Three-dimensional invariants and classification of Ladar signatures

In this paper we report new results in an ongoing study to address the problem of classification of Laser radar targets. We first discuss the issue of representation of 3D object such that they remain unchanged under affine transformation. A set of Ladar signatures of tactical military targets are then represented in the invariant feature spaces and their inter-class separability is studied by adding random noise of varying characteristics to the Ladar signatures. A number of performance metrics such as interclass distances and ROC curves are used to demonstrate the classification behaviors of 35 different target signatures.