Quality analysis of the sphere parameters determination in terrestrial laser scanning

A point cloud is the result of laser scanning; in the case of\ud terrestrial laser scanning, the point cloud is composed of points\ud scanned from one or more positions. To register these points\ud into one point cloud, so-called tie points are needed; these\ud may be object points (natural targets) or selected stabilized\ud targets (artificial targets). Spherical targets are often used as\ud artificial targets; these must have their centre coordinates and\ud radius determined. The centre coordinates of a sphere are\ud calculated on the basis of scanned points on the spheres’ surface.\ud This paper presents two procedures for determining the best\ud reflection region on the sphere to determine its parameters, and\ud the procedure for determining the optimal distance between\ud the scanner and sphere.The best reflection area on the sphere\ud is determined in two ways. The first is based on minimizing\ud the difference between sphere radii when, in the adjustment\ud process, the radius of the sphere is treated as a known and\ud unknown quantity. The second is based on the standard\ud deviation of the sphere’s centre coordinates at the independent\ud determinations of sphere parameters from randomly chosen\ud scanned points on the sphere surface. For each of the spheres,\ud the best ratio between the laser beam footprint area and the\ud target surface area is calculated for the optimal combination\ud of scanning distance and region. For the best combination\ud of scanning distance and region, we chose the one with the\ud smallest standard deviation of the sphere centre coordinates

Extraction robuste de primitives géométriques 3D dans un nuage de points et alignement basé sur les primitives

Dans ce projet, nous étudions les problèmes de rétro-ingénierie et de contrôle de la qualité qui jouent un rôle important dans la fabrication industrielle. La rétro-ingénierie tente de reconstruire un modèle 3D à partir de nuages de points, qui s’apparente au problème de la reconstruction de la surface 3D. Le contrôle de la qualité est un processus dans lequel la qualité de tous les facteurs impliqués dans la production est abordée. En fait, les systèmes ci-dessus nécessitent beaucoup d’intervention de la part d’un utilisateur expérimenté, résultat souhaité est encore loin soit une automatisation complète du processus. Par conséquent, de nombreux défis doivent encore être abordés pour atteindre ce résultat hautement souhaitable en production automatisée. La première question abordée dans la thèse consiste à extraire les primitives géométriques 3D à partir de nuages de points. Un cadre complet pour extraire plusieurs types de primitives à partir de données 3D est proposé. En particulier, une nouvelle méthode de validation est proposée pour évaluer la qualité des primitives extraites. À la fin, toutes les primitives présentes dans le nuage de points sont extraites avec les points de données associés et leurs paramètres descriptifs. Ces résultats pourraient être utilisés dans diverses applications telles que la reconstruction de scènes on d’édifices, la géométrie constructive et etc. La seconde question traiée dans ce travail porte sur l’alignement de deux ensembles de données 3D à l’aide de primitives géométriques, qui sont considérées comme un nouveau descripteur robuste. L’idée d’utiliser les primitives pour l’alignement arrive à surmonter plusieurs défis rencontrés par les méthodes d’alignement existantes. Ce problème d’alignement est une étape essentielle dans la modélisation 3D, la mise en registre, la récupération de modèles. Enfin, nous proposons également une méthode automatique pour extraire les discontinutés à partir de données 3D d’objets manufacturés. En intégrant ces discontinutés au problème d’alignement, il est possible d’établir automatiquement les correspondances entre primitives en utilisant l’appariement de graphes relationnels avec attributs. Nous avons expérimenté tous les algorithmes proposés sur différents jeux de données synthétiques et réelles. Ces algorithmes ont non seulement réussi à accomplir leur tâches avec succès mais se sont aussi avérés supérieus aux méthodes proposées dans la literature. Les résultats présentés dans le thèse pourraient s’avérér utilises à plusieurs applications.In this research project, we address reverse engineering and quality control problems that play significant roles in industrial manufacturing. Reverse engineering attempts to rebuild a 3D model from the scanned data captured from a object, which is the problem similar to 3D surface reconstruction. Quality control is a process in which the quality of all factors involved in production is monitored and revised. In fact, the above systems currently require significant intervention from experienced users, and are thus still far from being fully automated. Therefore, many challenges still need to be addressed to achieve the desired performance for automated production. The first proposition of this thesis is to extract 3D geometric primitives from point clouds for reverse engineering and surface reconstruction. A complete framework to extract multiple types of primitives from 3D data is proposed. In particular, a novel validation method is also proposed to assess the quality of the extracted primitives. At the end, all primitives present in the point cloud are extracted with their associated data points and descriptive parameters. These results could be used in various applications such as scene and building reconstruction, constructive solid geometry, etc. The second proposition of the thesis is to align two 3D datasets using the extracted geometric primitives, which is introduced as a novel and robust descriptor. The idea of using primitives for alignment is addressed several challenges faced by existing registration methods. This alignment problem is an essential step in 3D modeling, registration and model retrieval. Finally, an automatic method to extract sharp features from 3D data of man-made objects is also proposed. By integrating the extracted sharp features into the alignment framework, it is possible implement automatic assignment of primitive correspondences using attribute relational graph matching. Each primitive is considered as a node of the graph and an attribute relational graph is created to provide a structural and relational description between primitives. We have experimented all the proposed algorithms on different synthetic and real scanned datasets. Our algorithms not only are successful in completing their tasks with good results but also outperform other methods. We believe that the contribution of them could be useful in many applications

