Iterative version of Ramer-Douglas-Peucker line-simplification algorithm June 28, 2014. In one of our games we needed to beautify user mouse or touch input.Actually it isn’t simple task since there can be found many criteria due to point reduce.I have tried several solutions like discovering big angle change between segments (built of last given input points), big distance discovering.

Sample data of Douglas-Peucker algorithm parameter and certain attributes related to simplification quality is obtained by iteration method of simplification algorithm, Functions between threshold with line length, point number, and running time are get by curve fit, Through analyzing curvature of function between threshold with point number, function maximum curvature is confirmed and acts as.

The Douglas-Peucker Algorithm. The Douglas-Peucker algorithm is used to reduce the number of points in a line. It does so by discarding points that do not deviate significantly between its surrounding points. The amount a point may deviate before it is excluded is an input to the algorithm, and naturally will impact the number of points that.

I can't find any faults in your code. Some things to try: Add some debug print statements to check what maxDist is in the failing case. It should be really low, but if it comes out high then you know there's a problem with your line segment distance code.

Java Script Douglas-Peucker. If you try and load big GPX tracklogs they may well contain too much detail (too many short legs) for display as a GMaps GPolyline. To work around this, the point set needs to be thinned. The classic algorithm for this is known as the Douglas Peucker algorithm.

Simplify a 2D or 3D line. Implements the Ramer-Douglas-Peucker algorithm for simplifying a line defined by an ordered set of points, as described in Wikipedia: Ramer-Douglas-Peucker algorithm.

Douglas-Peucker algorithm is a good method for removing curve's noncharacteristic points and extracting characteristic points. This paper analyzes the efficiency of each step of buffer generalization and points out which procedures are time-consuming. Then this paper uses Douglas-Peucker algorithm to extract curve's characteristic points before buffer generating. The experimental results show.

It approximates a contour shape to another shape with less number of vertices depending upon the precision we specify. It is an implementation of Douglas-Peucker algorithm. Check the wikipedia page for algorithm and demonstration. We use the function: cv.approxPolyDP (curve, approxCurve, epsilon, closed) Parameters.