Delaunay Triangulation of a point set, and then selects edges of that triangulation as possible reconstruction of curves from which the point set has been sampled. For the construction of the Delaunay Triangulation, we used the edge-flipping algorithm, for the curve reconstruction you are welcome to try out algorithms, the simplest is to select for each point at least the edge to its nearest neighbor, and for those points that are of degree one after this stage, the second-shortest incident edge, if it is not too long. The underlying set may have multiple curves, and curves with endpoints as well as closed curves. The program is called with a command line argument, the name of the input file, which contains the points in the format P (12,345) with one point per line. All point coordinates are integers. Your program opens a window, using the xlib system, and shows the points as black dots, the Delaunay edges as blue lines, and the selected Delaunay-edges of the curve reconstruction as red lines.
Image Data Visualization for a Project Category: Artificial Intelligence, Deep Learning, Machine Learning (ML), Microsoft PowerBI, Python Budget: ₹100 - ₹400 INR
