Letters: A class of binary images thinning using two PCNNs

Authors:
Lifeng Shang;Zhang Yi
Affiliations:
Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China
Venue:
Neurocomputing
Year:
2007

Citing 11
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Image thinning using pulse coupled neural network

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Image Processing Using Pulse-Coupled Neural Networks

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Perfect image segmentation using pulse coupled neural networks

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Finding the shortest path in the shortest time using PCNN's

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Foveation by a pulse-coupled neural network

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Implementation of parallel thinning algorithms using recurrent neural networks

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A mixed noise image filtering method using weighted-linking PCNNs

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Constrained ZIP code segmentation by a PCNN-based thinning algorithm

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Review article: Review of pulse-coupled neural networks

Image and Vision Computing
Review: Pulse coupled neural networks and its applications

Expert Systems with Applications: An International Journal

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Abstract

This paper proposes a new algorithm for a class of binary images thinning by using two PCNNs (pulse coupled neural networks). Once the travelling pulses of the two PCNNs meet, the thinning result is obtained. The criterion of pulses meeting is given, and the parameters of the PCNNs are also specified, which make the implementation of the proposed thinning algorithm easier. The algorithm is used to thin such a class of binary images, which separate the original images into two regions, as circularity-like images and ribbon-like shapes. Experimental results show that the proposed algorithm is efficient in extracting the skeleton of images (such as circularity-like images, ribbon-like shapes, handwriting '0', etc.).