opencv条码(5)边缘检测

代码其实可以很简洁

#include <cv.h>
#include <highgui.h>

using namespace cv;

int main(){
    // Read input image
    cv::Mat image= cv::imread("C:/testdir/barcode5.jpg", 0);　　//0表示按黑白图读入
    if(!image.data) return 0;
    Mat contours;
    Canny(image, contours, 125, 350);
    imshow("result", contours);
    cv::waitKey();
    return 0;
}

 不过为了看起来效果更好一点，可以将黑白对调再显示：

#include <cv.h>
#include <highgui.h>
#include <iostream>
#include <vector>

using namespace std;
using namespace cv;

#define PI 3.1415926

int main(){
    Mat image=imread("C:/testdir/barcode0.jpg", 0);
    Mat contours;
    Canny(image, contours, 125, 350);       //对于image做边缘检测，结果处理在contours上
    //--------inverted representation--------//
    Mat contoursInv;
    threshold(contours, contoursInv, 128, 255, THRESH_BINARY_INV);//将contours黑白对换，结果处理在contoursInv上
    //---------------------------------------//
    imshow("sdfsdf", contoursInv);
    waitKey(0);
    return 0;
}

 用霍夫变换检测线段

#include <cv.h>
#include <highgui.h>
#include <iostream>
#include <vector>

using namespace std;
using namespace cv;

#define PI 3.1415926

class LineFinder{
private:
    Mat img;
    vector<Vec4i>lines;
    double deltaRho;
    double deltaTheta;
    int minVote;
    double minLength;
    double maxGap;
public:
    LineFinder():deltaRho(1), deltaTheta(PI/180), minVote(10), minLength(0.), maxGap(0.){}

    void setAccResolution(double dRho, double dTheta){
        deltaRho=dRho;
        deltaTheta=dTheta;
    }
    void setMinVote(int minv){
        minVote=minv;
    }
    void setLineLengthAndGap(double length, double gap){
        minLength=length;
        maxGap=gap;
    }
    vector<Vec4i>findLines(Mat& binary){
        lines.clear();
        HoughLinesP(binary, lines, deltaRho, deltaTheta, minVote, minLength, maxGap);
        return lines;
    }
    void drawDetectedLines(Mat &image, Scalar color=Scalar(255, 255, 255)){
        vector<Vec4i>::const_iterator it2=lines.begin();
        while(it2!=lines.end()){
            Point pt1((*it2)[0], (*it2)[1]);
            Point pt2((*it2)[2], (*it2)[3]);
            line(image, pt1, pt2, color);
            ++it2;
        }
    }
};

int main(){
    Mat image=imread("C:/testdir/barcode0.jpg", 0);
    Mat contours;
    Canny(image, contours, 125, 350);       //对于image做边缘检测，结果处理在contours上

    LineFinder finder;
    finder.setLineLengthAndGap(100, 20);
    finder.setMinVote(80);

    vector<Vec4i>lines=finder.findLines(contours);
    finder.drawDetectedLines(image);
    namedWindow("Detected Lines with HoughP");
    imshow("Detected Lines with HoughP", image);


  //  imshow("abracadabra", result);

    waitKey(0);
    return 0;
}