TRIPLET GEOMETRIC REPRESENTATION - A NOVEL SCALE, TRANSLATION AND ROTATION-INVARIANT FEATURE REPRESENTATION BASED ON GEOMETRIC CONSTRAINTS FOR RECOGNITION OF 2D OBJECT FEATURES

We present a novel representation for scale, translation and rotation independent recognition of 2D object features based on the invariance properties of the included angles of a triangle which we exploit to co nstruct signature histograms of local shape. We describe the practical implementation of this new technique together with its properties, an d present a statistical quantification of performance in the presence of: fragmentation, additive noise and clutter. The scale-invariant pro perties are assessed, the results of which imply a fundamental limit o n scale-invariant recognition from a single model.