A Pyramid Algorithm for Fast Curve Extraction

Abstract The human visual system has the impressive ability to quickly extract simple, global, curvilinear structure from input that may locally not even contain small fragments of this structure. Curves are easy to see globally even when they are locally broken, blurred, or jagged. Because the character of curve input can change with the scale at which it is considered, a hierarchical “pyramid” data structure is suggested. This paper describes a simple curve extraction process involving only local isotropic parallel operations. The noise-cleaned input image is smoothed and subsampled into a pyramid of lower-resolution versions by recursive computation of Gaussian-weighted sums. Curves are localized to thin strings of ridges and peaks at each scale. The method is compared with more abstract, essentially one-dimensional contour summarization processes.

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