Title :
Fast thinning algorithm based on improved SOG (SOG*)
Author :
Lee, Chan-Hee ; Jung, Soon-Ho
Author_Institution :
Dept. of Comput. Sci., PuKyong Nat. Univ., Pusan, South Korea
Abstract :
We propose improved self-organized graph (improved SOG: SOG ) thinning method, which maintains excellent thinning results of self-organized graph (SOG) built from self-organizing features map and improves the performance of the existing SOG by using a new incremental learning method of Kohonen features map. In the experiments, this method shows the thinning results to be equal to those of SOG but the time complexity O((logM)3) to be superior to that of SOG. Therefore, the proposed method is useful for the feature extraction from digits and characters in the preprocessing step.
Keywords :
computational complexity; feature extraction; image thinning; learning (artificial intelligence); self-organising feature maps; Kohonen features map; fast thinning algorithm; feature extraction; improved SOG; improved self-organized graph; incremental learning method; self-organizing features map; Character recognition; Computer science; Data mining; Equations; Image recognition; Maintenance engineering; Neural networks; Neurons; Pattern recognition; Telecommunication computing;
Conference_Titel :
Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE
Print_ISBN :
0-7803-8730-9
DOI :
10.1109/IECON.2004.1432140