Difference between revisions of "Publications/puybareau.18.icip"
From LRDE
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| title = Real-Time Document Detection in Smartphone Videos |
| title = Real-Time Document Detection in Smartphone Videos |
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| booktitle = Proceedings of the 24th IEEE International Conference on Image Processing (ICIP) |
| booktitle = Proceedings of the 24th IEEE International Conference on Image Processing (ICIP) |
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+ | | pages = 1498 to 1502 |
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| address = Athens, Greece |
| address = Athens, Greece |
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| abstract = Smartphones are more and more used to capture photos of any kind of important documents in many different situations, yielding to new image processing needs. One of these is the ability of detecting documents in real time on smartphones' video stream while being robust to classical defects such as low contrast, fuzzy images, flaresshadows, etc. This feature is interesting to help the user to capture his document in the best conditions and to guide this capture (evaluating appropriate distance, centering and tilt). In this paper we propose a solution to detect in real time documents taking very few assumptions concerning their contents and background. This method is based on morphological operators which contrasts with classical line detectors or gradient based thresholds. The use of such invariant operators makes our method robust to the defects encountered in video stream and suitable for real time document detection on smartphones. |
| abstract = Smartphones are more and more used to capture photos of any kind of important documents in many different situations, yielding to new image processing needs. One of these is the ability of detecting documents in real time on smartphones' video stream while being robust to classical defects such as low contrast, fuzzy images, flaresshadows, etc. This feature is interesting to help the user to capture his document in the best conditions and to guide this capture (evaluating appropriate distance, centering and tilt). In this paper we propose a solution to detect in real time documents taking very few assumptions concerning their contents and background. This method is based on morphological operators which contrasts with classical line detectors or gradient based thresholds. The use of such invariant operators makes our method robust to the defects encountered in video stream and suitable for real time document detection on smartphones. |
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| type = inproceedings |
| type = inproceedings |
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| id = puybareau.18.icip |
| id = puybareau.18.icip |
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+ | | identifier = doi:10.1109/ICIP.2018.8451533 |
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| bibtex = |
| bibtex = |
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@InProceedings<nowiki>{</nowiki> puybareau.18.icip, |
@InProceedings<nowiki>{</nowiki> puybareau.18.icip, |
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Image Processing (ICIP)<nowiki>}</nowiki>, |
Image Processing (ICIP)<nowiki>}</nowiki>, |
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year = <nowiki>{</nowiki>2018<nowiki>}</nowiki>, |
year = <nowiki>{</nowiki>2018<nowiki>}</nowiki>, |
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+ | pages = <nowiki>{</nowiki>1498--1502<nowiki>}</nowiki>, |
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month = oct, |
month = oct, |
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address = <nowiki>{</nowiki>Athens, Greece<nowiki>}</nowiki>, |
address = <nowiki>{</nowiki>Athens, Greece<nowiki>}</nowiki>, |
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+ | doi = <nowiki>{</nowiki>10.1109/ICIP.2018.8451533<nowiki>}</nowiki>, |
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abstract = <nowiki>{</nowiki>Smartphones are more and more used to capture photos of |
abstract = <nowiki>{</nowiki>Smartphones are more and more used to capture photos of |
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any kind of important documents in many different |
any kind of important documents in many different |
Latest revision as of 13:42, 24 November 2020
- Authors
- Élodie Puybareau, Thierry Géraud
- Where
- Proceedings of the 24th IEEE International Conference on Image Processing (ICIP)
- Place
- Athens, Greece
- Type
- inproceedings
- Projects
- Olena
- Keywords
- Image
- Date
- 2018-05-10
Abstract
Smartphones are more and more used to capture photos of any kind of important documents in many different situations, yielding to new image processing needs. One of these is the ability of detecting documents in real time on smartphones' video stream while being robust to classical defects such as low contrast, fuzzy images, flaresshadows, etc. This feature is interesting to help the user to capture his document in the best conditions and to guide this capture (evaluating appropriate distance, centering and tilt). In this paper we propose a solution to detect in real time documents taking very few assumptions concerning their contents and background. This method is based on morphological operators which contrasts with classical line detectors or gradient based thresholds. The use of such invariant operators makes our method robust to the defects encountered in video stream and suitable for real time document detection on smartphones.
Documents
Bibtex (lrde.bib)
@InProceedings{ puybareau.18.icip, author = {\'Elodie Puybareau and Thierry G\'eraud}, title = {Real-Time Document Detection in Smartphone Videos}, booktitle = {Proceedings of the 24th IEEE International Conference on Image Processing (ICIP)}, year = {2018}, pages = {1498--1502}, month = oct, address = {Athens, Greece}, doi = {10.1109/ICIP.2018.8451533}, abstract = {Smartphones are more and more used to capture photos of any kind of important documents in many different situations, yielding to new image processing needs. One of these is the ability of detecting documents in real time on smartphones' video stream while being robust to classical defects such as low contrast, fuzzy images, flares, shadows, etc. This feature is interesting to help the user to capture his document in the best conditions and to guide this capture (evaluating appropriate distance, centering and tilt). In this paper we propose a solution to detect in real time documents taking very few assumptions concerning their contents and background. This method is based on morphological operators which contrasts with classical line detectors or gradient based thresholds. The use of such invariant operators makes our method robust to the defects encountered in video stream and suitable for real time document detection on smartphones.} }