Question

I’ve tried to implement the example from the book named OpenCV 2 Computer Vision Application Programming Cookbook, which shows how to find a line with the help of the Hough Probabilistic Algorithm (page 170). (A very good book btw!)
the book in pdf

But I’ve encountered some problem with C++, I’m not a guru in programming this why I need your help.
Visual Studio shows me this following error :

Unhandled exception at 0x00e274b7 in LineTracking_v02.exe: 0xC0000005:
Access violation reading location 0x00000000.

When I debug, it seems to come from the line 57 (‘return lines;’ in ‘findLines’ function).

Have you got any idea why ?

Here is my code :

//v2

#include "opencv\cv.h"
#include "opencv\highgui.h"
#include <iostream>
using namespace cv;
using namespace std;
#define PI 3.1415926535898


class LineFinder{
private :
    //original image
    cv::Mat img;
    //vector containing the end points of the detected lines
    std::vector<cv::Vec4i> lines;
    //accumulator resolution parameters
    double deltaRho;
    double deltaTheta;
    //minimum number of votes that a lines must receive before
    //being considered
    int minVote;
    //min length for a line
    double minLength;
    //max allowed gap along the line
    double maxGap;

public:
    //default accumulator resolution is 1 pixel by 1 degree,
    //no gap, no minimum length
    LineFinder() :  deltaRho(1), 
        deltaTheta(PI/180), 
        minVote(10),
        minLength(0.) {}

    //Set the resolution of the accumulator
    void setAccResolution(double dRho, double dTheta){
        deltaRho = dRho;
        deltaTheta = dTheta;
    }

    //Set the minimum number of votes
    void setMinVote(int minv){
        minVote = minv;
    }

    //Set line length and gap
    void setLineLengthAndGap(double length, double gap){
        minLength = length;
        maxGap = gap;
    }

    //Apply probabilistic Hough Transform
    std::vector<cv::Vec4i> findLines(cv::Mat& binary){
        lines.clear();
        cv::HoughLinesP(binary, lines, deltaRho, deltaTheta, minVote, minLength, maxGap);
        return lines;
    }

    //Draw the detected lines on an image
    void drawDetectedLines(cv::Mat &image, cv::Scalar color=cv::Scalar(255,255,255)){
        std::vector<cv::Vec4i>::const_iterator it2 = lines.begin();
        while(it2!=lines.end()){
            cv::Point pt1((*it2)[0], (*it2)[1]);
            cv::Point pt2((*it2)[2], (*it2)[3]);
            cv::line(image, pt1, pt2, color);
            ++it2;
        }
    }
};

int main(int, char**)
{
    // Open the default camera
    cv::VideoCapture capture(0); 
    // Check if we succeeded
    if(!capture.isOpened()) 
    {
        std::cout<<"Video capture failed, please check the camera."<<std::endl;
        return -1;
    }else{
        std::cout<<"Video camera capture successful!"<<std::endl;
    }

    for(;;) {
        cv::Mat frame;
        cv::Mat grayFrame;
        cv::Mat gaussGrayFrame;
        cv::Mat edges;
        LineFinder finder;

        capture >> frame; // get a new frame from camera

        //Convert the frame into a gray Frame
        cv::cvtColor(frame, grayFrame, CV_BGR2GRAY);

        //Apply a Gaussian Blur on the gray-level Frame
        cv::GaussianBlur(grayFrame, gaussGrayFrame, cv::Size(7,7), 1.5, 1.5);

        //Apply Canny Algorithm
        cv::Canny(
            gaussGrayFrame, // gray-level source image
            edges,          // output contours
            0,              // low threshold
            30,             // high threshold
            3);             // aperture size
        //End Canny Algorithm

        //Detect lines
        std::vector<cv::Vec4i> lines = finder.findLines(edges);
        //Draw the detected lines
        finder.drawDetectedLines(frame);

        cv::imshow("Camera Preview", frame);
        if(cv::waitKey(30) >= 0) break;
    }

    // the camera will be deinitialized automatically in VideoCapture destructor
    return 0;
}

Thank u in advance for your help !

Answer 1

I have just successfully compiled and executed your program under Ubuntu Linux. My current random theory right now is that the edges is not initialised properly in your environment.

I would insert a few cv::imwrite or cv::imshow (for frame, grayFrame, edges) to see if all images are containing reasonable values.