opencv-060-二值图像分析(霍夫直线检测二)

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知识点

OpenCV中还有另外一个霍夫直线检测的API，该API更为常用，它会直接返回直线的空间坐标点，比返回霍夫空间参数更加的直观，容易理解，而且还可以声明线段长度、间隔等参数，非常有用。

API

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void cv::HoughLinesP(
	InputArray image,
	OutputArray lines,
	double rho,
	double theta,
	int threshold,
	double 	minLineLength = 0,
	double 	maxLineGap = 0 
)
Image输入二值图像
Lines 返回的直线两个点
Rho 极坐标r得步长
Theta角度步长
Threshold累加器阈值
minLineLength最小线段长度
maxLineGap线段间隔

代码（c++,python）

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#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

/*
 * 二值图像分析(霍夫直线检测二)
 */
int main() {
    Mat src = imread("../images/line.png");
    if (src.empty()) {
        cout << "could not load image.." << endl;
    }
    imshow("input", src);

    // 去噪声与二值化
    Mat binary;
    Canny(src, binary, 80, 160);

    // 霍夫直线检测
    vector<Vec4i> lines;
    HoughLinesP(binary, lines, 1, CV_PI / 180, 80, 30, 10);

    // 绘制直线
    Mat result = Mat::zeros(src.size(), src.type());
    for (size_t i = 0; i < lines.size(); ++i) {
        line(result, Point(lines[i][0], lines[i][1]),
             Point(lines[i][2], lines[i][3]), Scalar(0, 0, 255));
    }

    imshow("contours", result);

    waitKey(0);
    return 0;
}
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import cv2 as cv
import numpy as np

def canny_demo(image):
    t = 80
    canny_output = cv.Canny(image, t, t * 2)
    cv.imwrite("D:/canny_output.png", canny_output)
    return canny_output


src = cv.imread("D:/images/morph01.png")
cv.namedWindow("input", cv.WINDOW_AUTOSIZE)
cv.imshow("input", src)
binary = canny_demo(src)
cv.imshow("binary", binary)

linesP = cv.HoughLinesP(binary, 1, np.pi / 180, 50, None, 50, 10)
if linesP is not None:
    for i in range(0, len(linesP)):
        l = linesP[i][0]
        cv.line(src, (l[0], l[1]), (l[2], l[3]), (255, 0, 0), 1, cv.LINE_AA)

cv.imshow("hough line demo", src)
cv.imwrite("D:/contours_analysis.png", src)
cv.waitKey(0)
cv.destroyAllWindows()

结果

代码地址

github