OpenCV C++/Obj-C:连接附近的轮廓

发布于 2024-12-28 14:36:03 字数 1009 浏览 1 评论 0 原文

是否有连接两个(或多个)附近轮廓的功能?看看我的输入/输出,你就会明白我的意思......

我的代码:

[... some processing ...]

// getting contours
std::vector<std::vector<cv::Point> > contours;
findContours(input, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

// approximate contours
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
for( int i = 0; i < contours.size(); i++ ) {
  approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 5, true );
}

// debugging
cv::Scalar colors[3];
colors[0] = cv::Scalar(255, 0, 0);
colors[1] = cv::Scalar(0, 255, 0);
colors[2] = cv::Scalar(0, 0, 255);
for (int idx = 0; idx < contours_poly.size(); idx++) {
  cv::drawContours(output, contours_poly, idx, colors[idx % 3]);
} 

输出

Is there a function to connect two (or more) nearby contours? Take a look at my in-/output and you'll see what I mean …

My code:

[... some processing ...]

// getting contours
std::vector<std::vector<cv::Point> > contours;
findContours(input, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

// approximate contours
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
for( int i = 0; i < contours.size(); i++ ) {
  approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 5, true );
}

// debugging
cv::Scalar colors[3];
colors[0] = cv::Scalar(255, 0, 0);
colors[1] = cv::Scalar(0, 255, 0);
colors[2] = cv::Scalar(0, 0, 255);
for (int idx = 0; idx < contours_poly.size(); idx++) {
  cv::drawContours(output, contours_poly, idx, colors[idx % 3]);
} 

output
output

如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。

扫码二维码加入Web技术交流群

发布评论

需要 登录 才能够评论, 你可以免费 注册 一个本站的账号。

评论(2

蒗幽 2025-01-04 14:36:03

我想出了这个解决方案,因为我只需要整个对象周围的边界框:

[... some processing ...]

// getting contours
std::vector<std::vector<cv::Point> > contours;
findContours(input, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

// approximate contours
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
for( int i = 0; i < contours.size(); i++ ) {
  approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 5, true );
}

// merge all contours into one vector
std::vector<cv::Point> merged_contour_points;
for (int i = 0; i < contours_poly.size(); i++) {
  for (int j = 0; j < contours_poly[i].size(); j++) {
    merged_contour_points.push_back(contours_poly[i][j]);
  }
}

// get rotated bounding box
std::vector<cv::Point> hull;
cv::convexHull(cv::Mat(merged_contour_points),hull);
cv::Mat hull_points(hull);
cv::RotatedRect rotated_bounding_rect = minAreaRect(hull_points);

有时消除胡椒噪声可以带来更好的结果:

void removePepperNoise(cv::Mat &mask)
{
    for ( int y=2; y<mask.rows-2; y++ ) {
        uchar *pUp2 = mask.ptr(y-2);
        uchar *pUp1 = mask.ptr(y-1);
        uchar *pThis = mask.ptr(y);
        uchar *pDown1 = mask.ptr(y+1);
        uchar *pDown2 = mask.ptr(y+2);
        pThis += 2;
        pUp1 += 2;
        pUp2 += 2;
        pDown1 += 2;
        pDown2 += 2;

        for (int x=2; x<mask.cols-2; x++) {
            uchar value = *pThis; // Get this pixel value (0 or 255). // Check if this is a black pixel that is surrounded by white pixels
            if (value == 0) {
                bool above, left, below, right, surroundings;
                above = *(pUp2 - 2) && *(pUp2 - 1) && *(pUp2) && *(pUp2 + 1) && *(pUp2 + 2);
                left = *(pUp1 - 2) && *(pThis - 2) && *(pDown1 - 2);
                below = *(pDown2 - 2) && *(pDown2 - 1) && *(pDown2) && *(pDown2 + 1) && *(pDown2 + 2);
                right = *(pUp1 + 2) && *(pThis + 2) && *(pDown1 + 2);
                surroundings = above && left && below && right;
                if (surroundings == true) {
                    // Fill the whole 5x5 block as white. Since we know
                    // the 5x5 borders are already white, we just need to
                    // fill the 3x3 inner region.
                    *(pUp1 - 1) = 255;
                    *(pUp1 + 0) = 255;
                    *(pUp1 + 1) = 255;
                    *(pThis - 1) = 255;
                    *(pThis + 0) = 255;
                    *(pThis + 1) = 255;
                    *(pDown1 - 1) = 255;
                    *(pDown1 + 0) = 255;
                    *(pDown1 + 1) = 255;
                    // Since we just covered the whole 5x5 block with
                    // white, we know the next 2 pixels won't be black,
                    // so skip the next 2 pixels on the right.
                    pThis += 2;
                    pUp1 += 2;
                    pUp2 += 2;
                    pDown1 += 2;
                    pDown2 += 2;
                }
            }
            // Move to the next pixel on the right.
            pThis++;
            pUp1++;
            pUp2++;
            pDown1++;
            pDown2++;
        }
    }
}

I came up with this solution, because I just need the bounding box around the whole object:

[... some processing ...]

