Mealiness assessment in fruits using MRI techniques.

Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure). Previous studies propose the definition of mealiness as the lack of crispiness, of hardness and of juiciness. Current aims are focused on establishing non destructive tests for mealiness assessment. MultiSliceMultiEcho Magnetic resonance images (MRI, 64*64pixels) have been taken corresponding to a 3ms of Echo time. Small samples of Top Red apples stored 6 months at controlled atmosphere (expected to be non mealy) and 2°C (expected to be mealy) have been used for MRI imaging. Three out of four apples corresponding to the sample maintained at controlled atmosphere did not develop mealiness while three out of four fruits corresponding to the sample stored at 2°C became mealy after 6 month of storage. The minimum T2 values/image obtained for the mealy apples shows to be significantly lower when compared with non mealy apples pointing that a more dis-aggregated structure leads to a quicker loss of signal Also, there is a significant linear correlation (r=-0.76) between the number of pixels with a T2 value below 35ms within a fruit image and the deformation parameter registered during the Magness-Taylor firmness test. Finally, all the T2 images of the mealy apples show a regional variation of contrast which is not shown for non mealy apples. This variation of contrast is similar to the MRI images of water-cored apples indicating that in these cases there is a differential water movement that may precede the internal browning.

Mealiness assessment in apples and peaches using MRI techniques.

Since Januarv 1946 a wade EC Project entitled "Mealiness in fruits Consumers perception and means for detection is being carried out. Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure) Previous studies propose the definition of mealiness as the lack of crispiness of hardness and of juiciness. A destructive instrumental procedure combined with a integration technique has been already developed enabling to identify mealy fruits by destructive instrumental means use other contributions of Barreiro and Ortiz to this Ag Eng 98. Current aims .are focused on establishing non destructive tests for mealiness assessment. Magnetic resonance Imaging (MRI) makes use of the magnetic properties that some atomic nuclei have. especially hidrogen nuclei from water molecules to obtain high quality images in the field of internal quality evaluation the MRI has been used to assess internal injury due to conservation as o treatments as chilling injury un Persimmons Clark&Forbes (1994) and water-core in apples (Wang et al. 1998. In the case of persimmons the chilling injury is described as an initial tissue breakdown and lack of cohesion between cells followed by formation of a firm gel and by a lack of juiciness without changes in the total amount ol water content. Also a browning of the flesh is indicated (Clark&Forhes 1994). This definition fits into the previous description of mealiness.

Offshore remote sensing of the ocean by stereo vision systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss future lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

A new approach to change detection in multispectral images by means of ERGAS index

In this letter, we propose a novel method for unsupervised change detection (CD) in multitemporal Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) satellite images by using the relative dimensionless global error in synthesis index locally. In order to obtain the change image, the index is calculated around a pixel neighborhood (3x3 window) processing simultaneously all the spectral bands available. With the objective of finding the binary change masks, six thresholding methods are selected. A comparison between the proposed method and the change vector analysis method is reported. The accuracy CD showed in the experimental results demonstrates the effectiveness of the proposed method.

Aerial video geo-registration using terrain models from dense and coherent stereo matching

In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects and fusion of data acquired from multiple sensors. To solve this problem there are different approaches that require, in addition to a precise characterization of the camera sensor, high resolution referenced images or terrain elevation models, which are usually not publicly available or out of date. Building upon the idea of developing technology that does not need a reference terrain elevation model, we propose a geo-registration technique that applies variational methods to obtain a dense and coherent surface elevation model that is used to replace the reference model. The surface elevation model is built by interpolation of scattered 3D points, which are obtained in a two-step process following a classical stereo pipeline: first, coherent disparity maps between image pairs of a video sequence are estimated and then image point correspondences are back-projected. The proposed variational method enforces continuity of the disparity map not only along epipolar lines (as done by previous geo-registration techniques) but also across them, in the full 2D image domain. In the experiments, aerial images from synthetic video sequences have been used to validate the proposed technique.

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

Mulch materials in processing tomato: a multivariate approach.

