Saliency-Based Detection of Identy Documents Captured by Smartphones

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 our resulting saliency maps 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 perform in real-time on smartphones.