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Communication Dans Un Congrès Année : 2012

Accurate Junction Detection and Reconstruction in Line-Drawing Images

Résumé

In this paper, we present an approach for junction detection and reconstruction in line-drawing images. Our approach is shifted to a problem of high curvature point detection from the skeleton of image. Like this, it is independent of any vectorization process and parameter free. The junction reconstruction stage takes benefit of the reliable skeleton segments and their topological relations to reconstruct junctions and make their positions accurate. The experimental results show that the proposed method is competitive with other baseline methods and can achieve accurate junction detection with some pixel errors.
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Dates et versions

hal-01027447 , version 1 (22-07-2014)

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  • HAL Id : hal-01027447 , version 1

Citer

The Ahn Pham, Mathieu Delalandre, Sabine Barrat, Jean-Yves Ramel. Accurate Junction Detection and Reconstruction in Line-Drawing Images. 21st International Conference on Pattern Recognition, Nov 2012, Tsukuba Science City, Japan. pp.693-696. ⟨hal-01027447⟩
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