Mulch materials of different origins have been introduced into the agricultural sector in recent years alternatively to the standard polyethylene due to its environmental impact. This study aimed to evaluate the multivariate response of mulch materials over three consecutive years in a processing tomato (Solanum lycopersicon L.) crop in Central Spain. Two biodegradable plastic mulches (BD1, BD2), one oxo-biodegradable material (OB), two types of paper (PP1, PP2), and one barley straw cover (BS) were compared using two control treatments (standard black polyethylene [PE] and manual weed control [MW]). A total of 17 variables relating to yield, fruit quality, and weed control were investigated. Several multivariate statistical techniques were applied, including principal component analysis, cluster analysis, and discriminant analysis. A group of mulch materials comprised of OB and BD2 was found to be comparable to black polyethylene regarding all the variables considered. The weed control variables were found to be an important source of discrimination. The two paper mulches tested did not share the same treatment group membership in any case: PP2 presented a multivariate response more similar to the biodegradable plastics, while PP1 was more similar to BS and MW. Based on our multivariate approach, the materials OB and BD2 can be used as an effective, more environmentally friendly alternative to polyethylene mulches.

Transformer-coupled converter for voltage modulation techniques

In high performance digital systems as well as in RF systems, voltage scaling and modulation techniques have been adopted to achieve a more efficient processing of the energy. The implementation of such techniques relies on a power supply that is capable of rapidly adjusting the system supply voltage. In this paper, a pulsewidth modulation multiphase topology with magnetic coupling is proposed for its use in voltage modulation techniques. Since the magnetic coupling in this topology is done with transformers instead of coupled inductors, the energy storage is reduced and very fast voltage changes are achieved. Advantages and drawbacks of this topology have been previously presented in the literature and in this paper, the design criteria for implementing a power supply for the envelope elimination and restoration technique in an RF system are presented along with an implementation of the power supply.

A novel FPGA-based evolvable hardware system based on multiple processing arrays

In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications.

Refined facial disparity maps for automatic creation of 3D avatars

We propose a new method to automatically refine a facial disparity map obtained with standard cameras and under conventional illumination conditions by using a smart combination of traditional computer vision and 3D graphics techniques. Our system inputs two stereo images acquired with standard (calibrated) cameras and uses dense disparity estimation strategies to obtain a coarse initial disparity map, and SIFT to detect and match several feature points in the subjects face. We then use these points as anchors to modify the disparity in the facial area by building a Delaunay triangulation of their convex hull and interpolating their disparity values inside each triangle. We thus obtain a refined disparity map providing a much more accurate representation of the the subjects facial features. This refined facial disparity map may be easily transformed, through the camera calibration parameters, into a depth map to be used, also automatically, to improve the facial mesh of a 3D avatar to match the subjects real human features.

Application of NMR techniques for the evaluation of fruit internal quality and physical properties of food

