Edge Detection on Spiral Architecture: An Overview

Gradient-based edge detection is a straightforward method to identify the edge points in the original greylevel image. It is intuitive that in the human vision system the edge points always appear where the greylevel value is greatly changed Spiral Architecture is a relatively new image data structure that is inspired from anatomical considerations of the primate's vision. In Spiral Architecture, each image is represented as a collection of hexagonal pixels. Edge detection on Spiral Architecture has features of fast computation and accurate localization. In this paper, we briefly review the edge detection methods on Spiral Architecture including the edge focusing technique, bilateral filter, and triple-diagonal gradient. Parallel algorithms for edge detection will be discussed. We will also list problems for future work.