Skyline-based Approach for Natural Scene Identification

Ameni Sassi (1, 2) , Chokri Ben-Amar (1) , Serge Miguet (3)

1 REGIM-Lab - REsearch Group in Intelligent Machines [Sfax]
2 M2DisCo - Geometry Processing and Constrained Optimization
3 imagine - Extraction de Caractéristiques et Identification

The skyline, defined as the line separating the sky from other objects on the ground, could provide unique and useful information for a variety of applications. This line was used as a key data, especially, for geo-localization and aerial robotic applications. The particular shape and the geometric features of a skyline may be the identity of the landscape itself. The skyline, once well extracted, could show the silhouette of a famous tower, the mountain peaks, or the landscape topography. In this paper, we proposed a geometric description of the extracted skyline from landscapes. Based on some geometric descriptors, we tried to pick up practical measurements for each skyline. The first proposed approach was the straight lines' classification to differentiate between urban and natural landscapes from their horizon line. The second one is the curvature analysis using a Curvature Scale Space descriptor. This descriptor was used to enhance the first one and to distinguish between natural part and buildings in the same skyline. The results obtained from these geometric description tools were very competitive and they will be the inputs for a classification process.

Mots clés: skyline; geometric descriptor; landscape; curvature

Domaines: Traitement des images [eess.IV]

Ameni Sassi, Chokri Ben-Amar, Serge Miguet. Skyline-based Approach for Natural Scene Identification. 13th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2016), Nov 2016, Agadir, Morocco. ⟨hal-01385537⟩