Los alimentos son sistemas complejos, formados por diversas estructuras a diferentes escalas: macroscópica y microscópica. Muchas propiedades de los alimentos, que son importantes para su procesamiento, calidad y tratamiento postcosecha, están relacionados con su microestructura. La presente tesis doctoral propone una metodología completa para la determinación de la estructura de alimentos desde un punto de vista multi-escala, basándose en métodos de Resonancia Magnética Nuclear (NMR). Las técnicas de NMR son no invasivas y no destructivas y permiten el estudio tanto de macro- como de microestructura. Se han utilizado distintos procedimientos de NMR dependiendo del nivel que se desea estudiar. Para el nivel macroestructural, la Imagen de Resonancia Magnética (MRI) ha resultado ser muy útil para la caracterización de alimentos. Para el estudio microestructural, la MRI requiere altos tiempos de adquisición, lo que hace muy difícil la transferencia de esta técnica a aplicaciones en industria. Por tanto, la optimización de procedimientos de NMR basados en secuencias relaxometría 2D T1/T2 ha resultado ser una estrategia primordial en esta tesis. Estos protocolos de NMR se han implementado satisfactoriamente por primera vez en alto campo magnético. Se ha caracterizado la microestructura de productos alimentarios enteros por primera vez utilizando este tipo de protocolos. Como muestras, se han utilizado dos tipos de productos: modelos de alimentos y alimentos reales (manzanas). Además, como primer paso para su posterior implementación en la industria agroalimentaria, se ha mejorado una línea transportadora, especialmente diseñada para trabajar bajo condiciones de NMR en trabajos anteriores del grupo LPF-TAGRALIA. Se han estudiado y seleccionado las secuencias más rápidas y óptimas para la detección de dos tipos de desórdenes internos en manzanas: vitrescencia y roturas internas. La corrección de las imágenes en movimiento se realiza en tiempo real. Asimismo, se han utilizado protocolos de visión artificial para la clasificación automática de manzanas potencialmente afectadas por vitrescencia. El presente documento está dividido en diferentes capítulos: el Capítulo 2 explica los antecedentes de la presente tesis y el marco del proyecto en el que se ha desarrollado. El Capítulo 3 recoge el estado del arte. El Capítulo 4 establece los objetivos de esta tesis doctoral. Los resultados se dividen en cinco sub-secciones (dentro del Capítulo 5) que corresponden con los trabajos publicados bien en revistas revisadas por pares, bien en congresos internacionales o bien como capítulos de libros revisados por pares. La Sección 5.1. es un estudio del desarrollo de la vitrescencia en manzanas mediante MRI y lo relaciona con la posición de la fruta dentro de la copa del árbol. La Sección 5.2 presenta un trabajo sobre macro- y microestructura en modelos de alimentos. La Sección 5.3 es un artículo en revisión en una revista revisada por pares, en el que se hace un estudio microestrcutural no destructivo mediante relaxometría 2D T1/T2. la Sección 5.4, hace una comparación entre manzanas afectadas por vitrescencia mediante dos técnicas: tomografía de rayos X e MRI, en manzana. Por último, en la Sección 5.5 se muestra un trabajo en el que se hace un estudio de secuencias de MRI en línea para la evaluación de calidad interna en manzanas. Los siguientes capítulos ofrecen una discusión y conclusiones (Capítulo 6 y 7 respectivamente) de todos los capítulos de esta tesis doctoral. Finalmente, se han añadido tres apéndices: el primero con una introducción de los principios básicos de resonancia magnética nuclear (NMR) y en los otros dos, se presentan sendos estudios sobre el efecto de las fibras en la rehidratación de cereales de desayuno extrusionados, mediante diversas técnicas. Ambos