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社区首页 >问答首页 >从边缘检测器输出中修剪短线段?

从边缘检测器输出中修剪短线段?
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Stack Overflow用户
提问于 2009-09-22 19:27:36
回答 7查看 3.8K关注 0票数 8

我正在寻找一种算法,可以从边缘检测器的输出中修剪短线段。在下面的图像(和链接)中可以看到,有几个检测到的小边缘不是“长”线。理想情况下,我希望在处理后只显示四边形的4个边,但如果有几条杂乱的线,这不是什么大问题……有什么建议吗?

Image Link

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回答 7

Stack Overflow用户

回答已采纳

发布于 2009-09-22 19:59:12

在找到边之前,使用openclose操作(或两者)对图像进行预处理,即,先腐蚀后膨胀,或先膨胀后腐蚀。这应该会删除较小的对象,但保留较大的对象大致相同。

我在网上找过一些例子,我能找到的最好的是在this PDF的第41页。

票数 5
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Stack Overflow用户

发布于 2009-09-22 19:55:56

我怀疑通过简单的本地操作可以做到这一点。看看你想要保留的矩形--有几个空隙,因此执行本地操作来删除短线段可能会大大降低所需输出的质量。

因此,我会尝试通过闭合间隙、拟合多边形或类似的事情来检测矩形作为重要内容,然后在第二步中丢弃其余不重要的内容。也许Hough transform能帮上忙。

更新

我刚刚使用了这个sample application,对你的样本图像进行了Kernel Hough变换,得到了四条适合你的矩形的漂亮线条。

票数 4
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Stack Overflow用户

发布于 2012-04-20 10:36:59

如果有人踩到了这个线程,OpenCV 2.x带来了一个名为squares.cpp的示例,它基本上解决了这个任务。

我对应用程序做了一点修改,以提高对四边形的检测能力。

代码

代码语言:javascript
复制
#include "highgui.h"
#include "cv.h"

#include <iostream>
#include <math.h>
#include <string.h>

using namespace cv;
using namespace std;

void help()
{
        cout <<
        "\nA program using pyramid scaling, Canny, contours, contour simpification and\n"
        "memory storage (it's got it all folks) to find\n"
        "squares in a list of images pic1-6.png\n"
        "Returns sequence of squares detected on the image.\n"
        "the sequence is stored in the specified memory storage\n"
        "Call:\n"
        "./squares\n"
    "Using OpenCV version %s\n" << CV_VERSION << "\n" << endl;
}

int thresh = 70, N = 2; 
const char* wndname = "Square Detection Demonized";

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
double angle( Point pt1, Point pt2, Point pt0 )
{
    double dx1 = pt1.x - pt0.x;
    double dy1 = pt1.y - pt0.y;
    double dx2 = pt2.x - pt0.x;
    double dy2 = pt2.y - pt0.y;
    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
void findSquares( const Mat& image, vector<vector<Point> >& squares )
{
    squares.clear();

    Mat pyr, timg, gray0(image.size(), CV_8U), gray;

    // karlphillip: dilate the image so this technique can detect the white square,
    Mat out(image);
    dilate(out, out, Mat(), Point(-1,-1));
    // then blur it so that the ocean/sea become one big segment to avoid detecting them as 2 big squares.
    medianBlur(out, out, 3);

    // down-scale and upscale the image to filter out the noise
    pyrDown(out, pyr, Size(out.cols/2, out.rows/2));
    pyrUp(pyr, timg, out.size());
    vector<vector<Point> > contours;

    // find squares only in the first color plane
    for( int c = 0; c < 1; c++ ) // was: c < 3
    {
        int ch[] = {c, 0};
        mixChannels(&timg, 1, &gray0, 1, ch, 1);

        // try several threshold levels
        for( int l = 0; l < N; l++ )
        {
            // hack: use Canny instead of zero threshold level.
            // Canny helps to catch squares with gradient shading
            if( l == 0 )
            {
                // apply Canny. Take the upper threshold from slider
                // and set the lower to 0 (which forces edges merging)
                Canny(gray0, gray, 0, thresh, 5);
                // dilate canny output to remove potential
                // holes between edge segments
                dilate(gray, gray, Mat(), Point(-1,-1));
            }
            else
            {
                // apply threshold if l!=0:
                //     tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
                gray = gray0 >= (l+1)*255/N;
            }

            // find contours and store them all as a list
            findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);

            vector<Point> approx;

            // test each contour
            for( size_t i = 0; i < contours.size(); i++ )
            {
                // approximate contour with accuracy proportional
                // to the contour perimeter
                approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true)*0.02, true);

                // square contours should have 4 vertices after approximation
                // relatively large area (to filter out noisy contours)
                // and be convex.
                // Note: absolute value of an area is used because
                // area may be positive or negative - in accordance with the
                // contour orientation
                if( approx.size() == 4 &&
                    fabs(contourArea(Mat(approx))) > 1000 &&
                    isContourConvex(Mat(approx)) )
                {
                    double maxCosine = 0;

                    for( int j = 2; j < 5; j++ )
                    {
                        // find the maximum cosine of the angle between joint edges
                        double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
                        maxCosine = MAX(maxCosine, cosine);
                    }

                    // if cosines of all angles are small
                    // (all angles are ~90 degree) then write quandrange
                    // vertices to resultant sequence
                    if( maxCosine < 0.3 )
                        squares.push_back(approx);
                }
            }
        }
    }
}


// the function draws all the squares in the image
void drawSquares( Mat& image, const vector<vector<Point> >& squares )
{
    for( size_t i = 1; i < squares.size(); i++ )
    {
        const Point* p = &squares[i][0];
        int n = (int)squares[i].size();
        polylines(image, &p, &n, 1, true, Scalar(0,255,0), 3, CV_AA);
    }

    imshow(wndname, image);
}


int main(int argc, char** argv)
{
    if (argc < 2)
    {
        cout << "Usage: ./program <file>" << endl;
        return -1;
    }

    static const char* names[] = { argv[1], 0 };

    help();
    namedWindow( wndname, 1 );
    vector<vector<Point> > squares;

    for( int i = 0; names[i] != 0; i++ )
    {
        Mat image = imread(names[i], 1);
        if( image.empty() )
        {
            cout << "Couldn't load " << names[i] << endl;
            continue;
        }

        findSquares(image, squares);
        drawSquares(image, squares);
        imwrite("out.jpg", image);

        int c = waitKey();
        if( (char)c == 27 )
            break;
    }

    return 0;
}
票数 4
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页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接:

https://stackoverflow.com/questions/1462104

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