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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >SKELETON LOCATION AND EVALUATION BASED ON LOCAL DIGITAL WIDTH IN RIBBON-LIKE IMAGES
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SKELETON LOCATION AND EVALUATION BASED ON LOCAL DIGITAL WIDTH IN RIBBON-LIKE IMAGES

机译:基于带状图像的局部数字宽度的骨架定位与评估

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摘要

In this paper, we present a model for characterising the skeleton of line images. For comparative purposes, we base our theoretical model formulation on the ideal ribbon-like non-branching image. The model developed is first contrasted with Blum's model and the wave propagation model. The aim of the proposed model is to avoid spurious branches of the skeleton and to refine the definition of centrality at sharp angles of the input image. The underlying concept of this model is based on a new definition for local width, derived from the idea of minimum base segment. This is first introduced in the real space, and then discretised for characterising a discrete skeleton. A graph theoretic approach, which is model-independent, is introduced for locating skeletons of non-branching images. By applying the graph-theoretic algorithm, performance evaluation of the proposed model is contrasted with Blum's original model by investigating reconstruction performance of the output skeletons. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd. [References: 28]
机译:在本文中,我们提出了用于表征线图像骨架的模型。为了进行比较,我们将理论模型公式化为理想的带状非分支图像。首先将开发的模型与Blum模型和波传播模型进行对比。提出的模型的目的是避免骨骼的虚假分支,并改善输入图像锐角处的中心性定义。该模型的基本概念基于局部宽度的新定义,该定义是从最小基本段的思想中得出的。首先将其引入真实空间,然后离散化以表征离散骨骼。引入了一种与模型无关的图论方法来定位非分支图像的骨架。通过应用图论算法,通过研究输出骨架的重建性能,将提出的模型的性能评估与Blum的原始模型进行对比。 (C)1997模式识别学会。由Elsevier Science Ltd.发布[参考:28]

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