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Fitting two concentric spheres to data by orthogonal distance regression
I. A. Al-Subaihi
; Department of Science, King Abdulaziz Military Academy, Riyadh, K.S.A.
Puni tekst: pdf (108 KB),
Str. 233 - 239
The problem of this research tackles the process of
fitting two concentric spheres to data, which arises in
computational metrology. There are also many fitting criteria that
could be used effectively, and the most widely used one in
metrology, for example, is that of the sum of squared minimal
distance. However, a simple and robust algorithm assigned for
using the orthogonal distance regression will be proposed in this
paper. A common approach to this problem involves an iteration
process which forces orthogonality to hold at every iteration and
steps of Gauss-Newton type.
concentric spheres, orthogonal distance regression, Gauss-Newton method
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