contour

I found this code to get a skeletonized image. I have a circle image ( https://docs.google.com/file/d/0ByS6Z5WRz-h2RXdzVGtXUTlPSGc/edit?usp=sharing ). img = cv2.imread(nomeimg,0) size = np.size(img) skel = np.zeros(img.shape,np.uint8) ret,img = cv2.threshold(img,127,255,0) element = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3)) done = False while( not done): eroded = cv2.erode(img,element) temp = cv2.dilate(eroded,element) temp = cv2.subtract(img,temp) skel = cv2.bitwise_or(skel,temp) img = eroded.copy() zeros = size - cv2.countNonZero(img) if zeros==size: done = True print("skel") print

This must be simple for C++ developers using OpenCV directly. However what I'm using is Emgu (an OpenCV wrapper for .NET) and in the latest version we have the method CvInvoke.FindContours returning void, the output result is passed by parameter reference and is of type VectorOfVectorOfPoint . Here is a simple call: //outputResult is a VectorOfVectorOfPoint CvInvoke.FindContours(inputImage, outputResult, null, RetrType.Tree, ChainApproxMethod.ChainApproxSimple); For RetrType.List mode, we can just convert the result to some array of arrays and loop through all the contours easily. However here

I am trying to figure out a way to get the area inside a specific contour line? I use matplotlib.pyplot to create my contours. Does anyone have experience for this? Thanks a lot. From the collections attribute of the contour collection, which is returned by the contour function, you can get the paths describing each contour. The paths' vertices attributes then contain the ordered vertices of the contour. Using the vertices you can approximate the contour integral 0.5*(x*dy-y*dx), which by application of Green's theorem gives you the area of the enclosed region. However, the contours must be

I have an implicit scalar field defined in 2D, for every point in 2D I can make it compute an exact scalar value but its a somewhat complex computation. I would like to draw an iso-line of that surface, say the line of the '0' value. The function itself is continuous but the '0' iso-line can have multiple continuous instances and it is not guaranteed that all of them are connected. Calculating the value for each pixel is not an option because that would take too much time - in the order of a few seconds and this needs to be as real time as possible. What I'm currently using is a recursive

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

I'm using OpenCV (Canny + findCountours) to find external contours of objects. The curve drawn is typically almost, but not entirely, closed. I'd like to close it - to find the region it bounds. How do I do this? Things considered: Dilation - the examples I've seen show this after Canny, although it would seem to me it makes more sense to do this after findContours Convex hull - might work, though I'm really trying to complete a curve Shape simplification - related, but not exactly what I want Using PolyLine method to draw contours cv2.PolyLine(img, points, is_closed=True, 255, thickness=1,