Modélisation 3D des façades de bâtiments des anciennes Médina

Le LIDAR (Light Detecting and Ranging) terrestre statique est un outil de levé présentant actuellement une source de données 3D indispensable dans l’évaluation et la surveillance des bâtiments patrimoniaux. A travers des processus automatiques de modélisation 3D, la manipulation de cette source de données dans des outils de communication devient plus souple. Le processus de modélisation 3D impose des sous missions indispensables dont la segmentation. Une grande partie des approches de segmentation se focalisent sur l’emploi des composantes géométriques en exploitant la représentation mathématique d’une surface plane ou courbée. En raison de la complexité de l’architecture des façades, une segmentation utilisant uniquement l’aspect géométrique reste insuffisante. Ainsi, une nouvelle approche de segmentation est développée équilibrant les résultats de l’extraction des surfaces homogènes. Ceci, en se basant sur l’ensemble des composantes d’un nuage de points coloriés à savoir les composantes géométriques, les valeurs RGB et les intensités laser des détails constituant les façades des bâtiments des anciennes Médina. Le processus s’initialise par l’extraction des segments plans à l’aide de l’algorithme RANSAC. Le résultat fera l’objet d’une deuxième segmentation radiométrique basée sur l’introduction du critère de similarité couleur dans l’algorithme de croissance de région. Enfin une fusion de classes sera effectuée en fonction de la similarité de l’intensité laser.    The static terrestrial LIDAR is a tool of surveying which present a vital source of 3D data in the heritage buildings evaluation and monitoring. Through automated  3D modeling process, manipulating this data source in communication tools becomes more flexible. The 3D modeling process imposes on essential tasks including segmentation. Much of segmentation approaches focus on the use of geometric components by exploiting the mathematical representation of a plane or curved area. Due to the complexity of the facades architecture, segmentation using only the geometrical aspect is insufficient. Thus, a new segmentation approach is developed balancing the results of extracting homogeneous areas based on all colored point cloud components namely geometric data, the RGB values and intensities of facades details especially in old Medina building. The process consists of the planar segments extracting using the RANSAC algorithm. The result will be subject to radiometric segmentation through the introduction of color similarity criterion in the region growing algorithm and finally a fusion of classes based on the intensity’s similarity

SEGMENTATION OF HERITAGE BUILDING BY MEANS OF GEOMETRIC AND RADIOMETRIC COMPONENTS FROM TERRESTRIAL LASER SCANNING

Nowadays, the terrestrial laser scanning represents an integral source of data for cultural heritage 3D storage and access through digital communication tools. The achievement of 3D models requires the implementation of several tasks such as segmentation. Segmentation is the key step during the point cloud processing where all homogeneous areas are identified, which describe a building facade. Usually, a large part of the segmentation approach focuses on the geometric information contained in the point cloud data by exploiting mathematical representation of a parametric surface. However, due to the complexity of the architecture, such segmentation does not suffice. Henceforth, other approaches turn to the use of color and laser intensity components. Although a variety of algorithms have been developed in this sense, problems of over-segmentation or under-segmentation are observed. In this context, we propose a new approach for point cloud segmentation aiming at a more accurate result. This approach relies on all the components of a colored point – both geometric and radiometric – combining the RGB values, laser intensity and geometric data. Our process begins with the extraction of homogeneous planar segments using the RANSAC algorithm. Next, the result is subjected to a radiometric-based segmentation, first through color similarity as one of the homogeneity criteria of a region growing algorithm, then through the use of intensity similarity for segment fusion. Experiments are performed on a facade presenting an example of Moroccan classical architecture located in Casablanca's Medina. Results show the importance of integrating all point cloud components, both geometric and radiometric