934 resultados para Binary Image Representation


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Este proyecto, titulado “Caracterización de colectores para concentración fotovoltaica”, consiste en una aplicación en Labview para obtener las características de los elementos ópticos utilizados en sistemas de concentración fotovoltaica , atendiendo a la distribución espacial del foco de luz concentrado que generan. Un sistema de concentración fotovoltaica utiliza un sistema óptico para transmitir la radiación luminosa a la célula solar aumentando la densidad de potencia luminosa. Estos sistemas ópticos están formados por espejos o lentes para recoger la radiación incidente en ellos y concentrar el haz de luz en una superficie mucho menor. De esta manera se puede reducir el área de material semiconductor necesario, lo que conlleva una importante reducción del coste del sistema. Se pueden distinguir diferentes sistemas de concentración dependiendo de la óptica que emplee, la estructura del receptor o el rango de concentración. Sin embargo, ya que el objetivo es analizar la distribución espacial, diferenciaremos dos tipos de concentradores dependiendo de la geometría que presenta el foco de luz. El concentrador lineal o cilíndrico que enfoca sobre una línea, y el concentrador de foco puntual o circular que enfoca la luz sobre un punto. Debido a esta diferencia el análisis en ambos casos se realizará de forma distinta. El análisis se realiza procesando una imagen del foco tomada en el lugar del receptor, este método se llama LS-CCD (Difusión de luz y captura con CCD). Puede utilizarse en varios montajes dependiendo si se capta la imagen por reflexión o por transmisión en el receptor. En algunos montajes no es posible captar la imagen perpendicular al receptor por lo que la aplicación realizará un ajuste de perspectiva para obtener el foco con su forma original. La imagen del foco ofrece información detallada acerca de la uniformidad del foco mediante el mapa de superficie, que es una representación en 3D de la imagen pero que resulta poco manejable. Una representación más sencilla y útil es la que ofrecen los llamados “perfiles de intensidad”. El perfil de intensidad o distribución de la irradiancia que representa la distribución de la luz para cada distancia al centro, y el perfil acumulado o irradiancia acumulada que representa la luz contenida en relación también al centro. Las representaciones de estos perfiles en el caso de un concentrador lineal y otro circular son distintas debido a su diferente geometría. Mientras que para un foco lineal se expresa el perfil en función de la semi-anchura del receptor, para uno circular se expresa en función del radio. En cualquiera de los casos ofrecen información sobre la uniformidad y el tamaño del foco de luz necesarios para diseñar el receptor. El objetivo de este proyecto es la creación de una aplicación software que realice el procesado y análisis de las imágenes obtenidas del foco de luz de los sistemas ópticos a caracterizar. La aplicación tiene una interfaz sencilla e intuitiva para que pueda ser empleada por cualquier usuario. Los recursos necesarios para realizar el proyecto son: un PC con sistema operativo Windows, el software Labview 8.6 Professional Edition y los módulos NI Vision Development Module (para trabajar con imágenes) y NI Report Generation Toolkit (para realizar reportes y guardar datos de la aplicación). ABSTRACT This project, called “Characterization of collectors for concentration photovoltaic systems”, consists in a Labview application to obtain the characteristics of the optical elements used in photovoltaic concentrator, taking into account the spatial distribution of concentrated light source generated. A concentrator photovoltaic system uses an optical system to transmit light radiation to the solar cell by increasing the light power density. This optical system are formed by mirrors or lenses to collect the radiation incident on them and focus the beam of light in a much smaller surface area. In this way you can reduce the area of semiconductor material needed, which implies a significant reduction in system cost. There are different concentration systems depending on the optics used, receptor structure or concentration range. However, as the aim is to analyze the spatial distribution, distinguish between two types of concentrators depending on the geometry that has the light focus. The linear or cylindrical concentrator that focused on a line, and the circular concentrator that focused light onto a point. Because this difference in both cases the analysis will be carried out differently. The analysis is performed by processing a focus image taken at the receiver site, this method is called “LS-CCD” (Light Scattering and CCD recording). Can be used in several mountings depending on whether the image is captured by reflection or transmission on the receiver. In some mountings it is not possible to capture the image perpendicular to the receivers so that the application makes an adjustment of perspective to get the focus to its original shape. The focus image provides detail information about the uniformity of focus through the surface map, which is a 3D image representation but it is unwieldy. A simple and useful representation is provided by so called “intensity profiles”. The intensity profile or irradiance distribution which represents the distribution of light to each distance to the center. The accumulated profile or accumulated irradiance that represents the cumulative light contained in relation also to the center. The representation of these profiles in the case of a linear and a circular concentrator are different due to their distinct geometry. While for a line focus profile is expressed in terms of semi-width of the receiver, for a circular concentrator is expressed in terms of radius. In either case provides information about the uniformity and size of focus needed to design the receiver. The objective of this project is the creation of a software application to perform processing and analysis of images obtained from light source of optical systems to characterize.The application has a simple and a intuitive interface so it can be used for any users. The resources required for the project are: a PC with Windows operating system, LabVIEW 8.6 Professional Edition and the modules NI Vision Development Module (for working with images) and NI Report Generation Toolkit (for reports and store application data .)

