A fast directional filter set for pyramidal image-based robotic systems

In seeking to develop a real-time, pyramidal imaging system for tracking and robotic visual servoing applications, inadequacies in the standard, commonly available kernels for directional filtering have led to the implementation of an alternative set of simple filters that combine to act as oriented edge-contrast operators fulfilling the familiar requirements for both speed and a highly localized response pattern. Although numerous edge operators, kernels and directional filters have been proposed, and low-level filtering is a well-established and mature area of computer vision, within the application described here, this operator set is proving superior to more established methods in efficiently preserving the response localization requirement while propagating the oriented gradient energies through multichannel resolution pyramids for further recursive processing. This paper provides a detailed discussion of the technique, the context of its development, and supporting empirical tests and statistical results. The evidence presented shows that the scheme provides a unified response to both step and line edge types, with acceptable performance in the presence of anticipated noise levels. The approach is pragmatic, of low complexity, and of general utility.