classification of shape data using logistic regression

In this paper, a linear model using the principal component scores in shapedata that is fitted in the tangent space of shapes with the nominal responses is proposed.in that respect, the multinomial logistic regression for multivariate and logisticregression for binary responses is considered. in doing so, principal components in thetangent space are used to improve the estimation of logistic model parameters undermulti-collinearity and reduce the input data dimension. the result of this study issignificant and point to improving the classification shape data according to their differentnominal groups. we study the performance of the proposed technique on threereal-world data sets.