Triplet geometric representation: a novel scale, translation and rotation invariant feature representation based on geometric constraints for recognition of 2D object features

摘要

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 construct signature histograms of local shape. We describe the practical implementation of this new technique together with its properties, and present a statistical quantification of performance in the presence of: fragmentation, additive noise and clutter. The scale-invariant properties are assessed, the results of which imply a fundamental limit on scale-invariant recognition from a single model.