Colour image processing

In the context of the round table the following topics related to image colour processing will be discussed: historical point of view. Studies of Aguilonius, Gerritsen, Newton and Maxwell. CIE standard (Commission International de lpsilaEclaraige). Colour models. RGB, HIS, etc. Colour segmentation based on HSI model. Industrial applications. Summary and discussion. At the end, video images showing the robustness of colour in front of B/W images will be presented

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

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

Building wood debris piles benefits avian seed dispersers in burned and logged Mediterranean pine forests

Salvage logging is a common practice carried out in burned forests worldwide, and intended to mitigate the economic losses caused by wildfires. Logging implies an additional disturbance occurring shortly after fire, although its ecological effects can be somewhat mitigated by leaving wood debris on site. The composition of the bird community and its capacity to provide ecosystem services such as seed dispersal of fleshy-fruited plants have been shown to be affected by postfire logging. We assessed the effects of the habitat structure resulting from different postfire management practices on the bird community, in three burned pine forests in Catalonia (western Mediterranean). For this purpose, we focused on the group of species that is responsible for seed dispersal, a process which takes place primarily during the winter in the Mediterranean basin. In addition, we assessed microhabitat selection by seed disperser birds in such environments in relation to management practices. Our results showed a significant, positive relationship between the density of wood debris piles and the abundance of seed disperser birds. Furthermore, such piles were the preferred microhabitat of these species. This reveals an important effect of forest management on seed disperser birds, which is likely to affect the dynamics of bird-dependent seed dispersal. Thus, building wood debris piles can be a useful practice for the conservation of both the species and their ecosystem services, while also being compatible with timber harvesting

Can salvage logging affect seed dispersal by birds into burned forests?

The recovery of vegetation in Mediterranean ecosystems after wildfire is mostly a result of direct regeneration, since the same species existing before the fire regenerate on-site by seeding or resprouting. However, the possibility of plant colonization by dispersal of seeds from unburned areas remains poorly studied. We addressed the role of the frugivorous, bird-dependent seed dispersal (seed rain) of fleshy-fruited plants in a burned and managed forest in the second winter after a fire, before on-site fruit production had begun. We also assessed the effect on seed rain of different microhabitats resulting from salvage logging (erosion barriers, standing snags, open areas), as well as the microhabitats of unlogged patches and an unburned control forest, taking account of the importance of perches as seed rain sites. We found considerable seed rain by birds in the burned area. Seeds, mostly from Olive trees Olea europaea and Evergreen pistaches Pistacia lentiscus, belonged to plants fruiting only in surrounding unburned areas. Seed rain was heterogeneous, and depended on microhabitat, with the highest seed density in the unburned control forest but closely followed by the wood piles of erosion barriers. In contrast, very low densities were found under perches of standing snags. Furthermore, frugivorous bird richness seemed to be higher in the erosion barriers than elsewhere. Our results highlight the importance of this specific post-fire management in bird-dependent seed rain and also may suggest a consequent heterogeneous distribution of fleshy-fruited plants in burned and managed areas. However, there needs to be more study of the establishment success of dispersed seeds before an accurate assessment can be made of the role of bird-mediated seed dispersal in post-fire regeneration

Visualitzation and processing of diffusion tensor MRI

Diffusion Tensor Imaging (DTI) is a new magnetic resonance imaging modality capable of producing quantitative maps of microscopic natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. This technique has become a powerful tool in the investigation of brain structure and function because it allows for in vivo measurements of white matter fiber orientation. The application of DTI in clinical practice requires specialized processing and visualization techniques to extract and represent acquired information in a comprehensible manner. Tracking techniques are used to infer patterns of continuity in the brain by following in a step-wise mode the path of a set of particles dropped into a vector field. In this way, white matter fiber maps can be obtained.

