opencv2实现多张图片路经路牌检测_计算机视觉大作业2

linefinder.h同上一篇博文

main.cpp

/*------------------------------------------------------------------------------------------*
This file contains material supporting chapter 7 of the cookbook:  
Computer Vision Programming using the OpenCV Library. 
by Robert Laganiere, Packt Publishing, 2011.

This program is free software; permission is hereby granted to use, copy, modify, 
and distribute this source code, or portions thereof, for any purpose, without fee, 
subject to the restriction that the copyright notice may not be removed 
or altered from any source or altered source distribution. 
The software is released on an as-is basis and without any warranties of any kind. 
In particular, the software is not guaranteed to be fault-tolerant or free from failure. 
The author disclaims all warranties with regard to this software, any use, 
and any consequent failure, is purely the responsibility of the user.

Copyright (C) 2010-2011 Robert Laganiere, www.laganiere.name
*------------------------------------------------------------------------------------------*/

#include <iostream>
#include <vector>
#include <opencv2/core/core.hpp>
//#include <opencv2/imageproc/imageproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include<string>  
#include <sstream>
#include "linefinder.h"
//#include "edgedetector.h"

using namespace cv;
using namespace std;
#define PI 3.1415926

int main()
{
	stringstream ss;  
    string str; 
	for(int i=1;i<=80;i++)  
    {  
        str="D:大学课程智能技术2-2视觉作业视觉作业作业2014作业2";//选择F:图片中的5张图片  
        ss.clear();  
        ss<<str;  
        ss<<i;  
        ss<<".jpg";  
        ss>>str;  
        Mat image=imread(str,1);  
	// Read input image
	//Mat image= imread("1.jpg",1);
	if (!image.data)
		return 0; 
	/*namedWindow("Original Image");
	imshow("Original Image",image);*/


	Mat img=image(Rect(0.4*image.cols,0.58*image.rows,0.4*image.cols,0.3*image.rows));
	Mat contours;
	Canny(img,contours,80,100);

	cv::Mat contoursInv;
	cv::threshold(contours,contoursInv,128,255,cv::THRESH_BINARY_INV);

	// Display the image of contours
	/*cv::namedWindow("Canny Contours");
	cv::imshow("Canny Contours",contoursInv);*/


	// Create LineFinder instance
	LineFinder ld;

	// Set probabilistic Hough parameters
	ld.setLineLengthAndGap(80,30);
	ld.setMinVote(30);
	
	vector<Vec4i> li= ld.findLines(contours);
	ld.drawDetectedLines(img);
	
	/*namedWindow(" HoughP");
	imshow(" HoughP",img);*/
	/*namedWindow("Detected Lines with HoughP");
	imshow("Detected Lines with HoughP",image);*/

	Mat imgGry;
	cvtColor(image,imgGry,CV_BGR2GRAY);
	GaussianBlur(imgGry,imgGry,Size(5,5),1.5);
	vector<Vec3f> circles;
	HoughCircles(imgGry, circles, CV_HOUGH_GRADIENT, 
		2,   // accumulator resolution (size of the image / 2) 
		50,  // minimum distance between two circles
		200, // Canny high threshold 
		100, // minimum number of votes 
		25, 50); // min and max radius

	cout << "Circles: " << circles.size() << endl;

	// Draw the circles
	
	vector<Vec3f>::const_iterator itc= circles.begin();

	while (itc!=circles.end()) {

		circle(image, 
			Point((*itc)[0], (*itc)[1]), // circle centre
			(*itc)[2], // circle radius
			Scalar(255), // color 
			2); // thickness

		++itc;	
	}

	namedWindow(str);
	imshow(str,image);
	}
	waitKey();
	return 0;
}