GRoM — Generalized robust multichannel featur detector

A number of well-known computer vision algorithms for image feature detection use luminosity only or some specific color model. Although these methods are effective in many cases, it can be shown that these transformations of the full image information reduce detection performance due to method-induced restrictions. In this paper, we describe a formal approach to the construction of a multi-channel interest point detector for an arbitrary number of channels (regardless of data nature), which maximizes the benefits from the usage of information from these additional channels. We introduce the Generalized Robust Multi-channel (GRoM) feature detector prototype that is based upon the proposed approach, detail features of GRoM and include a set of illustrative examples to highlight its differentiation from existing methods.