Distribution-aware FAST feature point extraction and matching based on FPGA

Image feature extraction and matching are fundamental but computation intensive tasks in machine vision. This paper proposes a novel FPGA-based embedded system to accelerate feature extraction and matching. It implements SURF feature point detection and BRIEF feature descriptor construction and matching. For binocular stereo vision, feature matching includes both tracking matching and stereo matching, which simultaneously provide feature point correspondences and parallax information. The proposed design can process binocular video at high frame rate (640 x 480 @ 162fps). Different from similar works, the proposed approach considers feature point distribution in hardware design, and can homogenlize feature points over the image on the fly, and impacts on following feature point matching as well as homography transform matrix calculation are also evaluated. Experiment results demonstrate that our approach can reduce feature point matching overhead, and has no much adverse effect on holography projection.