Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Java 3D

Tämä insinöörityö kertoo Java 3D -ohjelmointirajapinnan perusteista ja sen käytöstä kolmiulotteisen tietokonegrafiikan luomisessa Java ohjelmointikielellä. Java 3D on rajapinta Java-ohjelmointikielelle, jonka avulla voidaan luoda ja käsitellä kolmiulotteista tietokonegrafiikkaa. Java 3D -rajapinnan avulla käsitellään kolmiulotteista tietokonegrafiikka erityisen maisemagraafimallin avulla. Maisemagraafi on binääripuuta muistuttava malli, joka mahdollistaa kolmiulotteisten kohteiden ja niille tapahtuvien muunnoksien käsittelyn hierarkisessa järjestyksessä. Työssä käydään läpi Java 3D -maisemagraafien luominen ja kolmiulotteisessa avaruudessa sijaitseville kappaleille tehtäviä perusoperaatioita kuten siirtoa ja kiertoa. Lisäksi käydään läpi myös erilaisia animoinnissa ja interaktiossa käytettäviä luokkia, joiden avulla ohjelmoija saa automatisoitua muunnoksia sekä käyttäjä voi antaa syötteitä hiirellä ja näppäimistöllä. Näiden lisäksi käydään läpi myös mallin valaistusta, varjoja, teksturointia sekä omien kolmiulotteisten mallien tuontia Java 3D -maailmaan. Opinnäytetyön yhteydessä on tehty myös kirjo erilaisia esimerkkejä, jotka ovat saatavilla verkkosivustolta osoitteessa http://www.pahvilaatikko.org/j3d lisäksi kopio verkkosivustosta löytyy myös opinnäytetyön mukana tulevalta cd-levyltä.

3D Surface Modeling From Point Clouds

The goal of this thesis is to implement software for creating 3D models from point clouds. Point clouds are acquired with stereo cameras, monocular systems or laser scanners. The created 3D models are triangular models or NURBS (Non-Uniform Rational B-Splines) models. Triangular models are constructed from selected areas from the point clouds and resulted triangular models are translated into a set of quads. The quads are further translated into an estimated grid structure and used for NURBS surface approximation. Finally, we have a set of NURBS surfaces which represent the whole model. The problem wasn’t so easy to solve. The selected triangular surface reconstruction algorithm did not deal well with noise in point clouds. To handle this problem, a clustering method is introduced for simplificating the model and removing noise. As we had better results with the smaller point clouds produced by clustering, we used points in clusters to better estimate the grids for NURBS models. The overall results were good when the point cloud did not have much noise. The point clouds with small amount of error had good results as the triangular model was solid. NURBS surface reconstruction performed well on solid models.

3D kinematics of the near-IR HH 223 outflow in L723

In this work, we derive the full 3D kinematics of the near-infrared outflow HH 223, located in the dark cloud Lynds 723 (L723), where a well-defined quadrupolar CO outflow is found. HH 223 appears projected on to the two lobes of the eastwest CO outflow. The radio continuum source VLA 2, towards the centre of the CO outflow, harbours a multiple system of low-mass young stellar objects. One of the components has been proposed to be the exciting source of the eastwest CO outflow. From the analysis of the kinematics, we get further evidence on the relationship between the near-infrared and CO outflows and on the location of their exciting source. The proper motions were derived using multi-epoch, narrow-band H2 (2.122 μm line) images. Radial velocities were derived from the 2.122 μm line of the spectra. Because of the extended (∼5 arcmin), S-shaped morphology of the target, the spectra were obtained with the multi-object-spectroscopy (MOS) observing mode using the instrument Long-Slit Intermediate Resolution Infrared Spectrograph (LIRIS) at the 4.2 m William Herschel Telescope. To our knowledge, this work is the first time that MOS observing mode has been successfully used in the near-infrared range for an extended target.

Um novo modelo para os sítios de interação dos antagonistas H2, baseado na caracterização química dos sítios primário e secundário por QSAR- 3D

A new model for the H2 antagonists binding site is postulated based on adsorption coefficient values of sixteen antagonists, in the affinities constants of the primary and secondary binding sites, and in the chemical characterization of these sites by 3D-QSAR. All study compounds are in the extended conformation and deprotonated form. The lateral validation of the QSARs, CoMFA analysis, affinity constants and chemical similarity data suggest that the antagonists block the proton pump in the H2 receptor interacting with two tyrosines - one in the helix 5, and other in the helix 6.

