Recognition of elliptical segments in scanned lines

Cylindrical surfaces, as one of the most frequent surfaces in mechanical engineering, are represented by elliptical (circular) or linear segments in scanned lines within structured point cloud. Having this in mind, segmentation and fitting of elliptical regions is a very important issue in the recognition of cylindrical surfaces. This paper presents the research in the recognition of elliptical (or circular) segments in scanned lines. Segments connected with G1 (or higher) continuity are considered. Presented method is based on seed independent region growing using direct least squares fitting of ellipses. The method is tested in the case studies considering synthesized as well as real world (scanned lines) examples

Recognition of one class of surfaces from structured point cloud

U određenim oblastima industrije postoji potreba za generisanjem kompjuterskih modela objekata samo na osnovu njihove fizičke realizacije, a bez unapred poznatih konstrukcionih ili tehnoloških informacija. Pri realizaciji ovakvih zahteva istaknuto mesto zauzimaju tzv. tehnike reverznog inženjerstva geometrijskih modela. Bitnu fazu primene navedenih tehnika predstavlja prepoznavanje geometrijskih primitiva od kojih se posmatrani objekat sastoji. U ovom radu predstavljen je metod za segmentaciju i prepoznavanje G1 kontinualnih površina koje su u skenirnim linijama struktuiranog oblaka predstavljene eliptičnim segmentima. Predloženi algoritam je pre svega namenjen za prepoznavanje eliptičkih cilindara, elipsoida i eliptičkih torusa, ali se u zavisnosti od načina skeniranja dela, može koristiti i za prepoznavanje još nekih površi drugog reda. Proces segmentacije je zasnovan na prepoznavanju eliptičkih segmenata u skeniranim linijama, a na osnovu osobina singulariteta informacione matrice pri regresionoj analizi metodom najmanjih kvadrata. Verifikacija predloženog metoda je izvršena procesiranjem tri sintetizovana, kao i jednog realnog oblaka tačaka.This paper presents a method for recognition of surfaces represented by elliptical segments in structured three dimensional (3D) point clouds. The method is based on direct least squares fitting of ellipses in scanned lines. By recognizing elliptical segments in both directions of structured cloud it is possible to efficiently allocate G1 (and higher) continuous regions which represent a certain class of surfaces. The proposed method is primarily developed for recognition of elliptical cylinders and ellipsoids, including cylinders and spheres. Depending on scanning mode, the method can be employed for recognition of other second degree surfaces like cones. Besides, as presented in the paper, the method can be utilized for recognition of certain class of higher degree surfaces such as elliptical tori. The proposed method is experimentally verified using several synthesized point clouds as well as using a real world case study

Etat de l'art de la segmentation de maillage 3D par patchs surfaciques

National audienceLa segmentation de maillage 3D est une composante essentielle de nombreuses applications. Elle se décline en deux familles : la segmentation en patchs surfaciques et la segmentation en parties significatives. Dans cet article, nous traitons principalement de la segmentation de maillages 3D en patchs surfaciques et en proposons un état de l'art. Nous positionnons le contexte de ce type de segmentation et discutons des contributions les plus pertinentes

Recognition of one class of quadrics from 3D point clouds

Within cyber physical production systems 3D vision as a source of information from real-world provides enormous possibilities. While the hardware of contemporary 3D scanners is characterized by high speed along with high resolution and accuracy, there is a lack of real-time online data processing algorithms that would give certain elements of intelligence to the sensory system. Critical elements of data processing software are efficient, real-time applicable methods for fully automatic recognition of high level geometric primitives from point cloud (surface segmentation and fitting). This paper presents a method for recognition of one class of quadrics from 3D point clouds, in particular for recognition of cylinders, elliptical cylinders and ellipsoids. The method is based on the properties of scatter matrix during direct least squares fitting of ellipsoids. Presented recognition procedure can be employed for segmentation of regions with G1 or higher continuity, and this is its comparative advantage to similar methods. The applicability of the method is illustrated and experimentally verified using two case studies. First case study refers to a synthesized, and the second to a real-world scanned point cloud

Recognition of quadrics from 3d point clouds generated by scanning of rotational parts

This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.*Ovaj rad je izabran sa konferencije 12th International Scientific Conference MMA 2015 - Flexible Technologies, i publikovan u casopisu Journal of Production Engineering

Recognition of one class of quadrics from 3D point clouds

Within cyber physical production systems 3D vision as a source of information from real-world provides enormous possibilities. While the hardware of contemporary 3D scanners is characterized by high speed along with high resolution and accuracy, there is a lack of real-time online data processing algorithms that would give certain elements of intelligence to the sensory system. Critical elements of data processing software are efficient, real-time applicable methods for fully automatic recognition of high level geometric primitives from point cloud (surface segmentation and fitting). This paper presents a method for recognition of one class of quadrics from 3D point clouds, in particular for recognition of cylinders, elliptical cylinders and ellipsoids. The method is based on the properties of scatter matrix during direct least squares fitting of ellipsoids. Presented recognition procedure can be employed for segmentation of regions with G1 or higher continuity, and this is its comparative advantage to similar methods. The applicability of the method is illustrated and experimentally verified using two case studies. First case study refers to a synthesized, and the second to a real-world scanned point cloud

Recognition of quadrics from 3d point clouds generated by scanning of rotational parts

This paper presents a method for recognition of second order surfaces (quadrics) from point clouds containing information about scanned rotational parts. The method is region growing method that exploits the scatter of data during least squares fitting of quadrics as a region growing criterion. The presented procedure is convenient for segmentation of regions with high (G1 or higher) continuity. Besides, the region seed point is automatically selected which is its comparative advantage to a number of existing methods. The applicability of the proposed method is evaluated using two case studies; the first case study refers to a synthesized signal, and the second presents the applicability of the method on a real world example.*Ovaj rad je izabran sa konferencije 12th International Scientific Conference MMA 2015 - Flexible Technologies, i publikovan u casopisu Journal of Production Engineering

Solid NURBS Conforming Scaffolding for Isogeometric Analysis

This work introduces a scaffolding framework to compactly parametrise solid structures with conforming NURBS elements for isogeometric analysis. A novel formulation introduces a topological, geometrical and parametric subdivision of the space in a minimal plurality of conforming vectorial elements. These determine a multi-compartmental scaffolding for arbitrary branching patterns. A solid smoothing paradigm is devised for the conforming scaffolding achieving higher than positional geometrical and parametric continuity. Results are shown for synthetic shapes of varying complexity, for modular CAD geometries, for branching structures from tessellated meshes and for organic biological structures from imaging data. Representative simulations demonstrate the validity of the introduced scaffolding framework with scalable performance and groundbreaking applications for isogeometric analysis