  Interest point detection is a common task in various computer vision
applications. Although a big variety of detector are developed so far
computational efficiency of interest point based image analysis remains to be
the problem. Current paper proposes a system-theoretic approach to interest
point detection. Starting from the analysis of interdependency between detector
and descriptor it is shown that given a descriptor it is possible to introduce
to notion of detector redundancy. Furthermore for each detector it is possible
to construct its irredundant and equivalent modification. Modified detector
possesses lower computational complexity and is preferable. It is also shown
that several known approaches to reduce computational complexity of image
registration can be generalized in terms of proposed theory.
