Fuzzy invariant indexing: a general indexing scheme for occluded object recognition

In this paper we present a general indexing scheme for model-based occluded object recognition. This new technique is called fuzzy invariant indexing (FII). It is based on fuzzy if-then-classification rules and fuzzified invariant object description, which can be either invariant values or invariant signatures. We describe the framework of the method and its general applicability: if invariant object descriptions can be constructed, the fuzzy invariant indexing technique can be utilized for recognizing the objects. The recognition performance of the FII-technique is demonstrated for partially occluded (quasi-) planar objects as well as for rotationally symmetric objects in real scenes.