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Single-scan skeletonization driven by a neighborhood-sequence distance

Abstract

International audienceShape description is an important step in image analysis. Skeletonization methods are widely used in image analysis as they are a powerful tool to describe a shape. Indeed, a skeleton is a one point wide line centered in the shape which keeps the shape's topology. Commonly, at least two scans of the image are needed for the skeleton computation in the state of art methods of skeletonization. In this work, a single scan is used considering information propagation in order to compute the skeleton. This paper presents also a new single-scan skeletonization using different distances likes d4, d8 and dns

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