opencv 文字分割

看了一些文字分割的代码原来这么简单。

using cpoints = vector<Point>;
cv::Mat fore_ground_extract(cv::Mat const &input)
{
    vector<Mat> bgr;
    split(input, bgr);

    //process on blue channel as andrew suggest, because it is
    //easier to get rid of vegetation
    Mat text_region = bgr[0];
    medianBlur(text_region, text_region, 1);
    threshold(text_region, text_region, 0, 255, cv::THRESH_OTSU);

    //further remove small noise, unwanted border
    Mat const erode_kernel = getStructuringElement(MORPH_ELLIPSE, {9, 9});
    erode(text_region, text_region, erode_kernel);
    Mat const dilate_kernel = getStructuringElement(MORPH_ELLIPSE, {7, 7});
    dilate(text_region, text_region, dilate_kernel);

    //change the text from black to white, easier to extract as contours
    bitwise_not(text_region, text_region);

    return text_region;
}

std::vector<std::vector<cv::Point>> get_text_contours(cv::Mat const &input)
{
    //Find the contours of candidate text, remove outlier with
    //some contour properties
    //Try ERFilter of opencv if accuracy of this solution is low
    vector<cpoints> contours;
    findContours(input, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);
    auto outlier = [](cpoints const &cp)
    {
        auto const rect = cv::boundingRect(cp);

        return rect.width > rect.height && (rect.area() < 100 || rect.area() >= 10000);
    };
    auto it = std::remove_if(std::begin(contours), std::end(contours), outlier);
    contours.erase(it, std::end(contours));

    std::sort(std::begin(contours), std::end(contours), [](cpoints const &lhs, cpoints const &rhs)
              {
                  return cv::boundingRect(lhs).x < cv::boundingRect(rhs).x;
              });

    return contours;
}

int main()
{
     Mat input = imread("/tmp/0.png");
     Mat const text_region = fore_ground_extract( input );

    vector<cpoints> const text_contours = get_text_contours( text_region );
    //imshow("2", text_region);
    //waitKey();

    Mat text_mask(text_region.size(), CV_8UC3);
    for(size_t i = 0; i < text_contours.size(); ++i)
     {
        Scalar const color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
        drawContours(text_mask, text_contours, static_cast<int>(i), color, 2);
        auto const text_loc = boundingRect(text_contours[i]);
        //crop_region can gain highest accuracy since it is trained on scene image
        rectangle(input, text_loc, color, 2);

        imshow("text_mask", text_mask);
        imshow("crop_region", input(text_loc));
        waitKey();
     }

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