DocumentCode :
3598876
Title :
Modular neural net architecture for one-step thinning algorithm
Author :
Lee, Jin-Ho ; Park, Dong-Sun
Author_Institution :
Dept. of Inf. & Commun. Eng., Chonbuk Nat. Univ., Chonju, South Korea
Volume :
4
fYear :
1995
Firstpage :
1719
Abstract :
A one-step parallel thinning algorithm using a deletion operator with 25 reference pixels and its neural implementation are presented. The one-step algorithm is an improved version of the previous parallel thinning algorithms in terms of the speed of the thinning process and the quality of thinned results. An efficient 2-layer neural net implementation of the one-step thinning algorithm is presented. The network consists of a module trained with the backpropagation learning rule and modules with hand-crafted weights
Keywords :
image processing; multilayer perceptrons; parallel algorithms; recurrent neural nets; 2-layer neural net; backpropagation learning rule; deletion operator; hand-crafted weight; modular neural net architecture; one-step parallel thinning algorithm; Algorithm design and analysis; Character recognition; Costs; Image analysis; Image processing; Image segmentation; Neural networks; Parallel algorithms; Skeleton; Structural shapes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488879
Filename :
488879
Link To Document :
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