Title :
Fast algorithm for ISE-bounded polygonal approximation
Author :
Kolesnikov, Alexander
Author_Institution :
Dept. of Comput. Sci. & Stat., Univ. of Joensuu, Joensuu
Abstract :
In this paper we consider a problem of optimal polygonal approximation with a minimum number of the line segments for a given constraint on the total distortion with L2 measure. A fast suboptimal algorithm for the problem is proposed. In order to improve the solution obtained, this algorithm can be used in combination with a Reduced-Search Dynamic Programming algorithm. The experiments with the large size vector data have demonstrated both high efficiency and high time performance of the proposed algorithms for the following practical applications: image vectorization and segmentation, vector maps simplification, vector data compression, digital shapes encoding, etc.
Keywords :
approximation theory; data compression; dynamic programming; image coding; image segmentation; digital shapes encoding; image segmentation; image vectorization; line segments; polygonal approximation; reduced-search dynamic programming; vector data compression; vector maps simplification; Approximation algorithms; Approximation error; Data compression; Distortion measurement; Dynamic programming; Heuristic algorithms; Image analysis; Image coding; Lagrangian functions; Shape; Data compression; Dynamic programming; Image shape analysis; Polygonal approximation;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4711929