Question

@robot_sherrick answered me this question, this is a follow-up question for his answer.

cv::SimpleBlobDetector in Opencv 2.4 looks very exciting but I am not sure I can make it work for more detailed data extraction.

I have the following concerns:

• if this only returns center of the blob, I can’t have an entire, labelled Mat, can I?
• how can I access the features of the detected blobs like area, convexity, color and so on?
• can I display an exact segmentation with this? (like with say, waterfall)

Answer 1

So the code should look something like this:

cv::Mat inputImg = imread(image_file_name, CV_LOAD_IMAGE_COLOR);   // Read a file
cv::SimpleBlobDetector::Params params; 
params.minDistBetweenBlobs = 10.0;  // minimum 10 pixels between blobs
params.filterByArea = true;         // filter my blobs by area of blob
params.minArea = 20.0;              // min 20 pixels squared
params.maxArea = 500.0;             // max 500 pixels squared
SimpleBlobDetector myBlobDetector(params);
std::vector<cv::KeyPoint> myBlobs;
myBlobDetector.detect(inputImg, myBlobs);

If you then want to have these keypoints highlighted on your image:

cv::Mat blobImg;    
cv::drawKeypoints(inputImg, myBlobs, blobImg);
cv::imshow("Blobs", blobImg);

To access the info in the keypoints, you then just access each element like so:

for(std::vector<cv::KeyPoint>::iterator blobIterator = myBlobs.begin(); blobIterator != myBlobs.end(); blobIterator++){
   std::cout << "size of blob is: " << blobIterator->size << std::endl;
   std::cout << "point is at: " << blobIterator->pt.x << " " << blobIterator->pt.y << std::endl;
} 

Note: this has not been compiled and may have typos.