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.
Spiral architecture, Edge detection, Triple-diagonal-gradient, Bilateral filter, Prewitt masks, Sobel operators, Hexagonal image structure
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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
February 23, 2021