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Least-Squares Fitting Based on Algebraic Distances


As said before, for noisy data, the system equation, Q(x,y)=0 in the case of conic fitting, can hardly hold true. A common practice is to directly minimize the algebraic distance tex2html_wrap_inline2587 , i.e., to minimize the following function:


Clearly, there exists a trivial solution A=B=C=D=E=F=0. In order to avoid it, we should normalize Q(x,y). There are many different normalizations proposed in the literature. Here we describe three of them.

Zhengyou Zhang
Thu Feb 8 11:42:20 MET 1996