trabajos se presentaron en un congreso internacional. Los resultados más relevantes de la presente tesis doctoral, se pueden dividir en tres grandes bloques: resultados sobre macroestructura, resultados sobre microestructura y resultados sobre MRI en línea. Resultados sobre macroestructura: - La imagen de resonancia magnética (MRI) se aplicó satisfactoriamente para la caracterización de macroestructura. En particular, la reconstrucción 3D de imágenes de resonancia magnética permitió identificar y caracterizar dos tipos distintos de vitrescencia en manzanas: central y radial, que se caracterizan por el porcentaje de daño y la conectividad (número de Euler). - La MRI proveía un mejor contraste para manzanas afectadas por vitrescencia que las imágenes de tomografía de rayos X (X-Ray CT), como se pudo verificar en muestras idénticas de manzana. Además, el tiempo de adquisición de la tomografía de rayos X fue alrededor de 12 veces mayor (25 minutos) que la adquisición de las imágenes de resonancia magnética (2 minutos 2 segundos). Resultados sobre microestructura: - Para el estudio de microestructura (nivel subcelular) se utilizaron con éxito secuencias de relaxometría 2D T1/T2. Estas secuencias se usaron por primera vez en alto campo y sobre piezas de alimento completo, convirtiéndose en una forma no destructiva de llevar a cabo estudios de microestructura. - El uso de MRI junto con relaxometría 2D T1/T2 permite realizar estudios multiescala en alimentos de forma no destructiva. Resultados sobre MRI en línea: - El uso de imagen de resonancia magnética en línea fue factible para la identificación de dos tipos de desórdenes internos en manzanas: vitrescencia y podredumbre interna. Las secuencias de imagen tipo FLASH resultaron adecuadas para la identificación en línea de vitrescencia en manzanas. Se realizó sin selección de corte, debido a que la vitrescencia puede desarrollarse en cualquier punto del volumen de la manzana. Se consiguió reducir el tiempo de adquisición, de modo que se llegaron a adquirir 1.3 frutos por segundos (758 ms por fruto). Las secuencias de imagen tipo UFLARE fueron adecuadas para la detección en línea de la podredumbre interna en manzanas. En este caso, se utilizó selección de corte, ya que se trata de un desorden que se suele localizar en la parte central del volumen de la manzana. Se consiguió reducir el tiempo de adquisicón hasta 0.67 frutos por segundo (1475 ms por fruto). En ambos casos (FLASH y UFLARE) fueron necesarios algoritmos para la corrección del movimiento de las imágenes en tiempo real. ABSTRACT Food is a complex system formed by several structures at different scales: macroscopic and microscopic. Many properties of foods that are relevant to process engineering or quality and postharvest treatments are related to their microstructure. This Ph.D Thesis proposes a complete methodology for food structure determination, in a multiscale way, based on the Nuclear Magnetic Resonance (NMR) phenomenon since NMR techniques are non-invasive and non-destructive, and allow both, macro- and micro-structure study. Different NMR procedures are used depending on the structure level under study. For the macrostructure level, Magnetic Resonance Imaging (MRI) revealed its usefulness for food characterization. For microstructure insight, MRI required high acquisition times, which is a hindrance for transference to industry applications. Therefore, optimization of NMR procedures based on T1/T2 relaxometry sequences was a key strategy in this Thesis. These NMR relaxometry protocols, are successfully implemented in high magnetic field. Microstructure of entire food products have been characterized for the first time using these protocols. Two different types of food products have been studied: food models and actual food (apples). Furthermore, as