PROJECT TITLE :
Comparison of Data With Multiple Degrees of Freedom Utilizing the Feature Selective Validation Method
ABSTRACT:
The feature selective validation methodology has been shown to produce results that are in broad agreement with the visual assessment of a cluster of engineers for line, one-D, information. An implementation using 2-D Fourier transforms and derivatives are obtainable for a few years, but verification of the performance has been difficult to obtain. More, that approach does not naturally scale well for three-D and higher degrees of freedom, significantly if there are sizable variations in the quantity of points in the various directions. This paper describes an approach primarily based on repeated 1-D FSV analyses that overcomes those challenges. The flexibility of the two-D case to mirror user perceptions is demonstrated using the LIVE database. Its extension to n-dimensions is also described and includes a suggestion for weighting the algorithm based on the quantity of knowledge points during a given “direction.”
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