Recognition of shapes by statistical modeling of centroidal profile

The recognition of unknown shapes by using maximum-likelihood methods is considered. The contour of a shape is represented by its centroidal profile, and it is fitted by a circular autoregressive model. The authors develop a decision rule to test whether two unknown shapes are identical. Then they develop a decision rule to classify an unknown object as a known object. Maximum-likelihood decision rules for these cases are derived. The decision rules are invariant to translation, rotation, and size change after the normalization of estimates. The developed algorithms are used to classify different machine parts and aircraft shapes.<<ETX>>