Real-Time Document Detection in Smartphone Videos

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

• Paper

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.}
}