An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 different compositional datasets and modelled the first canonical variable using a segmented regression model solely based on an observation about the scatter plots. In this paper, multiple linear regressions are applied to different datasets to confirm the validity of our proposed model. In addition to dating the unknown tephras by calibration as discussed previously, another method of mapping the unknown tephras into samples of the reference set or missing samples in between consecutive reference samples is proposed. The application of these methodologies is demonstrated with both simulated and real datasets. This new proposed methodology provides an alternative, more acceptable approach for geologists as their focus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age of unknown tephra. Kew words: Tephrochronology; Segmented regression

Application of discriminant function analysis and change-point problem in dating volcanic ashes

The application of Discriminant function analysis (DFA) is not a new idea in the study of tephrochrology. In this paper, DFA is applied to compositional datasets of two different types of tephras from Mountain Ruapehu in New Zealand and Mountain Rainier in USA. The canonical variables from the analysis are further investigated with a statistical methodology of change-point problems in order to gain a better understanding of the change in compositional pattern over time. Finally, a special case of segmented regression has been proposed to model both the time of change and the change in pattern. This model can be used to estimate the age for the unknown tephras using Bayesian statistical calibration

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

SLAM using an Imaging Sonar for Partially Structured Underwater Environments

In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach

Modificació de fibres de jute per l'elaboració de plàstics reforçats reciclables

El treball que s'ha dut a terme es centra en la recerca d'agents modificants per a fibres cel·lulòsiques capaços de reduir la polaritat de les funcions alcohol de la seva estructura per formació de funcions ester. Les fibres de jute se sotmeten a reacció en un sistema tancat provist d'atmòsfera de nitrogen a fi d'evitar reaccions laterals que no són del nostre interés.L'obtenció dels resultats perseguits està lligat a les condicions experimentals aplicades durant les reaccions. La influència de les diferents variables escollides facilitarà en major o menor grau la reacció entre les molècules d'agent d'acoblament i cel·lulosa vinculades. Una gran part de l'atenció es centrarà en l'estudi de l'etapa de modificació, sobretot en l'efectivitat dels reactius addicionats per la reacció amb els grups hidroxil. Un cop comparats els experiments realitzats tant amb clorur d'oleïl com amb anhídrid metacrílic, es conclou que la majoria de condicions provades permeten assolir valors de modificació prou significatius. L'excepció ve donada quan la temperatura utilitzada és de 20ºC, llavors les mateixes condicions que a una temperatura de 60ºC condueixen cap a resultats poc satisfactoris. La reactivitat per part dels dos agents d'acoblament utilitzats no ha estat la mateixa. Els resultats per condicions experimentals del mateix tipus han conduït cap a valors força diferents. Pel que fa a la determinació dels paràmetres òptims es conclou que les variables amb les que el grau de modificació millora considerablement són: una temperatura de 60ºC, 10% de catalitzador respecte la quantitat de clorur d'oleïl o anhídrid addicionada, relació OH reactiu estequiomètrica 1:1 i 40mL de solvent. Un cop modificada la fibra, se sotmet a reacció amb el monòmer estirè. Es comprova que el grau de polimerització segueix el valor de modificació prèviament obtingut, a menor quantitat de funcions alcohol lliures major interacció amb el monòmer estirè. Les propietats inicials de la fibra no es corresponen amb les obtingudes després del tractament, l'increment de la resistència a l'atac de microorganismes i a l'absorció d'humitat s'explica per una reducció de la presència de funcions alcohol polars i per la capa d'estirè polimeritzat per unió amb els dobles enllaços introduïts amb els agents d'acoblament. Pel que fa referència a les dues tècniques de caracterització més utilitzades, l'anàlisis elemental permet quantificar d'una manera precisa la reacció de la fibra amb els agents d'acoblament i la posterior reacció de la fibra modificada amb el monòmer estirè. La caracterització per espectroscopia d'infraroig permet comprovar qualitativament la reactivitat del clorur d'oleïl i qualitativament-quantitativament la de l'anhídrid metacrílic amb les funcions alcohol de la cel·lulosa present en les fibres de jute. Els pics més característics apareguts seran utilitzats per avaluar la reactivitat de la funció carbonílica del reactiu modificant amb l'estructura cel·lulòsica i del doble enllaç de la cel·lulosa modificada amb la matriu polimèrica.

