Image identification and estimation using the maximum entropy principle
Pattern Recognition Letters
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Color Image Segmentation Using Inhibitory Connected Pulse Coupled Neural Network
Advances in Neuro-Information Processing
IEEE Transactions on Neural Networks
Physiologically motivated image fusion for object detection using a pulse coupled neural network
IEEE Transactions on Neural Networks
Implementation of pulse-coupled neural networks in a CNAPS environment
IEEE Transactions on Neural Networks
Perfect image segmentation using pulse coupled neural networks
IEEE Transactions on Neural Networks
Object detection using pulse coupled neural networks
IEEE Transactions on Neural Networks
A novel method for palmprint feature extraction based on modified pulse-coupled neural network
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
An Iterative Thresholding Segmentation Model Using a Modified Pulse Coupled Neural Network
Neural Processing Letters
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PCNN is a novel neural network model to simulate the synchronous phenomenon in the visual cortex system of the mammals. It has been widely used in the field of image processing and pattern recognition. However, there are still some limitations when it is applied to solve image processing problems, such as trial-and-error parameter settings and manually selection of the final results. This paper studies a simple model of PCNN(S-PCNN) and applies it to image segmentation. The main contributions of this paper are: (1) A new method based on the simplified model of PCNN is proposed to segment the images automatically. (2) The parameter settings are studied to ensure that the threshold decay of S-PCNN would be adaptively adjusted according to the overall characteristics of the image. (3) Based on the time series in S-PCNN, a simple selection criteria for the final results is presented to promote efficiency of the proposed method. (4) Simulations are carried out to illustrate the performance of the proposed method.