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With the rapid growth of the internet and digital media techniques over the last decade, multimedia data such as images, video and audio can easily be copied, altered and distributed over the internet without any loss in quality. Therefore, protection of ownership of multimedia data has become a very significant and challenging issue. Three novel image watermarking algorithms have been designed and implemented for copyright protection. The first proposed algorithm is based on embedding multiple watermarks in the blue channel of colour images to achieve more robustness against attacks. The second proposed algorithm aims to achieve better trade-offs between imperceptibility and robustness requirements of a digital watermarking system. It embeds a watermark in adaptive manner via classification of DCT blocks with three levels: smooth, edges and texture, implemented in the DCT domain by analyzing the values of AC coefficients. The third algorithm aims to achieve robustness against geometric attacks, which can desynchronize the location of the watermark and hence cause incorrect watermark detection. It uses geometrically invariant feature points and image normalization to overcome the problem of synchronization errors caused by geometric attacks. Experimental results show that the proposed algorithms are robust and outperform related techniques found in literature.

No / This volume presents state-of-the-art research from a wide area of subjects brought about by the digital convergence of computing, television, telecommunications and the World-Wide Web. It represents a unique snapshot of trends across a wide range of subjects including virtual environments; virtual reality; telepresence; human-computer interface design; interactivity; avatars; and the Internet. Both researchers and practitioners will find it an invaluable source of reference.

This thesis deals with the development and evaluation of blind discrete cosine transform-based watermarking algorithms for copyright protection of digital still images using handwritten signatures and mobile phone numbers. The new algorithms take into account the perceptual capacity of each low frequency coefficients inside the Discrete Cosine Transform (DCT) blocks before embedding the watermark information. They are suitable for grey-scale and colour images. Handwritten signatures are used instead of pseudo random numbers. The watermark is inserted in the green channel of the RGB colour images and the luminance channel of the YCrCb images. Mobile phone numbers are used as watermarks for images captured by mobile phone cameras. The information is embedded multiple-times and a shuffling scheme is applied to ensure that no spatial correlation exists between the original host image and the multiple watermark copies. Multiple embedding will increase the robustness of the watermark against attacks since each watermark will be individually reconstructed and verified before applying an averaging process. The averaging process has managed to reduce the amount of errors of the extracted information. The developed watermarking methods are shown to be robust against JPEG compression, removal attack, additive noise, cropping, scaling, small degrees of rotation, affine, contrast enhancements, low-pass, median filtering and Stirmark attacks. The algorithms have been examined using a library of approximately 40 colour images of size 512 512 with 24 bits per pixel and their grey-scale versions. Several evaluation techniques were used in the experiment with different watermarking strengths and different signature sizes. These include the peak signal to noise ratio, normalized correlation and structural similarity index measurements. The performance of the proposed algorithms has been compared to other algorithms and better invisibility qualities with stronger robustness have been achieved.

