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Conference papers

Morphological Hierarchical Image Decomposition Based on Laplacian 0-Crossings

Abstract : A method of text detection in natural images, to be turned into an effective embedded software on a mobile device, shall be both efficient and lightweight. We observed that a simple method based on the morphological Laplace operator can do the trick: we can construct in quasi-linear time a hierarchical image decomposition / simplification based on its 0-crossings, and search for some text in the resulting tree. Yet, for this decomposition to be sound, we need " 0-crossings " to be Jordan curves, and to that aim, we rely on some discrete topology tools. Eventually, the hierarchical representation is the morphological tree of shapes of the Laplacian sign (ToSL). Moreover, we provide an algorithm with linear time complexity to compute this representation. We expect that the proposed hierarchical representation can be useful in some applications other than text detection.
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Submitted on : Friday, February 24, 2017 - 4:58:05 PM
Last modification on : Wednesday, June 9, 2021 - 5:28:03 PM
Long-term archiving on: : Thursday, May 25, 2017 - 1:51:54 PM


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  • HAL Id : hal-01476302, version 1



Lê Duy Huỳn, Yongchao Xu, Thierry Géraud. Morphological Hierarchical Image Decomposition Based on Laplacian 0-Crossings. 13th International Symposium on Mathematical Morphology (ISMM), May 2017, Fontainebleau, France. ⟨hal-01476302⟩



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