a first step for the food industry implementation, a grading line system, specially designed for working under NMR conditions in previous works of the LPF-TAGRALIA group, is improved. The study and selection of the most suitable rapid sequence to detect two different types of disorders in apples (watercore and internal breakdown) is performed and the real time image motion correction is applied. In addition, artificial vision protocols for the automatic classification of apples potentially affected by watercore are applied. This document is divided into seven different chapters: Chapter 2 explains the thesis background and the framework of the project in which it has been worked. Chapter 3 comprises the state of the art. Chapter 4 establishes de objectives of this Ph.D thesis. The results are divided into five different sections (in Chapter 5) that correspond to published peered reviewed works. Section 5.1 assesses the watercore development in apples with MRI and studies the effect of fruit location in the canopy. Section 5.2 is an MRI and 2D relaxometry study for macro- and microstructure assessment in food models. Section 5.3 is a non-destructive microstructural study using 2D T1/T2 relaxometry on watercore affected apples. Section 5.4 makes a comparison of X-ray CT and MRI on watercore disorder of different apple cultivars. Section 5.5, that is a study of online MRI sequences for the evaluation of apple internal quality. The subsequent chapters offer a general discussion and conclusions (Chapter 6 and Chapter 7 respectively) of all the works performed in the frame of this Ph.D thesis (two peer reviewed journals, one book chapter and one international congress).Finally, three appendices are included in which an introduction to NMR principles is offered and two published proceedings regarding the effect of fiber on the rehydration of extruded breakfast cereal are displayed. The most relevant results can be summarized into three sections: results on macrostructure, results on microstructure and results on on-line MRI. Results on macrostructure: - MRI was successfully used for macrostructure characterization. Indeed, 3D reconstruction of MRI in apples allows to identify two different types of watercore (radial and block), which are characterized by the percentage of damage and the connectivity (Euler number). - MRI provides better contrast for watercore than X-Ray CT as verified on identical samples. Furthermore, X-Ray CT images acquisition time was around 12 times higher (25 minutes) than MRI acquisition time (2 minutes 2 seconds). Results on microstructure: - 2D T1/T2 relaxometry were successfully applied for microstructure (subcellular level) characterization. 2D T1/T2 relaxometry sequences have been applied for the first time on high field for entire food pieces, being a non-destructive way to achieve microstructure study. - The use of MRI together with 2D T1/T2 relaxometry sequences allows a non-destructive multiscale study of food. Results on on-line MRI: - The use of on-line MRI was successful for the identification of two different internal disorders in apples: watercore and internal breakdown. FLASH imaging was a suitable technique for the on-line detection of watercore disorder in apples, with no slice selection, since watercore is a physiological disorder that may be developed anywhere in the apple volume. 1.3 fruits were imaged per second (768 ms per fruit). UFLARE imaging is a suitable sequence for the on-line detection of internal breakdown disorder in apples. Slice selection was used, as internal breakdown is usually located in the central slice of the apple volume. 0.67 fruits were imaged per second (1475 ms per fruit). In both cases (FLASH and UFLARE) motion correction was performed in real time, during the acquisition of the images.