A análise radiográfica tem sido eficiente na identificação das principais alterações na morfologia interna de sementes e, juntamente com análise de imagens digitalizadas de plântulas, está sendo cada vez mais utilizada em programas de controle de qualidade de sementes devido à sua praticidade, objetividade e rapidez na obtenção dos resultados. Apesar dessas vantagens, ainda não existem pesquisas comprovando a eficiência dessas técnicas para análise de sementes de café. Assim, esta pesquisa teve como objetivos avaliar a morfologia interna de sementes de café (Coffea arabica L.) por meio da análise de imagens radiográficas e a sua relação com o desempenho germinativo e testar a eficiência da análise de imagens digitalizadas de plântulas pelo Seed Vigor Imaging System (SVIS®) na determinação do vigor, comparativamente com os testes convencionalmente utilizados. Foram utilizadas sementes dos cultivares Bourbon e Catucaí 20/15, cada cultivar representado por seis lotes. A pesquisa foi conduzida em dois experimentos. No experimento I foram avaliadas imagens radiográficas para identificação das principais alterações na morfologia interna das sementes e sua relação com o desempenho germinativo por meio do teste de emergência de plântulas. O experimento II foi realizado em duas épocas de avaliação e o vigor foi determinado por meio das avaliações de primeira contagem de germinação, envelhecimento acelerado, condutividade elétrica, velocidade de emissão de raiz primária e análise de imagens digitalizadas de plântulas com o SVIS®. Concluiu-se que a análise de imagens radiográficas é eficiente na identificação das principais alterações na morfologia interna das sementes, relacionadas com malformações, danos por deterioração de tecidos e danos ocasionados pela broca-do-café, permitindo relacionar a ocorrência destes com o desempenho germinativo dos lotes de sementes. A análise de imagens digitalizadas de plântulas aos vinte dias de idade pelo SVIS® é eficiente na avaliação do vigor de lotes de sementes de café. / Radiographic analysis has been efficient in identifying the main changes in the internal morphology of seeds and, together with the digital image analysis of seedlings has been increasingly used in seed quality control programs due to its practicality, objectivity and rapid results. Despite these advantages, there are still no studies demonstrating the efficiency of these techniques for coffee seed analysis. The objective of this research was to evaluate the internal morphology of coffee seeds (Coffea arabica L.) by radiographic image analysis and their relation with germination performance. Furthermore, this research aimed to evaluate the efficiency of the Seed Vigor Imaging System (SVIS®) in determining seed vigor from digital seedling images in comparison to conventionally vigor tests. Seeds of the cultivars Bourbon and Catucaí 20/15 were used being each one represented by six seed lots. The research was conducted in two experiments. In experiment I radiographic images were taken to identify the main changes in the internal morphology of the seeds and stablish a relationship with the germination performance by the seedling emergence test. The experiment II was carried out in two evaluation periods and seed vigor was determined by the germination first count, accelerated aging, electrical conductivity, primary root emission velocity and analysis of scanned seedlings images by SVIS®. It was concluded that radiographic analysis is efficient in identifying internal morphology alterations in the seeds related to malformations, damages by tissue deterioration and damages caused by coffee borer, allowing to relate the occurrence of these problems with germination performance. The digitized analysis of 20-day-old seedlings by SVIS® is efficient in evaluating the vigor of coffee seeds.

A análise radiográfica tem sido eficiente na identificação das principais alterações na morfologia interna de sementes e, juntamente com análise de imagens digitalizadas de plântulas, está sendo cada vez mais utilizada em programas de controle de qualidade de sementes devido à sua praticidade, objetividade e rapidez na obtenção dos resultados. Apesar dessas vantagens, ainda não existem pesquisas comprovando a eficiência dessas técnicas para análise de sementes de café. Assim, esta pesquisa teve como objetivos avaliar a morfologia interna de sementes de café (Coffea arabica L.) por meio da análise de imagens radiográficas e a sua relação com o desempenho germinativo e testar a eficiência da análise de imagens digitalizadas de plântulas pelo Seed Vigor Imaging System (SVIS®) na determinação do vigor, comparativamente com os testes convencionalmente utilizados. Foram utilizadas sementes dos cultivares Bourbon e Catucaí 20/15, cada cultivar representado por seis lotes. A pesquisa foi conduzida em dois experimentos. No experimento I foram avaliadas imagens radiográficas para identificação das principais alterações na morfologia interna das sementes e sua relação com o desempenho germinativo por meio do teste de emergência de plântulas. O experimento II foi realizado em duas épocas de avaliação e o vigor foi determinado por meio das avaliações de primeira contagem de germinação, envelhecimento acelerado, condutividade elétrica, velocidade de emissão de raiz primária e análise de imagens digitalizadas de plântulas com o SVIS®. Concluiu-se que a análise de imagens radiográficas é eficiente na identificação das principais alterações na morfologia interna das sementes, relacionadas com malformações, danos por deterioração de tecidos e danos ocasionados pela broca-do-café, permitindo relacionar a ocorrência destes com o desempenho germinativo dos lotes de sementes. A análise de imagens digitalizadas de plântulas aos vinte dias de idade pelo SVIS® é eficiente na avaliação do vigor de lotes de sementes de café. / Radiographic analysis has been efficient in identifying the main changes in the internal morphology of seeds and, together with the digital image analysis of seedlings has been increasingly used in seed quality control programs due to its practicality, objectivity and rapid results. Despite these advantages, there are still no studies demonstrating the efficiency of these techniques for coffee seed analysis. The objective of this research was to evaluate the internal morphology of coffee seeds (Coffea arabica L.) by radiographic image analysis and their relation with germination performance. Furthermore, this research aimed to evaluate the efficiency of the Seed Vigor Imaging System (SVIS®) in determining seed vigor from digital seedling images in comparison to conventionally vigor tests. Seeds of the cultivars Bourbon and Catucaí 20/15 were used being each one represented by six seed lots. The research was conducted in two experiments. In experiment I radiographic images were taken to identify the main changes in the internal morphology of the seeds and stablish a relationship with the germination performance by the seedling emergence test. The experiment II was carried out in two evaluation periods and seed vigor was determined by the germination first count, accelerated aging, electrical conductivity, primary root emission velocity and analysis of scanned seedlings images by SVIS®. It was concluded that radiographic analysis is efficient in identifying internal morphology alterations in the seeds related to malformations, damages by tissue deterioration and damages caused by coffee borer, allowing to relate the occurrence of these problems with germination performance. The digitized analysis of 20-day-old seedlings by SVIS® is efficient in evaluating the vigor of coffee seeds.

