Abstract
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.
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