Morphology-Based Hierarchical Representation with Application to Text Segmentation in Natural Images

Authors

Lê Duy Hu`ynh, Yongchao Xu, Thierry Géraud

Where

Proceedings of the 23st International Conference on Pattern Recognition (ICPR)

Place

Cancún, México

Type

inproceedings

Publisher

IEEE Computer Society

Projects

Olena

Keywords

Image

Date

2016-07-13

Abstract

Many text segmentation methods are elaborate and thus are not suitable to real-time implementation on mobile devices. Having an efficient and effective method, robust to noiseblur, or uneven illumination, is interesting due to the increasing number of mobile applications needing text extraction. We propose a hierarchical image representationbased on the morphological Laplace operator, which is used to give a robust text segmentation. This representation relies on several very sound theoretical tools; its computation eventually translates to a simple labeling algorithm, and for text segmentation and grouping, to an easy tree-based processing. We also show that this method can also be applied to document binarization, with the interesting feature of getting also reverse-video text.

Documents

• Paper

Bibtex (lrde.bib)

@InProceedings{	  huynh.16.icpr,
  author	= {L\^e Duy {Hu\`ynh} and Yongchao Xu and Thierry G\'eraud},
  title		= {Morphology-Based Hierarchical Representation with
		  Application to Text Segmentation in Natural Images},
  booktitle	= {Proceedings of the 23st International Conference on
		  Pattern Recognition (ICPR)},
  year		= 2016,
  address	= {Canc\'un, M\'exico},
  month		= dec,
  optpages	= {485--488},
  publisher	= {IEEE Computer Society},
  abstract	= { Many text segmentation methods are elaborate and thus are
		  not suitable to real-time implementation on mobile devices.
		  Having an efficient and effective method, robust to noise,
		  blur, or uneven illumination, is interesting due to the
		  increasing number of mobile applications needing text
		  extraction. We propose a hierarchical image representation,
		  based on the morphological Laplace operator, which is used
		  to give a robust text segmentation. This representation
		  relies on several very sound theoretical tools; its
		  computation eventually translates to a simple labeling
		  algorithm, and for text segmentation and grouping, to an
		  easy tree-based processing. We also show that this method
		  can also be applied to document binarization, with the
		  interesting feature of getting also reverse-video text.},
  note		= {To appear}
}