An approach to coded structured light to obtain three dimensional information

The human visual ability to perceive depth looks like a puzzle. We perceive three-dimensional spatial information quickly and efficiently by using the binocular stereopsis of our eyes and, what is mote important the learning of the most common objects which we achieved through living. Nowadays, modelling the behaviour of our brain is a fiction, that is why the huge problem of 3D perception and further, interpretation is split into a sequence of easier problems. A lot of research is involved in robot vision in order to obtain 3D information of the surrounded scene. Most of this research is based on modelling the stereopsis of humans by using two cameras as if they were two eyes. This method is known as stereo vision and has been widely studied in the past and is being studied at present, and a lot of work will be surely done in the future. This fact allows us to affirm that this topic is one of the most interesting ones in computer vision. The stereo vision principle is based on obtaining the three dimensional position of an object point from the position of its projective points in both camera image planes. However, before inferring 3D information, the mathematical models of both cameras have to be known. This step is known as camera calibration and is broadly describes in the thesis. Perhaps the most important problem in stereo vision is the determination of the pair of homologue points in the two images, known as the correspondence problem, and it is also one of the most difficult problems to be solved which is currently investigated by a lot of researchers. The epipolar geometry allows us to reduce the correspondence problem. An approach to the epipolar geometry is describes in the thesis. Nevertheless, it does not solve it at all as a lot of considerations have to be taken into account. As an example we have to consider points without correspondence due to a surface occlusion or simply due to a projection out of the camera scope. The interest of the thesis is focused on structured light which has been considered as one of the most frequently used techniques in order to reduce the problems related lo stereo vision. Structured light is based on the relationship between a projected light pattern its projection and an image sensor. The deformations between the pattern projected into the scene and the one captured by the camera, permits to obtain three dimensional information of the illuminated scene. This technique has been widely used in such applications as: 3D object reconstruction, robot navigation, quality control, and so on. Although the projection of regular patterns solve the problem of points without match, it does not solve the problem of multiple matching, which leads us to use hard computing algorithms in order to search the correct matches. In recent years, another structured light technique has increased in importance. This technique is based on the codification of the light projected on the scene in order to be used as a tool to obtain an unique match. Each token of light is imaged by the camera, we have to read the label (decode the pattern) in order to solve the correspondence problem. The advantages and disadvantages of stereo vision against structured light and a survey on coded structured light are related and discussed. The work carried out in the frame of this thesis has permitted to present a new coded structured light pattern which solves the correspondence problem uniquely and robust. Unique, as each token of light is coded by a different word which removes the problem of multiple matching. Robust, since the pattern has been coded using the position of each token of light with respect to both co-ordinate axis. Algorithms and experimental results are included in the thesis. The reader can see examples 3D measurement of static objects, and the more complicated measurement of moving objects. The technique can be used in both cases as the pattern is coded by a single projection shot. Then it can be used in several applications of robot vision. Our interest is focused on the mathematical study of the camera and pattern projector models. We are also interested in how these models can be obtained by calibration, and how they can be used to obtained three dimensional information from two correspondence points. Furthermore, we have studied structured light and coded structured light, and we have presented a new coded structured light pattern. However, in this thesis we started from the assumption that the correspondence points could be well-segmented from the captured image. Computer vision constitutes a huge problem and a lot of work is being done at all levels of human vision modelling, starting from a)image acquisition; b) further image enhancement, filtering and processing, c) image segmentation which involves thresholding, thinning, contour detection, texture and colour analysis, and so on. The interest of this thesis starts in the next step, usually known as depth perception or 3D measurement.