OpenCV - Distance Transformation
www.tutorialspoint.com › opencv › opencv_distanceThe distance transform operator generally takes binary images as inputs. In this operation, the gray level intensities of the points inside the foreground regions are changed to distance their respective distances from the closest 0 value (boundary). You can apply distance transform in OpenCV using the method distanceTransform(). Following is the syntax of this method.
Distance transform - Wikipedia
https://en.wikipedia.org/wiki/Distance_transformA distance transform, also known as distance map or distance field, is a derived representation of a digital image. The choice of the term depends on the point of view on the object in question: whether the initial image is transformed into another representation, or it is simply endowed with an additional map or field. Distance fields can also be signed, in the case where it is important to distinguish whether the p…
The Euclidean Distance Transform (Thesis)
https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1970&context…1.1 The Euclidean Distance Function and Distance Transform Many distance functions, such as cityblock distance, chessboard distance, chamfer distance, octagonal distance, and quasi-Euclideandistance, have been used for digital image processing [7, 8, 46, 60, 14].
Distance Transform - Brown University
cs.brown.edu/people/pfelzens/dt28.12.2006 · Distance Transforms of Sampled Functions Below is a C++ implementation of the distance transform algorithm described in the paper: Distance Transforms of Sampled Functions P. Felzenszwalb, D. Huttenlocher Theory of Computing, Vol. 8, No. 19, September 2012 PDF.
OpenCV: Image Segmentation with Distance Transform and ...
docs.opencv.org › tutorial_distance_transformJan 08, 2013 · Use the OpenCV function cv::filter2D in order to perform some laplacian filtering for image sharpening. Use the OpenCV function cv::distanceTransform in order to obtain the derived representation of a binary image, where the value of each pixel is replaced by its distance to the nearest background pixel. Use the OpenCV function cv::watershed in order to isolate objects in the image from the background.