Comparisons of Reasoning Mechanisms for Computer Vision
Ze-Nian Li
TL;DR
This paper compares different reasoning mechanisms, including Dempster-Shafer theory, Bayesian formalism, and weight combination, for their effectiveness in real-world image analysis tasks.
Contribution
It introduces an evidential reasoning mechanism based on Dempster-Shafer theory and evaluates its performance against other established methods.
Findings
Dempster-Shafer based reasoning performs competitively in image analysis.
Bayesian formalism shows strengths in certain scenarios.
Weight combination method offers a simple alternative.
Abstract
An evidential reasoning mechanism based on the Dempster-Shafer theory of evidence is introduced. Its performance in real-world image analysis is compared with other mechanisms based on the Bayesian formalism and a simple weight combination method.
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Taxonomy
TopicsImage Retrieval and Classification Techniques · Rough Sets and Fuzzy Logic · Medical Image Segmentation Techniques