Nina's profile - activity

cv::Mat image;
UIImageToMat(input, image, false);
cv::Mat binary;
cv::cvtColor(image, binary, COLOR_BGR2GRAY);
cv::threshold(binary, binary, 100, 255, THRESH_BINARY);

    // Eliminate noise and smaller objects
cv::Mat fg;
cv::erode(binary,fg,cv::Mat(),cv::Point(-1,-1),2);

    // Identify image pixels without objects
cv::Mat bg;
cv::dilate(binary,bg,cv::Mat(),cv::Point(-1,-1),3);
cv::threshold(bg,bg,1, 128,cv::THRESH_BINARY_INV);

    // Create markers image
markers= fg+bg;
    // Create watershed segmentation object
WatershedSegmenter segmenter;
segmenter.setMarkers(markers);

cv::Mat result = segmenter.process(image);
result.convertTo(result,CV_8U);
return MatToUIImage(result);

class WatershedSegmenter{
private:
cv::Mat markers;
public:
void setMarkers(cv::Mat& markerImage)
{
markerImage.convertTo(markers, CV_32S);
}

cv::Mat process(cv::Mat &image)
{
cv::watershed(image, markers);
markers.convertTo(markers,CV_8U);
return markers;
}
};

While learning about OpenCV I came across the topic of segmentation, and found a thread here. I tried my hand at the provided answer and got the following error,

OpenCV Error: Assertion failed (src.type() == CV_8UC3 && dst.type() == CV_32SC1) in watershed, file /Users/siva/working/opencv/modules/imgproc/src/segmentation.cpp, line 147

And couldn't figure out a solution as I'm new to this topic. Any suggestions/solutions please?

It looked so. I wasn't sure about it. So I again performed canny, findContours, fillContours on the result from above code. The result was same as earlier.

@StevenPuttemans Nope. That gives the same result.

Complete Code

cv::Mat img, output;
UIImageToMat(input, img, false);

cv::Mat grayed;
cv::cvtColor(img, grayed, COLOR_BGR2GRAY);
cv::GaussianBlur(grayed, grayed, cv::Size(7, 7), 2);

int erosion_size = 1;
cv::Mat element = cv::getStructuringElement(0, cv::Size(erosion_size + 1, erosion_size + 1), cv::Point(1, 1));
cv::Mat temp;

cv::morphologyEx(grayed, temp, MORPH_GRADIENT, element);
cv::Mat dilateKernel(cv::Size(7, 7), CV_8UC1, cv::Scalar(1));
cv::dilate(temp, temp, dilateKernel);
cv::bitwise_not(temp, temp);
adaptiveThreshold(~temp, temp, 255, ADAPTIVE_THRESH_MEAN_C, 0, 207, -2);

    //skel
cv::Mat skel(grayed.size(), CV_8UC1, cv::Scalar(0));
cv::Mat temp1(grayed.size(), CV_8UC1);
cv::Mat element1 = cv::getStructuringElement(cv::MORPH_CROSS, cv::Size(3, 3));
bool done;
do {
    cv::morphologyEx(temp, temp1, cv::MORPH_OPEN, element1);
    cv::bitwise_not(temp1, temp1);
    cv::bitwise_and(temp, temp1, temp1);
    cv::bitwise_or(skel, temp1, skel);
    cv::erode(temp, temp, element1);

    double max;
    cv::minMaxLoc(temp, 0, &max);
    done = (max == 0);

} while (!done);

    //contour
vector<vector<cv::Point> > contours;
vector<Vec4i> hierarchy;
findContours( skel, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE);

Mat drawing = Mat::zeros( skel.size(), CV_8UC3 );

for( int i = 0; i< contours.size(); i++ ) {

    std::vector<cv::Point> contour_line;
    cv::approxPolyDP(cv::Mat(contours[i]), contour_line, 5, true);
    int nc = (int)contour_line.size();
    const cv::Point * pc = &(contour_line[0]);
    cv::polylines( drawing, &pc, &nc, 1, 0, cv::Scalar(255, 255, 255), nc, FILLED);
    drawContours(drawing, contours, i, Scalar(200, 200, 0), FILLED);
}
return MatToUIImage(drawing);

Question

I have followed this tutorial for Morphological Skeleton. The input and the skeleton result are here.

After performing morphological Skeleton operation, I'm processing findContours and filling it with drawContours. However the end result is not as expected. It thickens the border of each letter instead of filling. Could anyone advice what am I missing? Or do I need to perform any other operation instead of drawContours?

Note: This is most likely a follow-up question of my previous one.

Thank you! I will try the suggested solution..

For cvtColor code 0 is COLOR_BGR2BGRA? It works only if I change it to Grayscale. And the text "2" on top left and its background is just reversed. Is there any solution for it?

@LBerger Thank you! The result image is too perfect. But I couldn't understand the xml, as I'm fairly new to opencv. Is it possible for a pseudo-code or something?