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We present a framework for the analysis of the decoding delay in multiview video coding (MVC). We show that in real-time applications, an accurate estimation of the decoding delay is essential to achieve a minimum communication latency. As opposed to single-view codecs, the complexity of the multiview prediction structure and the parallel decoding of several views requires a systematic analysis of this decoding delay, which we solve using graph theory and a model of the decoder hardware architecture. Our framework assumes a decoder implementation in general purpose multi-core processors with multi-threading capabilities. For this hardware model, we show that frame processing times depend on the computational load of the decoder and we provide an iterative algorithm to compute jointly frame processing times and decoding delay. Finally, we show that decoding delay analysis can be applied to design decoders with the objective of minimizing the communication latency of the MVC system.

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Low cost RGB-D cameras such as the Microsoft’s Kinect or the Asus’s Xtion Pro are completely changing the computer vision world, as they are being successfully used in several applications and research areas. Depth data are particularly attractive and suitable for applications based on moving objects detection through foreground/background segmentation approaches; the RGB-D applications proposed in literature employ, in general, state of the art foreground/background segmentation techniques based on the depth information without taking into account the color information. The novel approach that we propose is based on a combination of classifiers that allows improving background subtraction accuracy with respect to state of the art algorithms by jointly considering color and depth data. In particular, the combination of classifiers is based on a weighted average that allows to adaptively modifying the support of each classifier in the ensemble by considering foreground detections in the previous frames and the depth and color edges. In this way, it is possible to reduce false detections due to critical issues that can not be tackled by the individual classifiers such as: shadows and illumination changes, color and depth camouflage, moved background objects and noisy depth measurements. Moreover, we propose, for the best of the author’s knowledge, the first publicly available RGB-D benchmark dataset with hand-labeled ground truth of several challenging scenarios to test background/foreground segmentation algorithms.

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There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

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In this paper, we present a new scheme for off-line recognition of multi-font numerals using the Takagi-Sugeno (TS) model. In this scheme, the binary image of a character is partitioned into a fixed number of sub-images called boxes. The features consist of normalized vector distances (gamma) from each box. Each feature extracted from different fonts gives rise to a fuzzy set. However, when we have a small number of fonts as in the case of multi-font numerals, the choice of a proper fuzzification function is crucial. Hence, we have devised a new fuzzification function involving parameters, which take account of the variations in the fuzzy sets. The new fuzzification function is employed in the TS model for the recognition of multi-font numerals.

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The local image representation produced by early stages of visual analysis is uninformative regarding spatially extensive textures and surfaces. We know little about the cortical algorithm used to combine local information over space, and still less about the area over which it can operate. But such operations are vital to support perception of real-world objects and scenes. Here, we deploy a novel reverse-correlation technique to measure the extent of spatial pooling for target regions of different areas placed either in the central visual field, or more peripherally. Stimuli were large arrays of micropatterns, with their contrasts perturbed individually on an interval-by-interval basis. By comparing trial-by-trial observer responses with the predictions of computational models, we show that substantial regions (up to 13 carrier cycles) of a stimulus can be monitored in parallel by summing contrast over area. This summing strategy is very different from the more widely assumed signal selection strategy (a MAX operation), and suggests that neural mechanisms representing extensive visual textures can be recruited by attention. We also demonstrate that template resolution is much less precise in the parafovea than in the fovea, consistent with recent accounts of crowding. © 2014 The Authors.

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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

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The applicability of a formalism involving an exponential function of composition x1 in interpreting the thermodynamic properties of alloys has been studied. The excess integral and partial molar free energies of mixing are expressed as: $$\begin{gathered} \Delta F^{xs} = a_o x_1 (1 - x_1 )e^{bx_1 } \hfill \\ RTln\gamma _1 = a_o (1 - x_1 )^2 (1 + bx_1 )e^{bx_1 } \hfill \\ RTln\gamma _2 = a_o x_1^2 (1 - b + bx_1 )e^{bx_1 } \hfill \\ \end{gathered} $$ The equations are used in interpreting experimental data for several relatively weakly interacting binary systems. For the purpose of comparison, activity coefficients obtained by the subregular model and Krupkowski’s formalism have also been computed. The present equations may be considered to be convenient in describing the thermodynamic behavior of metallic solutions.

