Teoría de decisión bayesiana en los criterios de similitud utilizados en la segmentación de imágenes de rango

El obtener una imagen segmentada correctamente sigue siendo un asunto sin resolverse. Por lo general los resultados obtenidos por un computador al segmentar una imagen contienen sobre-segmentaciones, sub-segmentaciones y bordes mal definidos. En gran parte, estos inconvenientes recaen sobre el criterio de similitud utilizado por los algoritmos de segmentación. En el presente artículo se hace un análisis de los criterios de similitud más utilizados en la literatura y de la utilización de criterios basados en la teoría de decisión bayesiana

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 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

A SEGMENTATION METHOD FOR 3D MESHES OF HISTORIC BUILDINGS

[EN] In this article, a method for 3D mesh segmentation focused on the representation of historic buildings is proposed. This type of buildings are characterized by having singularities and characteristic elements in the facades.The main objective is to recognize these features in the buildings, understanding features as those parts of the model that differ from the main structure of the building, such as doors or windows. The idea is to use a recognition algorithm of flat faces allowing to create a graph that reflects the shape of the three-dimensional model. At a later step, this graph will be matched against some pre-defined graphs that will represent the patterns to look for.[ES] En este artículo se propone un método de segmentación de mallas 3D enfocado a representaciones de edificios históricos.Este tipo de edificios se caracterizan por tener singularidades y elementos caracteristicos en las fachadas. El objetivo principal consiste en reconocer estas características en los edificios, entendiéndose como características aquellas partes del modelo que difieren de la estructura principal del edificio, tales como puertas o ventanas. La idea es utilizar un algoritmo de reconocimiento de caras planas que permita crear un grafo que refleje la forma del modelo tridimensional. En una etapa posterior, este grafo se comparará con grafos predefinidos que conformaran los patrones a buscar.Herráez, BJ.; Vendrell Vidal, E. (2016). UN PROCEDIMIENTO DE SEGMENTACIÓN DE MALLAS 3D DE EDIFICIOS HISTÓRICOS. En 8th International congress on archaeology, computer graphics, cultural heritage and innovation. Editorial Universitat Politècnica de València. 311-313. https://doi.org/10.4995/arqueologica8.2016.3524OCS31131

Image segmentation with adaptive region growing based on a polynomial surface model

A new method for segmenting intensity images into smooth surface segments is presented. The main idea is to divide the image into flat, planar, convex, concave, and saddle patches that coincide as well as possible with meaningful object features in the image. Therefore, we propose an adaptive region growing algorithm based on low-degree polynomial fitting. The algorithm uses a new adaptive thresholding technique with the L∞ fitting cost as a segmentation criterion. The polynomial degree and the fitting error are automatically adapted during the region growing process. The main contribution is that the algorithm detects outliers and edges, distinguishes between strong and smooth intensity transitions and finds surface segments that are bent in a certain way. As a result, the surface segments corresponding to meaningful object features and the contours separating the surface segments coincide with real-image object edges. Moreover, the curvature-based surface shape information facilitates many tasks in image analysis, such as object recognition performed on the polynomial representation. The polynomial representation provides good image approximation while preserving all the necessary details of the objects in the reconstructed images. The method outperforms existing techniques when segmenting images of objects with diffuse reflecting surfaces

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

Teoría de decisión bayesiana en los criterios de similitud utilizados en la segmentación de imágenes de rango

El obtener una imagen segmentada correctamente sigue siendo un asunto sin resolverse. Por lo general los resultados obtenidos por un computador al segmentar una imagen contienen sobre-segmentaciones, sub-segmentaciones y bordes mal definidos. En gran parte, estos inconvenientes recaen sobre el criterio de similitud utilizado por los algoritmos de segmentación. En el presente artículo se hace un análisis de los criterios de similitud más utilizados en la literatura y de la utilización de criterios basados en la teoría de decisión bayesiana

Recognition of one class of quadric surfaces from unstructured point cloud

Critical elements of the state of the art three-dimensional (3D) point cloud processing software are the algorithms for retrieval of high level geometric primitives from raw data. This paper presents a method for recognition of a class of quadric surfaces, in particular for recognition of cylinders, elliptical cylinders, and ellipsoids from 3D point clouds. The method is based on direct least squares fitting of ellipsoids, and it exploits the closeness of scatter matrix to singular in the case when data are sampled for an approximate ellipsoid. This method belongs to the class of region growing methods, and the region is expanded using region growing strategy that is also proposed in this paper. Presented recognition procedure is suitable for segmentation of regions with G1 or higher continuality, and this is its advantage when compared to similar methods. Besides, recognition of quadric surfaces can be performed on unstructured, as well as on structured point clouds. The applicability of the method is illustrated and experimentally verified using two examples that contain G1 continuous surfaces from the considered class. The first example represents synthesized, and the second real-world scanned point cloud