如何在OpenCV中过滤图像中的小段？

Question

我按以下方式打印轮廓：

std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
cv::findContours( mask, contours, hierarchy, cv::RETR_CCOMP, cv::CHAIN_APPROX_TC89_KCOS);
for ( size_t i=0; i<contours.size(); ++i )
{
    cv::drawContours( img, contours, i, Scalar(200,0,0), 1, 8, hierarchy, 0, Point() ); 
    cv::Rect brect = cv::boundingRect(contours[i]);
    cv::rectangle(img, brect, Scalar(255,0,0));
}

一旦我有了二进制图像，我想消除较小的轮廓。有关如何操作的任何建议吗？

我的输入图片：

我想要达到的目的：

修改

我正试图摆脱较小的细分市场。任何提示？

Answer 1

我已经构建了一个仅打印属于较大片段的点的函数。它使用pointPolygonTest，这是一个很棒的OpenCV函数，它可以说明一个点是在给定轮廓的内部，外部还是边界。看看：

// Gets only the biggest segments
Mat Morphology::threshSegments(Mat &src, double threshSize) {
    // FindContours:
    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;
    Mat srcBuffer, output;
    src.copyTo(srcBuffer);
    findContours(srcBuffer, contours, hierarchy, cv::RETR_CCOMP, cv::CHAIN_APPROX_TC89_KCOS);

    vector<vector<Point> > allSegments;

    // For each segment:
    for (size_t i = 0; i < contours.size(); ++i) {
        cv::drawContours(srcBuffer, contours, i, Scalar(200, 0, 0), 1, 8, hierarchy, 0, Point());
        cv::Rect brect = cv::boundingRect(contours[i]);
        cv::rectangle(srcBuffer, brect, Scalar(255, 0, 0));

        int result;
        vector<Point> segment;
        for (unsigned int row = brect.y; row < brect.y + brect.height; ++row) {
            for (unsigned int col = brect.x; col < brect.x + brect.width; ++col) {
                result = pointPolygonTest(contours[i], Point(col, row), false);
                if (result == 1 || result == 0) {
                    segment.push_back(Point(col, row));
                }
            }
        }
        allSegments.push_back(segment);
    }

    output = Mat::zeros(src.size(), CV_8U);
    int totalSize = output.rows*output.cols;
    for (int segmentCount = 0; segmentCount < allSegments.size(); ++segmentCount) {
        vector<Point> segment = allSegments[segmentCount];
        if(segment.size() > totalSize*threshSize){
            for (int idx = 0; idx < segment.size(); ++idx) {
                output.at<uchar>(segment[idx].y, segment[idx].x) = 255;
            }
        }
    }

    return output;
}

Answer 2

我建议使用形态学开口去除较小的斑点，然后填充形态学孔。