About This Project
What are the aims of this project?
One aim of this research is to examine the use of mixture modelling as an approximation to an image's histogram in greater detail using an iterative approach, while also examining the suitability of the Kullback-Leibler information measure for use as a possible relative or objective criterion for assessment of threshold selection. Another aim is to test the classification program Snob, to find the appropriate number of classes in an image's histogram (and so find the best segmentation of the image), while also assessing the suitability of the Minimum Message Length criterion as an objective measure for assessing the quality of thresholding results. The overall aim is to compare and assess examples of the supervised and unsupervised techniques.
Huh? Maybe go to the glossary
Why is this research useful?
The assessment of thresholding results can be very subjective. Often the best way to see if an image have been segmented successfully is simply to look at the resulting image. Work in this area may eventaully provide an objective criterion to use for assessment of thresholding results.
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LAST UPDATED: 4 March 2003