openCV—Python(11)—— 图像边缘检测

本文介绍了三种常见的边缘检测技术:Laplacian算子、Sobel算子和Canny算子,并通过实例展示了如何使用这些技术进行图像边缘检测。

一、函数简介

1、laplacian算子

函数原型:Laplacian(src, ddepth, dst=None, ksize=None, scale=None, delta=None, borderType=None)

src:图像矩阵

ddepth:深度类型

2、Sobel算子

函数原型:Sobel(src, ddepth, dx, dy, dst=None, ksize=None, scale=None, delta=None, borderType=None)

src:图像矩阵

ddepth:深度类型

dx:x方向

dy:y方向

3、Canny算子

函数原型:Canny(image, threshold1, threshold2, edges=None, apertureSize=None, L2gradient=None)

image:图像矩阵

threshold1:阈值1

threshold1:阈值2

二、实例演练

1、拉普拉斯边缘检测

代码如下:

<code class="hljs avrasm has-numbering" style="display: block; padding: 0px; background: transparent; color: inherit; box-sizing: border-box; font-family: "Source Code Pro", monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal;"><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#encoding:utf-8</span>

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#laplacian边缘检测</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>

import numpy as np
import cv2

image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imread</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"H:\\img\\lena.jpg"</span>)
image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.cvtColor</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.COLOR</span>_BGR2GRAY)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#将图像转化为灰度图像</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Original"</span>,image)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#拉普拉斯边缘检测</span>
lap = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.Laplacian</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.CV</span>_64F)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#拉普拉斯边缘检测</span>
lap = np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.uint</span>8(np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.absolute</span>(lap))<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">##对lap去绝对值</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Laplacian"</span>,lap)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()</code><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li><li style="box-sizing: border-box; padding: 0px 5px;">19</li></ul><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li><li style="box-sizing: border-box; padding: 0px 5px;">19</li></ul>

结果如下:

原图像:

这里写图片描述

laplacian边缘检测结果:

这里写图片描述

2、Soble边缘检测

代码如下:

<code class="hljs avrasm has-numbering" style="display: block; padding: 0px; background: transparent; color: inherit; box-sizing: border-box; font-family: "Source Code Pro", monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal;"><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#encoding:utf-8</span>

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#Sobel边缘检测</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>

import numpy as np
import cv2

image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imread</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"H:\\img\\lena.jpg"</span>)
image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.cvtColor</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.COLOR</span>_BGR2GRAY)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#将图像转化为灰度图像</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Original"</span>,image)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#Sobel边缘检测</span>
sobelX = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.Sobel</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.CV</span>_64F,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#x方向的梯度</span>
sobelY = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.Sobel</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.CV</span>_64F,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#y方向的梯度</span>

sobelX = np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.uint</span>8(np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.absolute</span>(sobelX))<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#x方向梯度的绝对值</span>
sobelY = np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.uint</span>8(np<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.absolute</span>(sobelY))<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#y方向梯度的绝对值</span>

sobelCombined = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.bitwise</span>_or(sobelX,sobelY)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Sobel X"</span>, sobelX)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Sobel Y"</span>, sobelY)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Sobel Combined"</span>, sobelCombined)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()</code><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li><li style="box-sizing: border-box; padding: 0px 5px;">19</li><li style="box-sizing: border-box; padding: 0px 5px;">20</li><li style="box-sizing: border-box; padding: 0px 5px;">21</li><li style="box-sizing: border-box; padding: 0px 5px;">22</li><li style="box-sizing: border-box; padding: 0px 5px;">23</li><li style="box-sizing: border-box; padding: 0px 5px;">24</li><li style="box-sizing: border-box; padding: 0px 5px;">25</li><li style="box-sizing: border-box; padding: 0px 5px;">26</li><li style="box-sizing: border-box; padding: 0px 5px;">27</li><li style="box-sizing: border-box; padding: 0px 5px;">28</li></ul><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li><li style="box-sizing: border-box; padding: 0px 5px;">19</li><li style="box-sizing: border-box; padding: 0px 5px;">20</li><li style="box-sizing: border-box; padding: 0px 5px;">21</li><li style="box-sizing: border-box; padding: 0px 5px;">22</li><li style="box-sizing: border-box; padding: 0px 5px;">23</li><li style="box-sizing: border-box; padding: 0px 5px;">24</li><li style="box-sizing: border-box; padding: 0px 5px;">25</li><li style="box-sizing: border-box; padding: 0px 5px;">26</li><li style="box-sizing: border-box; padding: 0px 5px;">27</li><li style="box-sizing: border-box; padding: 0px 5px;">28</li></ul>

结果如下:

原图像:

这里写图片描述

X方向边缘检测结果:

这里写图片描述

Y方向边缘检测结果:

这里写图片描述

XY方向结合边缘检测结果:

这里写图片描述

3、Canny边缘检测

代码如下:

<code class="hljs avrasm has-numbering" style="display: block; padding: 0px; background: transparent; color: inherit; box-sizing: border-box; font-family: "Source Code Pro", monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal;"><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#encoding:utf-8</span>

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#Canny边缘检测</span>
<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#</span>

import numpy as np
import cv2

image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imread</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"H:\\img\\lena.jpg"</span>)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#读入图像</span>
image = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.cvtColor</span>(image,cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.COLOR</span>_BGR2GRAY)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#将图像转化为灰度图像</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Image"</span>,image)<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#显示图像</span>
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()

<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#Canny边缘检测</span>
canny = cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.Canny</span>(image,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">30</span>,<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">150</span>)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.imshow</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"Canny"</span>,canny)
cv2<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">.waitKey</span>()</code><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li></ul><ul class="pre-numbering eye-protector-processed" style="box-sizing: border-box; position: absolute; width: 50px; background-color: rgb(193, 230, 198); top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right: 1px solid rgba(0, 0, 0, 0.34902); list-style: none; text-align: right; transition: background 0.3s ease;"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li></ul>

结果如下:

原图像:

这里写图片描述

Canny边缘检测结果:

这里写图片描述

PythonOpenCV中实现直线检测,可以使用Hough变换来检测直线。Hough变换是一种常用的图像处理方法,可用于检测直线、圆等几何形状。 以下是一个简单的示例代码,使用Hough变换来检测直线并计算交点: ```python import cv2 import numpy as np # 读取图像 img = cv2.imread('test.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 边缘检测 edges = cv2.Canny(gray, 50, 150, apertureSize=3) # Hough变换检测直线 lines = cv2.HoughLines(edges, 1, np.pi/180, 200) # 计算交点 points = [] for i in range(len(lines)): for j in range(i+1, len(lines)): rho1, theta1 = lines[i][0] rho2, theta2 = lines[j][0] if abs(theta1 - theta2) < np.pi/4: continue a = np.array([[np.cos(theta1), np.sin(theta1)], [np.cos(theta2), np.sin(theta2)]]) b = np.array([rho1, rho2]) x0, y0 = np.linalg.solve(a, b) points.append((int(x0), int(y0))) # 绘制直线和交点 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)) cv2.line(img, (x1,y1), (x2,y2), (0,0,255), 2) for point in points: cv2.circle(img, point, 5, (0,255,0), -1) # 显示图像 cv2.imshow('image', img) cv2.waitKey(0) cv2.destroyAllWindows() ``` 在代码中,首先读取图像并进行灰度转换和边缘检测。然后使用Hough变换检测直线,并计算交点。最后绘制直线和交点,并显示图像。 需要注意的是,在计算交点时,需要将两条直线的极坐标表示转换为直角坐标表示,并使用线性方程组求解。 希望这个例子能够帮助到你实现直线检测并计算交点。
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