. 对灰度图像进行二值化处理,将图片中的文本和背景分离出来。
```python
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
```
3. 对二值化图像进行膨胀操作,使得文档边缘更加明显。
```python
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
dilate = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel, iterations=4)
```
4. 使用霍夫变换检测图片中的直线,找到文档的四个边缘。
```python
lines = cv2.HoughLinesP(dilate, 1, cv2.cv2.PI / 180, threshold=100, minLineLength=100, maxLineGap=10)
for line in lines:
x1, y1, x2, y2 = line[0]
cv2.line(img, (x1, y1), (x2, y2), (0, 0, 255), 2)
```
5. 对检测到的直线进行筛选和排序,找到文档的四个角点。
```python
corners = cv2.goodFeaturesToTrack(gray, 4, 0.5, 100)
corners = np.int0(corners)
for corner in corners:
x, y = corner.ravel()
cv2.circle(img, (x, y), 3, (255, 0, 0), -1)
```
完整代码如下:
```python
import cv2
import numpy as np
img = cv2.imread("document.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
dilate = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel, iterations=4)
lines = cv2.HoughLinesP(dilate, 1, cv2.cv2.PI / 180, threshold=100, minLineLength=100, maxLineGap=10)
for line in lines:
x1, y1, x2, y2 = line[0]
cv2.line(img, (x1, y1), (x2, y2), (0, 0, 255), 2)
corners = cv2.goodFeaturesToTrack(gray, 4, 0.5, 100)
corners = np.int0(corners)
for corner in corners:
x, y = corner.ravel()
cv2.circle(img, (x, y), 3, (255, 0, 0), -1)
cv2.imshow("document", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
其中,corners变量就是文档的四个角点坐标。