// getting contours
std::vector<std::vector<cv::Point> > contours;
findContours(input, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);

// approximate contours
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
for( int i = 0; i < contours.size(); i++ ) {
  approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 5, true );
}

// merge all contours into one vector
std::vector<cv::Point> merged_contour_points;
for (int i = 0; i < contours_poly.size(); i++) {
  for (int j = 0; j < contours_poly[i].size(); j++) {
    merged_contour_points.push_back(contours_poly[i][j]);
  }
}

// get rotated bounding box
std::vector<cv::Point> hull;
cv::convexHull(cv::Mat(merged_contour_points),hull);
cv::Mat hull_points(hull);
cv::RotatedRect rotated_bounding_rect = minAreaRect(hull_points);

Sometimes removing pepper noise can lead to better results:

void removePepperNoise(cv::Mat &mask)
{
    for ( int y=2; y<mask.rows-2; y++ ) {
        uchar *pUp2 = mask.ptr(y-2);
        uchar *pUp1 = mask.ptr(y-1);
        uchar *pThis = mask.ptr(y);
        uchar *pDown1 = mask.ptr(y+1);
        uchar *pDown2 = mask.ptr(y+2);
        pThis += 2;
        pUp1 += 2;
        pUp2 += 2;
        pDown1 += 2;
        pDown2 += 2;

        for (int x=2; x<mask.cols-2; x++) {
            uchar value = *pThis; // Get this pixel value (0 or 255). // Check if this is a black pixel that is surrounded by white pixels
            if (value == 0) {
                bool above, left, below, right, surroundings;
                above = *(pUp2 - 2) && *(pUp2 - 1) && *(pUp2) && *(pUp2 + 1) && *(pUp2 + 2);
                left = *(pUp1 - 2) && *(pThis - 2) && *(pDown1 - 2);
                below = *(pDown2 - 2) && *(pDown2 - 1) && *(pDown2) && *(pDown2 + 1) && *(pDown2 + 2);
                right = *(pUp1 + 2) && *(pThis + 2) && *(pDown1 + 2);
                surroundings = above && left && below && right;
                if (surroundings == true) {
                    // Fill the whole 5x5 block as white. Since we know
                    // the 5x5 borders are already white, we just need to
                    // fill the 3x3 inner region.
                    *(pUp1 - 1) = 255;
                    *(pUp1 + 0) = 255;
                    *(pUp1 + 1) = 255;
                    *(pThis - 1) = 255;
                    *(pThis + 0) = 255;
                    *(pThis + 1) = 255;
                    *(pDown1 - 1) = 255;
                    *(pDown1 + 0) = 255;
                    *(pDown1 + 1) = 255;
                    // Since we just covered the whole 5x5 block with
                    // white, we know the next 2 pixels won't be black,
                    // so skip the next 2 pixels on the right.
                    pThis += 2;
                    pUp1 += 2;
                    pUp2 += 2;
                    pDown1 += 2;
                    pDown2 += 2;
                }
            }
            // Move to the next pixel on the right.
            pThis++;
            pUp1++;
            pUp2++;
            pDown1++;
            pDown2++;
        }
    }
}
无畏 2025-01-04 14:36:03

只需遍历点并找到最近的起点或终点,然后将它们连接起来即可。在您的情况下很难决定轮廓是否应该连接。如果 Adrian Popovici 所说的形态学没有帮助,您必须指定一些最大距离来决定点是否要连接。

Simply go through points and find the closest startpoints or endpoints and then connect them. It's hard to decide in your case if contours should be connected or not. If morfology as Adrian Popovici said doesn't help you must specify some max distance which decide if points are to be connected.

~没有更多了~
我们使用 Cookies 和其他技术来定制您的体验包括您的登录状态等。通过阅读我们的 隐私政策 了解更多相关信息。 单击 接受 或继续使用网站,即表示您同意使用 Cookies 和您的相关数据。
原文