Difference between revisions of "Publications/geraud.14.icip"
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{{Publication |
{{Publication |
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− | | published = |
+ | | published = true |
− | | date = 2014- |
+ | | date = 2014-06-03 |
| authors = Thierry Géraud |
| authors = Thierry Géraud |
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| title = A Morphological Method for Music Score Staff Removal |
| title = A Morphological Method for Music Score Staff Removal |
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− | | booktitle = |
+ | | booktitle = Proceedings of the 21st International Conference on Image Processing (ICIP) |
| address = Paris, France |
| address = Paris, France |
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− | | pages = |
+ | | pages = 2599 to 2603 |
− | | |
+ | | lrdeprojects = Olena |
⚫ | | abstract = Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. In this paper we present the method that has won in 2013 the staff removal competitionorganized at the International Conference on Document Analysis and Recognition (ICDAR). The main characteristics of this method is that it essentially relies on mathematical morphology filtering. So it is simple, fastand its full source code is provided to favor reproducible research. |
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− | | urllrde = 201402-ICIPc |
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⚫ | | abstract = Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. |
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| lrdeinc = Publications/geraud.14.icip.inc |
| lrdeinc = Publications/geraud.14.icip.inc |
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+ | | lrdepaper = http://www.lrde.epita.fr/dload/papers/geraud.14.icip.pdf |
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+ | | lrdeposter = http://www.lrde.epita.fr/dload/papers/geraud.14.icip.poster.pdf |
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| lrdekeywords = Image |
| lrdekeywords = Image |
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− | | lrdenewsdate = |
+ | | lrdenewsdate = 2014-06-03 |
− | | note = Submitted |
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| type = inproceedings |
| type = inproceedings |
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| id = geraud.14.icip |
| id = geraud.14.icip |
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+ | | identifier = doi:10.1109/ICIP.2014.7025526 |
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| bibtex = |
| bibtex = |
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@InProceedings<nowiki>{</nowiki> geraud.14.icip, |
@InProceedings<nowiki>{</nowiki> geraud.14.icip, |
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author = <nowiki>{</nowiki>Thierry G\'eraud<nowiki>}</nowiki>, |
author = <nowiki>{</nowiki>Thierry G\'eraud<nowiki>}</nowiki>, |
||
title = <nowiki>{</nowiki>A Morphological Method for Music Score Staff Removal<nowiki>}</nowiki>, |
title = <nowiki>{</nowiki>A Morphological Method for Music Score Staff Removal<nowiki>}</nowiki>, |
||
− | booktitle = <nowiki>{</nowiki> |
+ | booktitle = <nowiki>{</nowiki>Proceedings of the 21st International Conference on Image |
Processing (ICIP)<nowiki>}</nowiki>, |
Processing (ICIP)<nowiki>}</nowiki>, |
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year = 2014, |
year = 2014, |
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address = <nowiki>{</nowiki>Paris, France<nowiki>}</nowiki>, |
address = <nowiki>{</nowiki>Paris, France<nowiki>}</nowiki>, |
||
− | pages = <nowiki>{</nowiki> |
+ | pages = <nowiki>{</nowiki>2599--2603<nowiki>}</nowiki>, |
− | project = <nowiki>{</nowiki>Image<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>Removing the staff in music score images is a key to |
abstract = <nowiki>{</nowiki>Removing the staff in music score images is a key to |
||
improve the recognition of music symbols and, with ancient |
improve the recognition of music symbols and, with ancient |
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and its full source code is provided to favor reproducible |
and its full source code is provided to favor reproducible |
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research.<nowiki>}</nowiki>, |
research.<nowiki>}</nowiki>, |
||
− | + | doi = <nowiki>{</nowiki>10.1109/ICIP.2014.7025526<nowiki>}</nowiki> |
|
<nowiki>}</nowiki> |
<nowiki>}</nowiki> |
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Latest revision as of 17:00, 27 May 2021
- Authors
- Thierry Géraud
- Where
- Proceedings of the 21st International Conference on Image Processing (ICIP)
- Place
- Paris, France
- Type
- inproceedings
- Projects
- Olena
- Keywords
- Image
- Date
- 2014-06-03
Abstract
Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. In this paper we present the method that has won in 2013 the staff removal competitionorganized at the International Conference on Document Analysis and Recognition (ICDAR). The main characteristics of this method is that it essentially relies on mathematical morphology filtering. So it is simple, fastand its full source code is provided to favor reproducible research.
Documents
Figure
.
Step-by-step staff removal: the same image excerpt is depicted: click on the images to enlarge.
.
![]() |
(a) Input image. |
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![]() |
(b) Step 1: permissive hit-or-miss. |
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![]() |
(c) Step 2: horizontal median filter. |
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![]() |
(d) Step 3: horizontal reconstruction. |
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![]() |
(e) Step 4: cleaning. |
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![]() |
(f) Step 5: after line selection (contour superimposed). |
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![]() |
(g) Step 6: output, after a local vertical median filter. |
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![]() |
(h) Ground truth. |
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Source Code
Code of the method described in the paper: [1]
Useful Links
- The staff removal competition organized at the International Conference on Document Analysis and Recognition (ICDAR) 2013:
http://www.icdar2013.org/program/competitions
- The CVC-MUSCIMA database of handwritten music score images:
http://www.cvc.uab.es/cvcmuscima
- The Olena Image Processing Platform (containing the Milena C++ image processing library):
- An online demo of staff removal:
http://olena.lrde.epita.fr/demos/staff_removal.php
- Reproducible research:
Contact
- Homepage: http://www.lrde.epita.fr/wiki/User:Theo
- Email: thierry.geraud@lrde.epita.fr
Bibtex (lrde.bib)
@InProceedings{ geraud.14.icip, author = {Thierry G\'eraud}, title = {A Morphological Method for Music Score Staff Removal}, booktitle = {Proceedings of the 21st International Conference on Image Processing (ICIP)}, year = 2014, address = {Paris, France}, pages = {2599--2603}, abstract = {Removing the staff in music score images is a key to improve the recognition of music symbols and, with ancient and degraded handwritten music scores, it is not a straightforward task. In this paper we present the method that has won in 2013 the staff removal competition, organized at the International Conference on Document Analysis and Recognition (ICDAR). The main characteristics of this method is that it essentially relies on mathematical morphology filtering. So it is simple, fast, and its full source code is provided to favor reproducible research.}, doi = {10.1109/ICIP.2014.7025526} }