A correspondence-based neural mechanism for position invariant feature processing

Abstract

We here focus on constructing a hierarchical neural sys-tem for position-invariant recognition, which is one of themost fundamental invariant recognition achieved in vis-ual processing [1,2]. The invariant recognition have beenhypothesized to be done by matching a sensory image ofa particular object stimulated on the retina to the mostsuitable representation stored in memory of the highervisual cortical area. Here arises a general problem: In sucha visual processing, the position of the object image onthe retina must be initially uncertain. Furthermore, theretinal activities possessing sensory information are beingfar from the ones in the higher area with a loss of the sen-sory object information. Nevertheless, with such recogni-tion ambiguity, the particular object can effortlessly andeasily be recognized. Our aim in this work is an attempt toresolve such a general recognition problem.