A streaming FPGA implementation of a steerable filter for real-time applications (abstract only)

Abstract

Oriented filters are used in many early vision and image processing tasks for feature extraction at arbitrary orientations. Steerable filters are a class of filters in which a filter of arbitrary orientation is synthesized as a linear combination of a set of basis filters. In this work, we describe a streaming implementation of a steerable filter on FPGAs, which includes a two-dimensional convolution filter and a modulator for modulation by a set of oriented sine waves. We present a highly configurable streaming 2D convolution implementation and a novel separable look-up-table based implementation of the modulation step. This steerable filter has been extended to multiple resolutions to realize a steerable pyramid filter. Experimental results on a Virtex6 FPGA show that the steerable pyramid filter provides up to 14X and 21X speedups over related FPGA and CPU implementations respectively. This work was supported in part by a grant from NSF 0916887 and DARPA Neovision2 programs.