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EVG-THIN v1.1: A Thinning Approximation to the Extended Voronoi Graph Copyright (C) 2006 - Patrick Beeson (email@example.com) This program is released under the GNU General Public License (GPL). See COPYING for details. ---------------------------------- This program implements an extension of the pixel-based "thinning" algorithm that finds skeletons of bitmaps. The classic thinning algorithm is a fast approximation of the Voronoi diagram; however, this software also approximates the Extended Voronoi graph. This code was written to be applied in real-time to occupancy grids (from the mobile robotics literature) where cells are either occupied, free, or unknown, but it should work on bitmap images for other domains. Relevant Citations: Classic Thinning Algorithm: Zhang and Suen, 1984, "A Fast Parallel Algorithm for Thinning Digital Patterns." Communications of the ACM, vol. 27, no. 3, pp. 236-239. Extended Voronoi Graph: Beeson, Jong, and Kuipers, 2005, "Towards autonomous topological place detection using the Extended Voronoi Graph." IEEE International Conference on Robotics and Automation (ICRA-05). ---------------------------------- See CHANGELOG for revision notes. Installation ------------ $ make Running ------- $ ./test -image-file FILENAME1 <options> FILENAME1 must be a .ppm, .pgm, or .pnm file. options: -output-file FILENAME2 : By default the output file name is the input filename with '_skeleton.ppm' appended to the end. -min-unknown N : The minimum greyscale value (1-254) of unknown cells. Occupied cells are 0-(N-1). -max-unknown M : The maximum greyscale value (1-254) of unknown cells. Free cells are (M+1)-255. -pruning [0|1] : Turns pruning on or off. Pruning removes ALL "branches" of the skeleton EXCEPT those that meet one of these conditions: 1) The branch touches the edge of the grid, 2) the branch touches unknown cells. By default, pruning is on. -min-distance R : Bleeds obstacles by R cells before calculating skeleton. This removes branches that come too close to obstacles. -max-distance S : If the skeleton gets more the S cells from the nearest occupied cells, it switches to following the occupied cells S away. -robot_loc X Y : This location is used to select which skeleton is valid, given complex images with multiple, disjoint skeletons. By default, the "robot" is located at the center of the image. -robot-close [0|1] : The robot location (see above) is used to choose which skeleton is valid (if multiple exist). This is done by Euclidean distance between the robot's location at the skeletal points. This option turn off that checking except for points where the robot's distance is within the distance of the skeletal point to its closest obstacle. By default, this is turned on. Examples -------- $ ./test -image-file test1.pgm output : test1_skeleton.ppm Basically, the Voronoi graph of the local occupancy grid of a robot. $ ./test -image-file test2.pgm -output-file test2_outA.ppm output: test2_outA.ppm Notice that because the skeleton does not touch the edges (or unknown, grey cells), pruning removes the skeleton. $ ./ test -image-file test2.pgm -output-file test2_outB.ppm -pruning 0 output: test2_outB.ppm Because we turned off pruning, the skeleton now appears in the output image. $ ./ test -image-file test2.pgm -output-file test2_outC.ppm -pruning 0 -max_distance 10 -robot-close 0 output: test2_outC.ppm Here, we set a maximum distance the skeleton can be from occupied cells. Because the robot's location is by default at the center of the image, we turn off 'robot-close' because the robot is not with 10 cells of any point on the skeleton. Try turning 'robot-close' on (default) and the skeleton disappears in the output image. Even with -robot-close turned on, we can get the output to include the skeleton by using the 'robot-loc' option.