Image thresholding based on the EM algorithm and the generalized Gaussian distribution

Authors:
Yakoub Bazi;Lorenzo Bruzzone;Farid Melgani
Affiliations:
Department of Information and Communication Technologies, University of Trento, Via Sommarive, 14, I-38050, Trento, Italy;Department of Information and Communication Technologies, University of Trento, Via Sommarive, 14, I-38050, Trento, Italy;Department of Information and Communication Technologies, University of Trento, Via Sommarive, 14, I-38050, Trento, Italy
Venue:
Pattern Recognition
Year:
2007

Citing 18
Cited 21

Minimum error thresholding

Pattern Recognition
Numerical recipes in C: the art of scientific computing

Numerical recipes in C: the art of scientific computing
Automatic thresholding of gray-level pictures using two-dimensional entropy

Computer Vision, Graphics, and Image Processing
Performance study of several global thresholding techniques for segmentation

Computer Vision, Graphics, and Image Processing
Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
An analysis of histogram-based thresholding algorithms

CVGIP: Graphical Models and Image Processing
Maximum entropy segmentation based on the autocorrelation function of the image histogram

Journal of Computing and Information Technology
Bayesian Approaches to Gaussian Mixture Modeling

IEEE Transactions on Pattern Analysis and Machine Intelligence
Integral Ratio: A New Class of Global Thresholding Techniques for Handwriting Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Evaluation of global image thresholding for change detection

Pattern Recognition Letters
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
EM algorithm for image segmentation initialized by a tree structure scheme

IEEE Transactions on Image Processing
Adaptive thresholding by variational method

IEEE Transactions on Image Processing
Thresholding using two-dimensional histogram and fuzzy entropy principle

IEEE Transactions on Image Processing
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance

IEEE Transactions on Image Processing
An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images

IEEE Transactions on Image Processing
Image segmentation by histogram thresholding using fuzzy sets

IEEE Transactions on Image Processing

A novel image thresholding method based on Parzen window estimate

Pattern Recognition
A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation

Computer Vision and Image Understanding
Type-2 fuzzy Gaussian mixture models

Pattern Recognition
Fractional differentiation and non-Pareto multiobjective optimization for image thresholding

Engineering Applications of Artificial Intelligence
A fast estimation method for the generalized Gaussian mixture distribution on complex images

Computer Vision and Image Understanding
A thresholding method based on two-dimensional fractional differentiation

Image and Vision Computing
2009 Special Issue: Error-probability noise benefits in threshold neural signal detection

Neural Networks
Respiratory parameter estimation in non-invasive ventilation based on generalized Gaussian noise models

Signal Processing
Magnetic resonance image segmentation based on two-dimensional exponential entropy and a parameter free PSO

EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem

Engineering Applications of Artificial Intelligence
Unsupervised range-constrained thresholding

Pattern Recognition Letters
Bayesian learning of finite generalized Gaussian mixture models on images

Signal Processing
Ridler and Calvard's, Kittler and Illingworth's and Otsu's methods for image thresholding

Pattern Recognition Letters
Data field-based mechanism for three-dimensional thresholding

Neurocomputing
An improved MRF-based change detection approach for multitemporal remote sensing imagery

Signal Processing
Medical image thresholding using online trained neural networks

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Automatic iterative algorithm for image segmentation using a modified pulse-coupled neural network

Neurocomputing
Secure randomized image watermarking based on singular value decomposition

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A generalized multiclass histogram thresholding approach based on mixture modelling

Pattern Recognition
An Iterative Thresholding Segmentation Model Using a Modified Pulse Coupled Neural Network

Neural Processing Letters
Maximum similarity thresholding

Digital Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, a novel parametric and global image histogram thresholding method is presented. It is 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. The adoption of such a statistical model as an alternative to the more common Gaussian model is motivated by its attractive capability to approximate a broad variety of statistical behaviors with a small number of parameters. Since the quality of the solution provided by the iterative EM algorithm is strongly affected by initial conditions (which, if inappropriately set, may lead to unreliable estimation), a robust initialization strategy based on genetic algorithms (GAs) is proposed. Experimental results obtained on simulated and real images confirm the effectiveness of the proposed method.