Optimization of terrestrial laser scanning for high precision measurements

V disertaciji se ukvarjamo z optimizacijo postopkov terestričnega laserskega skeniranja, ker želimo povečati natančnost in zanesljivost rezultatov ter zmanjšati čas in stroške za izvedbo postopka. Glavni namen je kalibracija laserskega skenerja, ki jo želimo nadgraditi s postopki strojnega učenja. Za izvedbo kalibracije vzpostavimo postopek preciznega določanja centrov tarč iz skenogramov. Predlagamo robusten postopek visoke natančnosti, s katerim ovrednotimo tudi natančnost meritev s skenerjem. Vzpostavili smo dve kalibracijski bazi, v katerih smo položaje točk določili s klasično geodetsko metodologijo z najvišjo dosegljivo natančnostjo. Izdelali smo lasten program za izravnavo samokalibracije z izvirnim načinom zagotovitve geodetskega datuma. Na kalibracijskih bazah smo kalibrirali dva terestrična laserska skenerja. Rezultate samokalibracije smo uporabili za določanje dodatnih sistematičnih pogreškov meritev, pri čemer smo uporabili klasično analizo z izravnavo krivulj ter strojno učenje. Prikazana sta dva praktična primera uporabe terestričnega laserskega skeniranja za naloge, kjer je zahtevana visoka natančnost meritev in rezultatov. V termoelektrarni Brestanica preverjamo odklon visokih dimnikov od navpičnice, na pregradi Melje na Dravi pa preizkušamo zaznavanje spremembe oblike ali položaja prelivne stene z inovativno metodo statističnega testiranja sprememb parametrov ravnine.The thesis deals with the optimization of terrestrial laser scanning procedures in terms of increasing the accuracy and reliability of the results and reducing the time and cost of the procedure. The main intent of the dissertation is to calibrate the laser scanner and upgrade it with machine learning procedures. In order to carry out the calibration, we need to establish the procedure for precisely determining the target centers from the scans. We propose a robust high precision process with which we also veri�ed the accuracy of the scanner. Two calibration �elds were established and within them we determined the positions of the points with the classical geodetic methodology with the highest achievable accuracy. We developed self-calibration software with an original method for de�ning geodetic datum. Two terrestrial laser scanners were calibrated on the calibration �elds. The self-calibration results were used to determine the additional systematic errors of the measurements at which we used the classical analysis with curve adjustment as well as machine learning. Two practical examples of the application of the terrestrial laser scanning for tasks that require high accuracy measurements and results are shown. In the thermal power plant Brestanica we determined the inclination of its high chimneys. On the high barrier on the Drava River we tried to detect changes in the shape or position of the over ow wall with the use of an innovative method of statistically testing the changes of the plane parameters