Simulations of 3D Stripixel Detectors

Large Hadron Collider (LHC) is the main particle accelerator at CERN. LHC is created with main goal to search elementary particles and help science investigate our universe. Radiation in LHC is caused by charged particles circular acceleration, therefore detectors tracing particles in existed severe conditions during the experiments must be radiation tolerant. Moreover, further upgrade of luminosity (up to 1035 cm-2s-1) requires development of particle detector’s structure. This work is dedicated to show the new type 3D stripixel detector with serious structural improvement. The new type of radiation-hard detector has a three-dimensional (3D) array of the p+ and n+ electrodes that penetrate into the detector bulk. The electrons and holes are then collected at oppositely biased electrodes. Proposed 3D stripixel detector demonstrates that full depletion voltage is lower that that for planar detectors. Low depletion voltage is one of the main advantages because only depleted part of the device is active are. Because of small spacing between electrodes, charge collection distances are smaller which results in high speed of the detector’s response. In this work is also briefly discussed dual-column type detectors, meaning consisting both n+ and p+ type columnar electrodes in its structure, and was declared that dual-column detectors show better electric filed distribution then single sided radiation detectors. The dead space or in other words low electric field region in significantly suppressed. Simulations were carried out by using Atlas device simulation software. As a simulation results in this work are represented the electric field distribution under different bias voltages.

Modelling syntectonic sedimentation: combining a discrete element model of tectonic. Deformation and process-based sedimentary Model in 3D.

This paper presents a new numerical program able to model syntectonic sedimentation. The new model combines a discrete element model of the tectonic deformation of a sedimentary cover and a process-based model of sedimentation in a single framework. The integration of these two methods allows us to include the simulation of both sedimentation and deformation processes in a single and more effective model. The paper describes briefly the antecedents of the program, Simsafadim-Clastic and a discrete element model, in order to introduce the methodology used to merge both programs to create the new code. To illustrate the operation and application of the program, analysis of the evolution of syntectonic geometries in an extensional environment and also associated with thrust fault propagation is undertaken. Using the new code, much more complex and realistic depositional structures can be simulated together with a more complex analysis of the evolution of the deformation within the sedimentary cover, which is seen to be affected by the presence of the new syntectonic sediments.

Image Segmentation Using Information Bottleneck Method

In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Reconeixement de gestos de la mà amb el sensor Kinect

El reconeixement dels gestos de la mà (HGR, Hand Gesture Recognition) és actualment un camp important de recerca degut a la varietat de situacions en les quals és necessari comunicar-se mitjançant signes, com pot ser la comunicació entre persones que utilitzen la llengua de signes i les que no. En aquest projecte es presenta un mètode de reconeixement de gestos de la mà a temps real utilitzant el sensor Kinect per Microsoft Xbox, implementat en un entorn Linux (Ubuntu) amb llenguatge de programació Python i utilitzant la llibreria de visió artifical OpenCV per a processar les dades sobre un ordinador portàtil convencional. Gràcies a la capacitat del sensor Kinect de capturar dades de profunditat d’una escena es poden determinar les posicions i trajectòries dels objectes en 3 dimensions, el que implica poder realitzar una anàlisi complerta a temps real d’una imatge o d’una seqüencia d’imatges. El procediment de reconeixement que es planteja es basa en la segmentació de la imatge per poder treballar únicament amb la mà, en la detecció dels contorns, per després obtenir l’envolupant convexa i els defectes convexos, que finalment han de servir per determinar el nombre de dits i concloure en la interpretació del gest; el resultat final és la transcripció del seu significat en una finestra que serveix d’interfície amb l’interlocutor. L’aplicació permet reconèixer els números del 0 al 5, ja que s’analitza únicament una mà, alguns gestos populars i algunes de les lletres de l’alfabet dactilològic de la llengua de signes catalana. El projecte és doncs, la porta d’entrada al camp del reconeixement de gestos i la base d’un futur sistema de reconeixement de la llengua de signes capaç de transcriure tant els signes dinàmics com l’alfabet dactilològic.

Polarimetric 3D integral imaging in photon-starved conditions

We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging.

Estudos de QSAR 3D para um conjunto de inibidores de butirilcolinesterase humana

Alzheimer's disease (AD) is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE) can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs) and high predictive power (r²predict=0.88). Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.

Identificação de adulteração de biocombustível por adição de óleo residual ao diesel por espectrofluorimetria total 3D e análise das componentes principais

Total spectrofluorimetry associated to Principal Components Analysis (PCA) were used to classify into different groups the samples of diesel oil, biodiesel, vegetal oil and residual oil, as well as, to identify addition of non-transesterified residual vegetable oil, instead of biodiesel, to the diesel oil. Using this method, the samples of diesel oil, mixtures of biodiesel in diesel and mixtures of residual oil in diesel were separated into well-defined groups.