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Tourism is one of important livelihoods in Lapland. Christmas tourism was launched in the early 1980s and it became a success story - being labelled as the most epochal tourism product in Finland. Hence, today Christmas tourists are one of the most significant foreign groups arriving to Lapland during the winter season and contributing considerably to the economics of the northeastern periphery of the EU. Christmas tourism concentrates around Father Christmas who uses reindeer for transportation. The Sämi are the only indigenous people in the EU. They are all stereotypically perceived to be reindeer herders. Somehow these three, that is, Santa Claus, reindeer and the Sämi, have been incorporated into same fairytale dominion. In practice, this has happened by using the most visible cultural but also significant identity marker of the Sämi, the Sämi costume. This, in turn, has created controversy over authenticity due to manners in which the costume is used in tourism - often in imitational, mismatched forms by non-Sämi. In this thesis, after relevant literature review I intend to establish how the Sâmi are represented in Christmas tourism through visual data consisting of ten images from three foreign sources. Then I clarify why and to whom it matters of how the Sâmi are represented in Christmas tourism with the aid of 65 questionnaires and nineteen expert interviews collected mainly in the Finnish Sâmi Home Region in October 2009. Through the multiplicity of the voices of various interest and ethnic groups and by using critical discourse analysis I attempt to give an overview of the respondents' opinions and look at some preliminary solutions to the controversy. Based on my data, the non-Sami appear to accept the Sami costume usage in Christmas tourism most readily. Consequently, respect and attitudinal changes have become the respondents' propositions in addition to common set of rules of how the Sami image could be appropriated without violating the integrity of the Sami people, or a similar system of S¿m¡ Duodji trademark guaranteeing the authenticity of the tourism products. Additionally, though half of the interviewees explicate Sami presence in Christmas tourism by adding local flavour to otherwise commercial enterprise, the other half see no rationale to connect facts with fiction, that is, the Sami with Santa Claus.

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Tourism is one of important livelihoods in Lapland. Christmas tourism was launched in the early 1980s and it became a success story - being labelled as the most epochal tourism product in Finland. Hence, today Christmas tourists are one of the most significant foreign groups arriving to Lapland during the winter season and contributing considerably to the economics of the northeastern periphery of the EU. Christmas tourism concentrates around Father Christmas who uses reindeer for transportation. The Sämi are the only indigenous people in the EU. They are all stereotypically perceived to be reindeer herders. Somehow these three, that is, Santa Claus, reindeer and the Sämi, have been incorporated into same fairytale dominion. In practice, this has happened by using the most visible cultural but also significant identity marker of the Sämi, the Sämi costume. This, in turn, has created controversy over authenticity due to manners in which the costume is used in tourism - often in imitational, mismatched forms by non-Sämi. In this thesis, after relevant literature review I intend to establish how the Sâmi are represented in Christmas tourism through visual data consisting of ten images from three foreign sources. Then I clarify why and to whom it matters of how the Sâmi are represented in Christmas tourism with the aid of 65 questionnaires and nineteen expert interviews collected mainly in the Finnish Sâmi Home Region in October 2009. Through the multiplicity of the voices of various interest and ethnic groups and by using critical discourse analysis I attempt to give an overview of the respondents' opinions and look at some preliminary solutions to the controversy. Based on my data, the non-Sami appear to accept the Sami costume usage in Christmas tourism most readily. Consequently, respect and attitudinal changes have become the respondents' propositions in addition to common set of rules of how the Sami image could be appropriated without violating the integrity of the Sami people, or a similar system of S¿m¡ Duodji trademark guaranteeing the authenticity of the tourism products. Additionally, though half of the interviewees explicate Sami presence in Christmas tourism by adding local flavour to otherwise commercial enterprise, the other half see no rationale to connect facts with fiction, that is, the Sami with Santa Claus.

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In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

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We demonstrate that a pattern spectrum can be decomposed into the union of hit-or-miss transforms with respect to a series of structure-element pairs. Moreover we use a Boolean-logic function to express the pattern spectrum and show that the Boolean-logic representation of a pattern spectrum is composed of hit-or-miss min terms. The optical implementation of a pattern spectrum is based on an incoherent optical correlator with a feedback operation. (C) 1996 Optical Society of America

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This thesis explores how to represent image texture in order to obtain information about the geometry and structure of surfaces, with particular emphasis on locating surface discontinuities. Theoretical and psychophysical results lead to the following conclusions for the representation of image texture: (1) A texture edge primitive is needed to identify texture change contours, which are formed by an abrupt change in the 2-D organization of similar items in an image. The texture edge can be used for locating discontinuities in surface structure and surface geometry and for establishing motion correspondence. (2) Abrupt changes in attributes that vary with changing surface geometry ??ientation, density, length, and width ??ould be used to identify discontinuities in surface geometry and surface structure. (3) Texture tokens are needed to separate the effects of different physical processes operating on a surface. They represent the local structure of the image texture. Their spatial variation can be used in the detection of texture discontinuities and texture gradients, and their temporal variation may be used for establishing motion correspondence. What precisely constitutes the texture tokens is unknown; it appears, however, that the intensity changes alone will not suffice, but local groupings of them may. (4) The above primitives need to be assigned rapidly over a large range in an image.