Book ChapterDOI
Color Image Segmentation Using Gaussian Mixture Model and EM Algorithm
Zhaoxia Fu,Liming Wang +1 more
- Vol. 346, pp 61-66
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TLDR
The method uses Gaussian mixture models to model the original image, and transforms segmentation problem into the maximum likelihood parameter estimation by expectation-maximization (EM) algorithm, and using the method to classify their pixels of the image can be resolved to some extent.Abstract:
The segmentation of color image is an important research field of image processing and pattern recognition A color image could be considered as the result from Gaussian mixture model (GMM) to which several Gaussian random variables contribute In this paper, an efficient method of image segmentation is proposed The method uses Gaussian mixture models to model the original image, and transforms segmentation problem into the maximum likelihood parameter estimation by expectation-maximization (EM) algorithm And using the method to classify their pixels of the image, the problem of color image segmentation can be resolved to some extent The experiment results confirm this method validityread more
Citations
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Journal ArticleDOI
Plant disease leaf image segmentation based on superpixel clustering and EM algorithm
TL;DR: A novel segmentation method based on a hybrid clustering that can provide useful clustering cues to guide image segmentation to accelerate the convergence speed of the expectation maximization (EM) algorithm.
Journal ArticleDOI
Fusion of superpixel, expectation maximization and PHOG for recognizing cucumber diseases
TL;DR: Experimental results show the proposed method, combining superpixels, expectation maximization (EM) algorithm, and logarithmic frequency pyramid of histograms of orientation gradients (PHOG), to recognize cucumber diseases is effective and feasible.
Journal ArticleDOI
Optimizing the Formation of DMAs in a Water Distribution Network through Advanced Modelling
TL;DR: In this article, a hybrid, two-stage approach is proposed to provide optimal separation of a WDN into district metered areas (DMAs), improving both water age and pressure.
Journal ArticleDOI
Uncertainty Estimation for Ultrasonic Inspection of Composite Aerial Structures
TL;DR: A comparative analysis of various image segmentation methods in the light of accuracy of damage detection in ultrasonic C-Scans of composite structures is presented and the most suitable approaches are introduced.
Journal ArticleDOI
Image segmentation using fuzzy competitive learning based counter propagation network
TL;DR: A hybrid Fuzzy Competitive Learning based Counter Propagation Network (FCPN) is proposed for the segmentation of natural scene images that compromises of the uncertainty handling capabilities of the fuzzy system and proficiency of parallel learning ability of neural network.
References
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Proceedings ArticleDOI
Gaussian mixture models of texture and colour for image database retrieval
TL;DR: Gaussian mixture models of 'structure' and colour features are introduced in order to classify coloured textures in images, with a view to the retrieval of textured colour images from databases.
Journal ArticleDOI
Statistical physics, mixtures of distributions, and the EM algorithm
TL;DR: There are strong relationships between approaches to optmization and learning based on statistical physics or mixtures of experts, and the EM algorithm can be interpreted as converging either to a local maximum of the mixtures model or to a saddle point solution to the statistical physics system.
BookDOI
Computational and Information Science
Jun Zhang,Ji-Huan He,Yuxi Fu +2 more
TL;DR: The authors may not be able to make you love reading, but computational and information science first international symposium cis 2004 shanghai china december 16 18 2004 proceedings will lead you to love reading starting from now.
Proceedings ArticleDOI
Recovery of egomotion and segmentation of independent object motion using the em-algorithm
TL;DR: Two new methods, based on the EM algorithm, are proposed to perform robust motion segmentation on image sequences that contain IMOs and tracks depth-structure over time and evaluates rigidity allowing IMOs to be identified as outliers.
Journal ArticleDOI
Registering incomplete radar images using the EM algorithm
Simon Moss,Edwin R. Hancock +1 more
TL;DR: The Levenberg-Marquardt optimisation method is adopted to reduce the local convergence difficulties posed by these local rotation maxima and is demonstrated to be relatively insensitive to random measurement errors on the line-segments.