Fractal analysis of laplacian pyramidal filters applied to segmentation of soil images

The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. The required properties to the pyramidal filter produce a family of filters, which is unipara metrical in the case of the classical problem, when the length of the filter is 5. We pay attention to gaussian and fractal behaviour of these basis functions (or filters), and we determine the gaussian and fractal ranges in the case of single parameter ?. These fractal filters loose less energy in every step of the laplacian pyramid, and we apply this property to get threshold values for segmenting soil images, and then evaluate their porosity. Also, we evaluate our results by comparing them with the Otsu algorithm threshold values, and conclude that our algorithm produce reliable test results.

Generación de una librería RVC - CAL para la etapa de estimación de abundancias en el proceso de análisis de imágenes hiperespectrales

Las imágenes hiperespectrales permiten extraer información con una gran resolución espectral, que se suele extender desde el espectro ultravioleta hasta el infrarrojo. Aunque esta tecnología fue aplicada inicialmente a la observación de la superficie terrestre, esta característica ha hecho que, en los últimos años, la aplicación de estas imágenes se haya expandido a otros campos, como la medicina y, en concreto, la detección del cáncer. Sin embargo, este nuevo ámbito de aplicación ha generado nuevas necesidades, como la del procesado de las imágenes en tiempo real. Debido, precisamente, a la gran resolución espectral, estas imágenes requieren una elevada capacidad computacional para ser procesadas, lo que imposibilita la consecución de este objetivo con las técnicas tradicionales de procesado. En este sentido, una de las principales líneas de investigación persigue el objetivo del tiempo real mediante la paralelización del procesamiento, dividiendo esta carga computacional en varios núcleos que trabajen simultáneamente. A este respecto, en el presente documento se describe el desarrollo de una librería de procesado hiperespectral para el lenguaje RVC - CAL, que está específicamente pensado para el desarrollo de aplicaciones multimedia y proporciona las herramientas necesarias para paralelizar las aplicaciones. En concreto, en este Proyecto Fin de Grado se han desarrollado las funciones necesarias para implementar dos de las cuatro fases de la cadena de análisis de una imagen hiperespectral - en concreto, las fases de estimación del número de endmembers y de la estimación de la distribución de los mismos en la imagen -; conviene destacar que este trabajo se complementa con el realizado por Daniel Madroñal en su Proyecto Fin de Grado, donde desarrolla las funciones necesarias para completar las otras dos fases de la cadena. El presente documento sigue la estructura clásica de un trabajo de investigación, exponiendo, en primer lugar, las motivaciones que han cimentado este Proyecto Fin de Grado y los objetivos que se esperan alcanzar con él. A continuación, se realiza un amplio análisis del estado del arte de las tecnologías necesarias para su desarrollo, explicando, por un lado, las imágenes hiperespectrales y, por otro, todos los recursos hardware y software necesarios para la implementación de la librería. De esta forma, se proporcionarán todos los conceptos técnicos necesarios para el correcto seguimiento de este documento. Tras ello, se detallará la metodología seguida para la generación de la mencionada librería, así como el proceso de implementación de una cadena completa de procesado de imágenes hiperespectrales que permita la evaluación tanto de la bondad de la librería como del tiempo necesario para analizar una imagen hiperespectral completa. Una vez expuesta la metodología utilizada, se analizarán en detalle los resultados obtenidos en las pruebas realizadas; en primer lugar, se explicarán los resultados individuales extraídos del análisis de las dos etapas implementadas y, posteriormente, se discutirán los arrojados por el análisis de la ejecución de la cadena completa, tanto en uno como en varios núcleos. Por último, como resultado de este estudio se extraen una serie de conclusiones, que engloban aspectos como bondad de resultados, tiempos de ejecución y consumo de recursos; asimismo, se proponen una serie de líneas futuras de actuación con las que se podría continuar y complementar la investigación desarrollada en este documento. ABSTRACT. Hyperspectral imaging collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. Although this technology was initially developed for remote sensing and earth observation, its multiple advantages - such as high spectral resolution - led to its application in other fields, as cancer detection. However, this new field has shown specific requirements; for example, it needs to accomplish strong time specifications, since all the potential applications - like surgical guidance or in vivo tumor detection - imply real-time requisites. Achieving this time requirements is a great challenge, as hyperspectral images generate extremely high volumes of data to process. For that reason, some new research lines are studying new processing techniques, and the most relevant ones are related to system parallelization: in order to reduce the computational load, this solution executes image analysis in several processors simultaneously; in that way, this computational load is divided among the different cores, and real-time specifications can be accomplished. This document describes the construction of a new hyperspectral processing library for RVC - CAL language, which is specifically designed for multimedia applications and allows multithreading compilation and system parallelization. This Diploma Project develops the required library functions to implement two of the four stages of the hyperspectral imaging processing chain - endmember and abundance estimations -. The two other stages - dimensionality reduction and endmember extraction - are studied in the Diploma Project of Daniel Madroñal, which complements the research work described in this document. The document follows the classical structure of a research work. Firstly, it introduces the motivations that have inspired this Diploma Project and the main objectives to achieve. After that, it thoroughly studies the state of the art of the technologies related to the development of the library. The state of the art contains all the concepts needed to understand the contents of this research work, like the definition and applications of hyperspectral imaging and the typical processing chain. Thirdly, it explains the methodology of the library implementation, as well as the construction of a complete processing chain in RVC - CAL applying the mentioned library. This chain will test both the correct behavior of the library and the time requirements for the complete analysis of one hyperspectral image, either executing the chain in one processor or in several ones. Afterwards, the collected results will be carefully analyzed: first of all, individual results -from endmember and abundance estimations stages - will be discussed and, after that, complete results will be studied; this results will be obtained from the complete processing chain, so they will analyze the effects of multithreading and system parallelization on the mentioned processing chain. Finally, as a result of this discussion, some conclusions will be gathered regarding some relevant aspects, such as algorithm behavior, execution times and processing performance. Likewise, this document will conclude with the proposal of some future research lines that could continue the research work described in this document.