El uso de cámaras de video para obtener información de la zona costera se ha extendido en los últimos años, debido al alcance espacial y temporal y el bajo costo del equipo. Con esto se han desarrollado técnicas para realizar mediciones en las imágenes. Estas requieren supervisión, lo que limita el número de imágenes que pueden ser analizadas. En este trabajo se desarrolló una metodología para clasificar imágenes digitales según las características morfodinámicas observadas y reducir el conjunto de imágenes a unos prototipos representativos de todo el conjunto. Esta clasificación se realiza por medio de mapas auto-organizativos. Los mapas auto organizativos son redes neuronales competitivas no supervisadas diseñadas para trabajar en espacios multidimensionales. La metodología desarrollada se aplico en dos playas; la primera, macromareal, se estudio la evolución morfodinámica según el modelo de Wright y Short 1984. En la segunda, micromareal, se estudio, la evolución de la línea de costa. / The use of video cameras to study the coastal zone has been developed in the last years, due to the spatial and temporal possibilities. A large number of techniques to obtain measurements of images were developed too. Most of these techniques require the human supervision, this limit the number of images to be analyzed. In this Thesis, a methodology to classify digital images based on the morphodynamic and reduce the number of images to a few prototypes is proposed. The classification is done by means of Sel-Organizative Maps (SOMs). The SOMs are a competitive and unsupervised neural networks, specifically designed to deal with high dimensional data The methodology proposed was applied to two beaches. In the first one, macrotidal, the morphodynamic evolution was studied using the Wright and Short Model 1984. In the last one, a microtidal beach, the coastline evolution was studied.

Vast collections of historical photographs are being digitally archived and placed online, providing an objective record of the last two centuries that remains largely untapped. We propose that time-varying 3D models can pull together and index large collections of images while also serving as a tool of historical discovery, revealing new information about the locations, dates, and contents of historical images. In particular, our goal is to use computer vision techniques to tie together a large set of historical photographs of a given city into a consistent 4D model of the city: a 3D model with time as an additional dimension. To extract 4D city models from historical images, we must perform inference about the position of cameras and scene structure in both space and time. Traditional structure from motion techniques can be used to deal with the spatial problem, while here we focus on the problem of inferring temporal information: a date for each image and a time interval for which each structural element in the scene persists. We first formulate this task as a constraint satisfaction problem based on the visibility of structural elements in each image, resulting in a temporal ordering of images. Next, we present methods to incorporate real date information into the temporal inference solution. Finally, we present a general probabilistic framework for estimating all temporal variables in structure from motion problems, including an unknown date for each camera and an unknown time interval for each structural element. Given a collection of images with mostly unknown or uncertain dates, we can use this framework to automatically recover the dates of all images by reasoning probabilistically about the visibility and existence of objects in the scene. We present results for image collections consisting of hundreds of historical images of cities taken over decades of time, including Manhattan and downtown Atlanta.

