Difference between revisions of "Publications/huynh.17.ismm"
From LRDE
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| authors = Lê Duy Huỳnh, Yongchao Xu, Thierry Géraud |
| authors = Lê Duy Huỳnh, Yongchao Xu, Thierry Géraud |
||
| title = Morphological Hierarchical Image Decomposition Based on Laplacian 0-Crossings |
| title = Morphological Hierarchical Image Decomposition Based on Laplacian 0-Crossings |
||
− | | booktitle = Mathematical Morphology and Its Application to Signal and Image Processing |
+ | | booktitle = Mathematical Morphology and Its Application to Signal and Image Processing – Proceedings of the 13th International Symposium on Mathematical Morphology (ISMM) |
| editors = J Angulo, S Velasco-Forero, F Meyer |
| editors = J Angulo, S Velasco-Forero, F Meyer |
||
| volume = 10225 |
| volume = 10225 |
||
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| address = Fontainebleau, France |
| address = Fontainebleau, France |
||
| publisher = Springer |
| publisher = Springer |
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− | | abstract = A method of text detection in natural images, to be turn into an effective embedded software on a mobile deviceshall 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 |
+ | | abstract = A method of text detection in natural images, to be turn into an effective embedded software on a mobile deviceshall 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. 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. |
| lrdepaper = http://www.lrde.epita.fr/dload/papers/huynh.17.ismm.pdf |
| lrdepaper = http://www.lrde.epita.fr/dload/papers/huynh.17.ismm.pdf |
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| lrdekeywords = Image |
| lrdekeywords = Image |
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| type = inproceedings |
| type = inproceedings |
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| id = huynh.17.ismm |
| id = huynh.17.ismm |
||
+ | | identifier = doi:10.1007/978-3-319-57240-6_13 |
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| bibtex = |
| bibtex = |
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@InProceedings<nowiki>{</nowiki> huynh.17.ismm, |
@InProceedings<nowiki>{</nowiki> huynh.17.ismm, |
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address = <nowiki>{</nowiki>Fontainebleau, France<nowiki>}</nowiki>, |
address = <nowiki>{</nowiki>Fontainebleau, France<nowiki>}</nowiki>, |
||
publisher = <nowiki>{</nowiki>Springer<nowiki>}</nowiki>, |
publisher = <nowiki>{</nowiki>Springer<nowiki>}</nowiki>, |
||
+ | doi = <nowiki>{</nowiki>10.1007/978-3-319-57240-6_13<nowiki>}</nowiki>, |
||
abstract = <nowiki>{</nowiki>A method of text detection in natural images, to be turn |
abstract = <nowiki>{</nowiki>A method of text detection in natural images, to be turn |
||
into an effective embedded software on a mobile device, |
into an effective embedded software on a mobile device, |
Latest revision as of 13:42, 24 November 2020
- Authors
- Lê Duy Huỳnh, Yongchao Xu, Thierry Géraud
- Where
- Mathematical Morphology and Its Application to Signal and Image Processing – Proceedings of the 13th International Symposium on Mathematical Morphology (ISMM)
- Place
- Fontainebleau, France
- Type
- inproceedings
- Publisher
- Springer
- Keywords
- Image
- Date
- 2017-02-23
Abstract
A method of text detection in natural images, to be turn into an effective embedded software on a mobile deviceshall 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. 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.
Documents
Bibtex (lrde.bib)
@InProceedings{ huynh.17.ismm, author = {L\^e Duy {Hu\`ynh} and Yongchao Xu and Thierry G\'eraud}, title = {Morphological Hierarchical Image Decomposition Based on {L}aplacian 0-Crossings}, booktitle = {Mathematical Morphology and Its Application to Signal and Image Processing -- Proceedings of the 13th International Symposium on Mathematical Morphology (ISMM)}, year = {2017}, editor = {J. Angulo and S. Velasco-Forero and F. Meyer}, volume = {10225}, series = {Lecture Notes in Computer Science}, month = may, pages = {159--171}, address = {Fontainebleau, France}, publisher = {Springer}, doi = {10.1007/978-3-319-57240-6_13}, abstract = {A method of text detection in natural images, to be turn 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. 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.} }