Procesado de imágenes médicas en MATLAB

La relación entre la ingeniería y la medicina cada vez se está haciendo más estrecha, y debido a esto se ha creado una nueva disciplina, la bioingeniería, ámbito en el que se centra el proyecto. Este ámbito cobra gran interés debido al rápido desarrollo de nuevas tecnologías que en particular permiten, facilitan y mejoran la obtención de diagnósticos médicos respecto de los métodos tradicionales. Dentro de la bioingeniería, el campo que está teniendo mayor desarrollo es el de la imagen médica, gracias al cual se pueden obtener imágenes del interior del cuerpo humano con métodos no invasivos y sin necesidad de recurrir a la cirugía. Mediante métodos como la resonancia magnética, rayos X, medicina nuclear o ultrasonidos, se pueden obtener imágenes del cuerpo humano para realizar diagnósticos. Para que esas imágenes puedan ser utilizadas con ese fin hay que realizar un correcto tratamiento de éstas mediante técnicas de procesado digital. En ése ámbito del procesado digital de las imágenes médicas es en el que se ha realizado este proyecto. Gracias al desarrollo del tratamiento digital de imágenes con métodos de extracción de información, mejora de la visualización o resaltado de rasgos de interés de las imágenes, se puede facilitar y mejorar el diagnóstico de los especialistas. Por todo esto en una época en la que se quieren automatizar todos los procesos para mejorar la eficacia del trabajo realizado, el automatizar el procesado de las imágenes para extraer información con mayor facilidad, es muy útil. Actualmente una de las herramientas más potentes en el tratamiento de imágenes médicas es Matlab, gracias a su toolbox de procesado de imágenes. Por ello se eligió este software para el desarrollo de la parte práctica de este proyecto, su potencia y versatilidad simplifican la implementación de algoritmos. Este proyecto se estructura en dos partes. En la primera se realiza una descripción general de las diferentes modalidades de obtención de imágenes médicas y se explican los diferentes usos de cada método, dependiendo del campo de aplicación. Posteriormente se hace una descripción de las técnicas más importantes de procesado de imagen digital que han sido utilizadas en el proyecto. En la segunda parte se desarrollan cuatro aplicaciones en Matlab para ejemplificar el desarrollo de algoritmos de procesado de imágenes médicas. Dichas implementaciones demuestran la aplicación y utilidad de los conceptos explicados anteriormente en la parte teórica, como la segmentación y operaciones de filtrado espacial de la imagen, así como otros conceptos específicos. Las aplicaciones ejemplo desarrolladas han sido: obtención del porcentaje de metástasis de un tejido, diagnóstico de las deformidades de la columna vertebral, obtención de la MTF de una cámara de rayos gamma y medida del área de un fibroadenoma de una ecografía de mama. Por último, para cada una de las aplicaciones se detallará su utilidad en el campo de la imagen médica, los resultados obtenidos y su implementación en una interfaz gráfica para facilitar su uso. ABSTRACT. The relationship between medicine and engineering is becoming closer than ever giving birth to a recently appeared science field: bioengineering. This project is focused on this subject. This recent field is becoming more and more important due to the fast development of new technologies that provide tools to improve disease diagnosis, with regard to traditional procedures. In bioengineering the fastest growing field is medical imaging, in which we can obtain images of the inside of the human body without need of surgery. Nowadays by means of the medical modalities of magnetic resonance, X ray, nuclear medicine or ultrasound, we can obtain images to make a more accurate diagnosis. For those images to be useful within the medical field, they should be processed properly with some digital image processing techniques. It is in this field of digital medical image processing where this project is developed. Thanks to the development of digital image processing providing methods for data collection, improved visualization or data highlighting, diagnosis can be eased and facilitated. In an age where automation of processes is much sought, automated digital image processing to ease data collection is extremely useful. One of the most powerful image processing tools is Matlab, together with its image processing toolbox. That is the reason why that software was chosen to develop the practical algorithms in this project. This final project is divided into two main parts. Firstly, the different modalities for obtaining medical images will be described. The different usages of each method according to the application will also be specified. Afterwards we will give a brief description of the most important image processing tools that have been used in the project. Secondly, four algorithms in Matlab are implemented, to provide practical examples of medical image processing algorithms. This implementation shows the usefulness of the concepts previously explained in the first part, such as: segmentation or spatial filtering. The particular applications examples that have been developed are: calculation of the metastasis percentage of a tissue, diagnosis of spinal deformity, approximation to the MTF of a gamma camera, and measurement of the area of a fibroadenoma in an ultrasound image. Finally, for each of the applications developed, we will detail its usefulness within the medical field, the results obtained, and its implementation in a graphical user interface to ensure ease of use.

A new approach for the glotis segmentation using Snakes

The present work describes a new methodology for the automatic detection of the glottal space from laryngeal images based on active contour models (snakes). In order to obtain an appropriate image for the use of snakes based techniques, the proposed algorithm combines a pre-processing stage including some traditional techniques (thresholding and median filter) with more sophisticated ones such as anisotropic filtering. The value selected for the thresholding was fixed to the 85% of the maximum peak of the image histogram, and the anisotropic filter permits to distinguish two intensity levels, one corresponding to the background and the other one to the foreground (glottis). The initialization carried out is based on the magnitude obtained using the Gradient Vector Flow field, ensuring an automatic process for the selection of the initial contour. The performance of the algorithm is tested using the Pratt coefficient and compared against a manual segmentation. The results obtained suggest that this method provided results comparable with other techniques such as the proposed in (Osma-Ruiz et al., 2008).