Current Web image search engines, such as Google or Bing Images, adopt a hybrid search approach in which a text-based query (e.g. "apple") is used to retrieve a set of relevant images, which are then refined by the user (e.g. by re-ranking the retrieved images based on similarity to a selected example). This approach makes it possible to use both text information (e.g. the initial query) and image features (e.g. as part of the refinement stage) to identify images which are relevant to the user. One limitation of these current systems is that text and image features are treated as independent components and are often used in a decoupled manner. This work proposes to develop an integrated hybrid search method which leverages the synergies between text and image features. Recently, there has been tremendous progress in the computer vision community in learning models of visual concepts from collections of example images. While impressive performance has been achieved on standardized data sets, scaling these methods so that they are capable of working at web scale remains a significant challenge. This work will develop approaches to visual modeling that can be scaled to address the task of retrieving billions of images on the Web. Specifically, we propose to address two research issues related to integrated text- and image-based retrieval. First, we will explore whether models of visual concepts which are learned from collections of web images can be utilized to improve the image ranking associated with a text-based query. Second, we will investigate the hypothesis that the click-patterns associated with standard web image search engines can be utilized to learn query-specific image similarity measures that support improved query-refinement performance. We will evaluate our research by constructing a prototype integrated hybrid retrieval system based on the data from 300K real-world image queries. We will conduct user-studies to evaluate the effectiveness of our learned similarity measures and quantify the benefit of our method in real world search tasks such as target search.

Skaitmeniniai vaizdai yra plačiai naudojami kompiuterių taikomosiose programose. Nesuspaustų skaitmeninių vaizdų laikymui atmintyje reikia žymiai daugiau talpos ir spartesnio (didesnio pralaidumo) tinklo galimybių jų perdavimui tinklu. Efektyvūs vaizdų suspaudimo sprendimai tampa kritiškesni dėl pastaruoju metu didelio duomenų augimo intensyvumo, multimedijos pagrindu kuriamų tinklo programų. Šiame darbe pristatoma nauja lokaliai progresyvaus vaizdų kodavimo idėja (procedūra). Procedūra grindžiama specifinėmis Haaro bangelių savybėmis bei progresyvųjį vaizdų kodavimą realizuojančiu EZW algoritmu. Taip pat apžvelgiamos kitų diskrečiųjų transformacijų ypatybės, praktinis jų pritaikymas pramoninėje, mokslinėje srityse. Preliminarūs eksperimento rezultatai rodo, jog diskrečioji Haaro transformacija ir progresyvus vaizdų glaudinimo algoritmas EZW skaitmeninių vaizdų spaudimui nėra efektyvus. Efektyvumo didinimui pasirinktas tikslinis vaizdo spektro koeficientų modifikavimas, kas leido pasiekti kur kas geresnių kodavimo rezultatų. / Digital images are widely used in computer applications. Uncompressed digital images require considerable storage capacity and transmission bandwidth. Efficient image compression solutions are becoming more critical with the recent growth of data intensive, multimedia-based web applications. In this paper, a novel locally progressive image encoding idea (procedure) is presented. The procedure explores both specific properties of Haar wavelets and the EZW algorithm originally used for progressive image encoding. Properties of various discrete transforms and areas of their practical applicability are discussed too. Preliminary experimental results show that the joint application of the discrete Haar transform and the EZW algorithm to locally progressive compression of digital images is not effective. To increase efficiency of the approach (idea), some modifications are proposed. In particular, appropriately chosen enlargement of Haar spectral coefficients led to much better overall performance, unfortunately, at the expense of time expenditures.