opencv学习笔记四十七：基于形态学的直线检测

案例背景：将答题卡中的直线提取出来

方案思路：二值化后利用霍夫直线检测，效果特别差；canny边缘检测后利用霍夫直线检测效果也很差，有些线检测不出来。这里采用的方法是基于形态学的直线提取，再利用霍夫直线检测。

#include<opencv2\opencv.hpp>
using namespace cv;
using namespace std;

int main(int arc, char** argv) { 
	Mat src = imread("1.jpg");
	namedWindow("input", CV_WINDOW_AUTOSIZE);
	imshow("input", src);
	cvtColor(src, src, CV_BGR2GRAY);
	Mat binaryImg, morphImg;
	Rect roi = Rect(10, 10, src.cols - 20, src.rows - 20);
	Mat roiImg = src(roi);
	threshold(roiImg, binaryImg, 0, 255, THRESH_BINARY_INV | THRESH_OTSU);
	imshow("binaryImg", binaryImg);

	//定义水平直线结构元素，开操作进行水平直线的提取
	Mat kernel = getStructuringElement(MORPH_RECT, Size(30, 1), Point(-1, -1));
	morphologyEx(binaryImg, morphImg, MORPH_OPEN, kernel);
	imshow("morphImg", morphImg);
	//膨胀加强直线
	kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
	dilate(morphImg, morphImg, kernel);
	imshow("dilateImg", morphImg);
	//霍夫直线检测
	vector<Vec4i>lines;
	HoughLinesP(morphImg, lines, 1, CV_PI / 180, 30, 20.0,0);
	Mat resultImg = roiImg.clone();
	cvtColor(resultImg, resultImg, CV_GRAY2BGR);
	for (int i = 0; i < lines.size(); i++) {
		Vec4i ln = lines[i];
		line(resultImg, Point(ln[0], ln[1]), Point(ln[2], ln[3]), Scalar(0, 0, 255));
	}
	imshow("result", resultImg);
	printf("%d", lines.size());
	waitKey(0);
	return 0;
}