Implementation of parallel thinning algorithms using recurrent neural networks

Authors:
R. Krishnapuram;L. -F. Chen
Affiliations:
Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO;-
Venue:
IEEE Transactions on Neural Networks
Year:
1993

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Abstract

The use of recurrent neural networks for skeletonization and thinning of binary images is investigated. The networks are trained to learn a deletion rule and they iteratively delete object pixels until only the skeleton remains. Recurrent neural network architectures that implement a variety of thinning algorithms, such as the Rosenfeld-Kak algorithm and the Wang-Zhang (WZ) algorithm, are presented. A modified WZ algorithm which produces skeletons that are intuitively more pleasing is introduced