Mixture Modeling

Mixture Modeling

Authors: Christopher Mei (christopher.mei at sophia.inria.fr), Maxime Dauphin

History: 2003/12/15 : First version

Requires: ImageJ 1.31p or later, which adds the ability to package plugins in JAR files

Source: Contained in Mixture_Modeling.jar, which can be opened using a ZIP utility

Installation: Download Mixture_Modeling.jar to the plugins folder, or subfolder, restart ImageJ, and there will be a new Plugins/Filters/Mixture Modeling... command.

Description: This algorithm separates the histogram of an image into two classes using a Gaussian model. It then calculates the image threshold as the intersection of these two Gaussians. This thresholding technique has the advantage of finding a threshold that is in certain cases closer to real world data. The Gaussian parameters can also be used to caracterise the two regions obtained.
The plugin returns a histogram with the two Gaussians, the parameters obtained (average, standard deviation, threshold) and the thresholded image.

The image on the left represents trees viewed on a Digital Elevation Model. This data can be quite well modeled by two Gaussians and the obtained threshold is satisfactory.

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Authors:	Christopher Mei (christopher.mei at sophia.inria.fr), Maxime Dauphin
History:	2003/12/15 : First version
Requires:	ImageJ 1.31p or later, which adds the ability to package plugins in JAR files
Source:	Contained in Mixture_Modeling.jar, which can be opened using a ZIP utility
Installation:	Download Mixture_Modeling.jar to the plugins folder, or subfolder, restart ImageJ, and there will be a new Plugins/Filters/Mixture Modeling... command.
Description:	This algorithm separates the histogram of an image into two classes using a Gaussian model. It then calculates the image threshold as the intersection of these two Gaussians. This thresholding technique has the advantage of finding a threshold that is in certain cases closer to real world data. The Gaussian parameters can also be used to caracterise the two regions obtained. The plugin returns a histogram with the two Gaussians, the parameters obtained (average, standard deviation, threshold) and the thresholded image.