OpenCV——15直线检测

直线检测

• 霍夫直线变换介绍
• 相关API代码演示

1.霍夫直线变换介绍

• Hough Line Transform用来做直线检测
• 前提条件 – 边缘检测已经完成
• 平面空间到极坐标空间转换
  
  

# -*- coding:utf-8 -*-
import cv2 as cv
import numpy as np

def line_detection(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    lines = cv.HoughLines(edges, 1, np.pi/180, 200)
    for line in lines:
        print(type(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))
        cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
    cv.imshow("image-lines", image)

def line_detection_possible_demo(image):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    edges = cv.Canny(gray, 50, 150, apertureSize=3)
    lines = cv.HoughLinesP(edges, 1, np.pi/180, 100, minLineLength=50, maxLineGap=10)
    for line in lines:
        print(type(line))
        x1, y1, x2, y2 = line[0]
        cv.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)
    cv.imshow("line_detect_possible_demo", image)

# 读取图片
src = cv.imread("D:\Python\Projects\OpenCV_toturial\images\sudoku.png")
# 创建opencv的GUI窗口
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
# 将图片放入指定名字的窗口中显示出来
cv.imshow("input image", src)

# line_detection(src)
line_detection_possible_demo(src)

# 设置waitKey中的delay为0，程序会等待用户操作后关闭窗口
cv.waitKey(0)
cv.destroyAllWindows()

调用cv.HoughLines的结果：

调用cv.HoughLinesP的结果：