Journal ArticleDOI
Image thresholding based on the EM algorithm and the generalized Gaussian distribution
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TLDR
A novel parametric and global image histogram thresholding method based on the estimation of the statistical parameters of ''object'' and ''background'' classes by the expectation-maximization (EM) algorithm, under the assumption that these two classes follow a generalized Gaussian (GG) distribution.About:
This article is published in Pattern Recognition.The article was published on 2007-02-01. It has received 238 citations till now. The article focuses on the topics: Balanced histogram thresholding & Thresholding.read more
Citations
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Journal ArticleDOI
Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data
TL;DR: An automatic near-real time (NRT) flood detection approach is presented, which combines histogram thresholding and segmentation based classification, specifically oriented to the analysis of single-polarized very high resolution Synthetic Aperture Radar (SAR) satellite data.
Journal ArticleDOI
Characterizing brain anatomical connections using diffusion weighted MRI and graph theory.
Yasser Iturria-Medina,Erick J. Canales-Rodríguez,Lester Melie-Garcia,Pedro A. Valdés-Hernández,Eduardo Martínez-Montes,Yasser Alemán-Gómez,Jose M. Sanchez-Bornot +6 more
TL;DR: A new methodology based on Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) and Graph Theory is presented for characterizing the anatomical connections between brain gray matter areas, showing that nervous fiber pathways between some regions of interest were reconstructed correctly.
Journal ArticleDOI
A Split-Based Approach to Unsupervised Change Detection in Large-Size Multitemporal Images: Application to Tsunami-Damage Assessment
TL;DR: Experimental results that are obtained on multitemporal RADARSAT-1 SAR images of the Sumatra Island, Indonesia, confirm the effectiveness of both the proposed SBA and the presented system for tsunami-damage assessment.
Journal ArticleDOI
A Novel Approach to Unsupervised Change Detection Based on a Semisupervised SVM and a Similarity Measure
TL;DR: This paper presents a novel approach to unsupervised change detection in multispectral remote-sensing images by using a selective Bayesian thresholding for deriving a pseudotraining set that is necessary for initializing an adequately defined binary semisupervised support vector machine classifier.
Journal ArticleDOI
A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation
TL;DR: Experiments and comparative results with multilevel thresholding methods over a synthetic histogram and real images show the efficiency of the proposed method.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
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