Journal ArticleDOI
A New Automatic Parameter Setting Method of a Simplified PCNN for Image Segmentation
TLDR
The experimental segmentation results of the gray natural images from the Berkeley Segmentation Dataset, rather than synthetic images, prove the validity and efficiency of the proposed automatic parameter setting method of SPCNN.Abstract:
An automatic parameter setting method of a simplified pulse coupled neural network (SPCNN) is proposed here. Our method successfully determines all the adjustable parameters in SPCNN and does not need any training and trials as required by previous methods. In order to achieve this goal, we try to derive the general formulae of dynamic threshold and internal activity of the SPCNN according to the dynamic properties of neurons, and then deduce the sub-intensity range expression of each segment based on the general formulae. Besides, we extract information from an input image, such as the standard deviation and the optimal histogram threshold of the image, and attempt to build a direct relation between the dynamic properties of neurons and the static properties of each input image. Finally, the experimental segmentation results of the gray natural images from the Berkeley Segmentation Dataset, rather than synthetic images, prove the validity and efficiency of our proposed automatic parameter setting method of SPCNN.read more
Citations
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Journal ArticleDOI
Medical Image Fusion With Parameter-Adaptive Pulse Coupled Neural Network in Nonsubsampled Shearlet Transform Domain
TL;DR: Experimental results demonstrate that the proposed method can obtain more competitive performance in comparison to nine representative medical image fusion methods, leading to state-of-the-art results on both visual quality and objective assessment.
Journal ArticleDOI
Visual-Based Defect Detection and Classification Approaches for Industrial Applications-A SURVEY.
Tamas Czimmermann,Gastone Ciuti,Mario Milazzo,Marcello Chiurazzi,Stefano Roccella,Calogero Maria Oddo,Paolo Dario +6 more
TL;DR: This paper reviews automated visual-based defect detection approaches applicable to various materials, such as metals, ceramics and textiles, and describes artificial visual processing techniques that are aimed at understanding of the captured scenery in a mathematical/logical way.
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Breast mass classification in digital mammography based on extreme learning machine
Weiying Xie,Yunsong Li,Yide Ma +2 more
TL;DR: The results show that the proposed CAD system not only has good performance in terms of specificity, sensitivity and accuracy, but also achieves a significant reduction in training time compared with SVM and particle swarm optimization-support vector machine (PSO-SVM).
Journal ArticleDOI
Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review
TL;DR: Insight into the internal operations and behaviors of PCNN is provided, and the way how PCNN achieves good performance in digital image processing is revealed.
Journal ArticleDOI
MRI and SPECT Image Fusion Using a Weighted Parameter Adaptive Dual Channel PCNN
TL;DR: Experimental results demonstrate that the proposed method outperforms some of the state-of-the-art methods in terms of both visual quality and objective assessment.
References
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Normalized cuts and image segmentation
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Proceedings ArticleDOI
Normalized cuts and image segmentation
Jianbo Shi,Jitendra Malik +1 more
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Proceedings ArticleDOI
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
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Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex
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