Saliency-Based Detection of Identy Documents Captured by Smartphones
From LRDE
- Authors
- Minh Ôn Vũ Ngoc, Jonathan Fabrizio, Thierry Géraud
- Where
- Proceedings of the IAPR International Workshop on Document Analysis Systems (DAS)
- Place
- Vienna, Austria
- Type
- inproceedings
- Projects
- Olena
- Keywords
- Image
- Date
- 2018-01-24
Abstract
Smartphones have became an easy and convenient mean to acquire documents. In this paper, we focus on the automatic segmentation of identity documents in smartphone photos or videos using visual saliency (VS). VS-based approaches, which pertain to computer vision, have not be considered yet for this particular task. Here we compare different VS methods, and we propose a new VS schemebased on a recent distance belonging to the scope of mathematical morphology. We show that the saliency maps we obtain are competitive with state-of-the-art visual saliency methods and, that such approaches are very promising for use in identity document detection and segmentation, even without taking into account any prior knowledge about document contents. In particular they can work in real-time on smartphones.
Documents
Bibtex (lrde.bib)
@InProceedings{ movn.18.das, author = {Minh {\^On V\~{u} Ng\d{o}c} and Jonathan Fabrizio and Thierry G\'eraud}, title = {Saliency-Based Detection of Identy Documents Captured by Smartphones}, booktitle = {Proceedings of the IAPR International Workshop on Document Analysis Systems (DAS)}, year = {2018}, opteditor = {}, optvolume = {}, optnumber = {}, optseries = {}, optpages = {}, month = {April}, address = {Vienna, Austria}, abstract = {Smartphones have became an easy and convenient mean to acquire documents. In this paper, we focus on the automatic segmentation of identity documents in smartphone photos or videos using visual saliency (VS). VS-based approaches, which pertain to computer vision, have not be considered yet for this particular task. Here we compare different VS methods, and we propose a new VS scheme, based on a recent distance belonging to the scope of mathematical morphology. We show that the saliency maps we obtain are competitive with state-of-the-art visual saliency methods and, that such approaches are very promising for use in identity document detection and segmentation, even without taking into account any prior knowledge about document contents. In particular they can work in real-time on smartphones.}, note = {To appear} }