Signal processing of microstructure profiles: integrating turbulent spatial scales in aquatic ecological modeling

The main objective of this thesis was the integration of microstructure information in synoptic descriptors of turbulence, that reflects the mixing processes. Turbulent patches are intermittent in space and time, but they represent the dominant process for mixing. In this work, the properties of turbulent patches were considered the potential input for integrating the physical microscale measurements. The development of a method for integrating the properties of the turbulent patches required solving three main questions: a) how can we detect the turbulent patches from he microstructure measurements?; b) which are the most relevant properties of the turbulent patches?; and ) once an interval of time has been selected, what kind of synoptic parameters could better reflect the occurrence and properties of the turbulent patches? The answers to these questions were the final specific objectives of this thesis.

Advances in animal blood processing: development of a biopreservation system and insights on the functional properties of plasma

La sang és un subproducte amb un alt potencial de valorització que s'obté en quantitats importants en els escorxadors industrials. Actualment, la majoria de sistemes de recollida de la sang no segueixen unes mesures d'higiene estrictes, pel que esdevé un producte de baixa qualitat microbiològica. Conseqüentment, l'aprofitament de la sang és una sortida poc estimulant des del punt de vista econòmic, ja que acostuma a perdre les qualitats que permetrien l'obtenció de productes d'alt valor afegit. El capítol I del present treball s'inclou dins d'un projecte que proposa la inoculació de bacteris de l'àcid làctic (LAB) com un cultiu bioconservador de la sang, un sistema senzill i de baix cost que cerca l'estabilitat de la sang, tant microbiològica com fisicoquímica, durant el període del seu emmagatzematge. El capítol II s'emmarca dins d'un projecte que cerca la millora de l'aprofitament integral de la sang que, en el cas de la fracció plasmàtica, es centra en l'estudi de la funcionalitat dels seus principals constituents. Conèixer la contribució dels components majoritaris ha de permetre la millora de la funcionalitat dels ingredients alimentaris derivats. Els resultats presentats en aquesta tesi poden ajudar a la valorització de la sang porcina d'escorxadors industrials, mitjançant els coneixements adquirits pel que fa a la millora del seu sistema de recollida i del desenvolupament d'ingredients alimentaris amb interessants propietats funcionals.

Image segmentation integrating colour, texture and boundary information

La tesis se centra en la Visión por Computador y, más concretamente, en la segmentación de imágenes, la cual es una de las etapas básicas en el análisis de imágenes y consiste en la división de la imagen en un conjunto de regiones visualmente distintas y uniformes considerando su intensidad, color o textura. Se propone una estrategia basada en el uso complementario de la información de región y de frontera durante el proceso de segmentación, integración que permite paliar algunos de los problemas básicos de la segmentación tradicional. La información de frontera permite inicialmente identificar el número de regiones presentes en la imagen y colocar en el interior de cada una de ellas una semilla, con el objetivo de modelar estadísticamente las características de las regiones y definir de esta forma la información de región. Esta información, conjuntamente con la información de frontera, es utilizada en la definición de una función de energía que expresa las propiedades requeridas a la segmentación deseada: uniformidad en el interior de las regiones y contraste con las regiones vecinas en los límites. Un conjunto de regiones activas inician entonces su crecimiento, compitiendo por los píxeles de la imagen, con el objetivo de optimizar la función de energía o, en otras palabras, encontrar la segmentación que mejor se adecua a los requerimientos exprsados en dicha función. Finalmente, todo esta proceso ha sido considerado en una estructura piramidal, lo que nos permite refinar progresivamente el resultado de la segmentación y mejorar su coste computacional. La estrategia ha sido extendida al problema de segmentación de texturas, lo que implica algunas consideraciones básicas como el modelaje de las regiones a partir de un conjunto de características de textura y la extracción de la información de frontera cuando la textura es presente en la imagen. Finalmente, se ha llevado a cabo la extensión a la segmentación de imágenes teniendo en cuenta las propiedades de color y textura. En este sentido, el uso conjunto de técnicas no-paramétricas de estimación de la función de densidad para la descripción del color, y de características textuales basadas en la matriz de co-ocurrencia, ha sido propuesto para modelar adecuadamente y de forma completa las regiones de la imagen. La propuesta ha sido evaluada de forma objetiva y comparada con distintas técnicas de integración utilizando imágenes sintéticas. Además, se han incluido experimentos con imágenes reales con resultados muy positivos.