Derivation of an Efficient Rule System Pattern Matcher

Formalizing algorithm derivations is a necessary prerequisite for developing automated algorithm design systems. This report describes a derivation of an algorithm for incrementally matching conjunctive patterns against a growing database. This algorithm, which is modeled on the Rete matcher used in the OPS5 production system, forms a basis for efficiently implementing a rule system. The highlights of this derivation are: (1) a formal specification for the rule system matching problem, (2) derivation of an algorithm for this task using a lattice-theoretic model of conjunctive and disjunctive variable substitutions, and (3) optimization of this algorithm, using finite differencing, for incrementally processing new data.

The Computation of Color

This thesis takes an interdisciplinary approach to the study of color vision, focussing on the phenomenon of color constancy formulated as a computational problem. The primary contributions of the thesis are (1) the demonstration of a formal framework for lightness algorithms; (2) the derivation of a new lightness algorithm based on regularization theory; (3) the synthesis of an adaptive lightness algorithm using "learning" techniques; (4) the development of an image segmentation algorithm that uses luminance and color information to mark material boundaries; and (5) an experimental investigation into the cues that human observers use to judge the color of the illuminant. Other computational approaches to color are reviewed and some of their links to psychophysics and physiology are explored.

A Vector Signal Processing Approach to Color

Surface (Lambertain) color is a useful visual cue for analyzing material composition of scenes. This thesis adopts a signal processing approach to color vision. It represents color images as fields of 3D vectors, from which we extract region and boundary information. The first problem we face is one of secondary imaging effects that makes image color different from surface color. We demonstrate a simple but effective polarization based technique that corrects for these effects. We then propose a systematic approach of scalarizing color, that allows us to augment classical image processing tools and concepts for multi-dimensional color signals.

Role of color in face recognition

One of the key challenges in face perception lies in determining the contribution of different cues to face identification. In this study, we focus on the role of color cues. Although color appears to be a salient attribute of faces, past research has suggested that it confers little recognition advantage for identifying people. Here we report experimental results suggesting that color cues do play a role in face recognition and their contribution becomes evident when shape cues are degraded. Under such conditions, recognition performance with color images is significantly better than that with grayscale images. Our experimental results also indicate that the contribution of color may lie not so much in providing diagnostic cues to identity as in aiding low-level image-analysis processes such as segmentation.

Un jardín con aroma y color.

Seleccionado en la convocatoria: Ayudas a la innovación e investigación educativa en centros docentes de niveles no universitarios, Gobierno de Aragón 2010-11

Color generador de emociones II.

Seleccionado en la convocatoria: Ayudas a la innovación e investigación educativa en centros docentes de niveles no universitarios, Gobierno de Aragón 2008-09

El color generador de emociones en el ámbito de la educación especial.

Seleccionado en la convocatoria: Ayudas a la innovación e investigación educativa en centros docentes de niveles no universitarios, Gobierno de Aragón 2007-08

Estabilització del color de la fracció cel·lular de sang de porc deshidratada per atomització

L’ús de colorants alimentaris pot ser controvertit, ja que la seva presència s’associa amb problemes provocats pel seu consum a llarg termini, o perquè es tem que siguin emprats per dissimular deficiències en la qualitat del producte. Aquesta preocupació és una tendència creixent entre els consumidors i ha portat a moltes empreses del sector alimentari a revisar la formulació dels seus productes i substituir, sempre que sigui econòmica i tecnològicament possible, els colorants artificials per colorants naturals. L’hemoglobina procedent de la sang dels escorxadors industrials podria ser una font important de colorant vermell natural degut a les grans quantitats generades diàriament. A més, s' evitaria que anés a parar a les aigües residuals. El seu ús com a colorant vermell natural queda supeditada al fet de trobar alguna substància o sistema capaç de protegir-la de l’oxidació durant el procés de deshidratació i el posterior període d’emmagatzematge ja que l’hemoglobina és poc estable i es poden produir canvis en el seu color. Inicialment l’hemoglobina presenta un color vermell brillant. La seva desoxigenació comporta un canvi a color porpra. I l’oxidació del ferro confereix a la molècula un indesitjable color marró. En l’estudi que aquí es presenta es pretén estabilitzar el color de l’hemoglobina de sang porcina tant durant la seva deshidratació per atomització com durant l’emmagatzematge a temperatura ambient de la pols obtinguda afegint al concentrat d’hemoglobina, prèviament a la deshidratació, combinacions de diferents substàncies que puguin actuar de manera complementària en l’estabilització del ferro hèmic enfront la seva oxidació. L’objectiu d’aquest treball és determinar si la seva combinació amb agents antioxidants comporta una millora en l’estabilització de la forma reduïda de l’hemoglobina tant durant la deshidratació per atomització com durant l’emmagatzematge de la pols a temperatura ambient

Developmental pattern of digit span in Spanish population

Resumen tomado de la publicaci??n

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Implementation of a robust coded structured light technique for dynamic 3D measurements

This paper presents the implementation details of a coded structured light system for rapid shape acquisition of unknown surfaces. Such techniques are based on the projection of patterns onto a measuring surface and grabbing images of every projection with a camera. Analyzing the pattern deformations that appear in the images, 3D information of the surface can be calculated. The implemented technique projects a unique pattern so that it can be used to measure moving surfaces. The structure of the pattern is a grid where the color of the slits are selected using a De Bruijn sequence. Moreover, since both axis of the pattern are coded, the cross points of the grid have two codewords (which permits to reconstruct them very precisely), while pixels belonging to horizontal and vertical slits have also a codeword. Different sets of colors are used for horizontal and vertical slits, so the resulting pattern is invariant to rotation. Therefore, the alignment constraint between camera and projector considered by a lot of authors is not necessary

An overview of the advantages and constraints of coded pattern projection techniques for autonomous navigation

The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

Espai creatiu. Expressió artística. Arrossegar color: traç

Pastel sobre paper 50 x 65 cm. Treball realitzat en els tallers de l'assignatura troncal d'educació artística de 2n de Mestres d'Educació Infantil durant el curs 2007-08. Ha estat proposat, dirigit i fotografiat o escanejat per la professora Muntsa Calbó, amb l'ajut de Dayan Castañeda