Gradient-based edge detection on a hexagonal structure

Authors

Xiangjian He, University of Technology, Sydney, Australia
Qiang Wu, University of Technology, Sydney, Australia
Tom Hintz, University of Technology, Sydney, Australia
Wenjing Jia, University of Technology, Sydney, Australia

Abstract

Gradient-based edge detection is a straightforward method to identify the edge points in the original grey-level image. It is intuitive that in the human vision system the edge points always appear where the grey-level 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 review the gradient-based edge detection algorithms on Spiral Architecture. An edge point is defined as a hexagonal pixel at which the magnitude of the gradient of brightness function assumes a local maximum.

Keywords

Spiral architecture, Edge detection, Triple-diagonal-gradient, Bilateral filter, Prewitt masks, Sobel operators, Hexagonal image structure

DOI

https://doi.org/10.54784/1990-6587.1137

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

He, X., Wu, Q., Hintz, T., & Jia, W. (2008). Gradient-based edge detection on a hexagonal structure. Business Review, 3(1), 133-144. Retrieved from https://doi.org/10.54784/1990-6587.1137