Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.

Probing the interaction between two single molecules: fluorescence resonance energy transfer between a single donor and a single acceptor.

We extend the sensitivity of fluorescence resonance energy transfer (FRET) to the single molecule level by measuring energy transfer between a single donor fluorophore and a single acceptor fluorophore. Near-field scanning optical microscopy (NSOM) is used to obtain simultaneous dual color images and emission spectra from donor and acceptor fluorophores linked by a short DNA molecule. Photodestruction dynamics of the donor or acceptor are used to determine the presence and efficiency of energy transfer. The classical equations used to measure energy transfer on ensembles of fluorophores are modified for single-molecule measurements. In contrast to ensemble measurements, dynamic events on a molecular scale are observable in single pair FRET measurements because they are not canceled out by random averaging. Monitoring conformational changes, such as rotations and distance changes on a nanometer scale, within single biological macromolecules, may be possible with single pair FRET.

An exercises editor for an e-learning environment

One of the most important tenets of e-learning is that it bridges work and learning. A great e-learning experience brings learning into the work environment. This is a key point, the capacity to construct a work environment when the student can develop proper tasks to complete the learning process. This paper describes a work environment based on the development of two tools, an exercises editor and an exercises viewer. Both tools are able to manage color images where, because of the implementation of basic steganographic techniques, it is possible to add information, exercises, questions, and so on. The exercises editor allows to decide which information must be visible or remain hidden to the user, when the image is loaded in the exercises viewer. Therefore, it is possible to hide the solutions of the proposed tasks; this is very useful to complete a self-evaluation learning process. These tools constitute a learning architecture with the final objective that learners can apply and practice new concepts or skills.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

New galactic star clusters discovered in the VVV survey. Candidates projected on the inner disk and bulge

Context. VISTA Variables in the Vía Láctea (VVV) is one of six ESO Public Surveys using the 4 meter Visible and Infrared Survey Telescope for Astronomy (VISTA). The VVV survey covers the Milky Way bulge and an adjacent section of the disk, and one of the principal objectives is to search for new star clusters within previously unreachable obscured parts of the Galaxy. Aims. The primary motivation behind this work is to discover and analyze obscured star clusters in the direction of the inner Galactic disk and bulge. Methods. Regions of the inner disk and bulge covered by the VVV survey were visually inspected using composite JHKS color images to select new cluster candidates on the basis of apparent overdensities. DR1, DR2, CASU, and point spread function photometry of 10 × 10 arcmin fields centered on each candidate cluster were used to construct color–magnitude and color–color diagrams. Follow-up spectroscopy of the brightest members of several cluster candidates was obtained in order to clarify their nature. Results. We report the discovery of 58 new infrared cluster candidates. Fundamental parameters such as age, distance, and metallicity were determined for 20 of the most populous clusters.

Self-contained encrypted image folding

The recently introduced approach for Encrypted Image Folding is generalized to make it self-contained. The goal is achieved by enlarging the folded image so as to embed all the necessary information for the image recovery. The need for extra size is somewhat compensated by considering a transformation with higher folding capacity. Numerical examples show that the size of the resulting cipher image may be significantly smaller than the plain text one. The implementation of the approach is further extended to deal also with color images.

Determinação de cenários futuros de uso e cobertura do solo e sua influência na vulnerabilidade ambiental : o caso do município de Formosa – GO

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, 2015.

Análise da paisagem e das alterações de uso/ocupação do solo no Lubango e arredores

A cartografia temática surge como um aliado indispensável ao estudo e conhecimento do estado da paisagem e dos ecossistemas terrestres. Angola é um país com uma enorme lacuna em termos de informação cartográfica para suporte a diversas actividades desenvolvidas em várias áreas. É por isso necessária informação sobre a superfície terrestre que registe as alterações temporais ocorridas nos ecossistemas e identifique os factores que estão na sua origem de forma a implementar medidas que permitam uma gestão mais sustentável do seu enorme território. O presente estudo foi realizado no sector Sudoeste de Angola, abrangendo os municípios do Lubango, Humpata e Chibia, com uma área aproximada de 9600 km2. Os objectivos foram: a) cartografar o coberto do solo e monitorizar as alterações ocorridas na área de estudo no período 1990-2010, b) analisar e interpretar as alterações da estrutura da paisagem nos últimos 20 anos usando cartografia de ocupação do solo, produzida recorrendo a imagens de satélite, e métricas da paisagem, e c) quantificar e examinar a relação entre a fragmentação da paisagem e os factores geradores. A metodologia utilizada no estudo é composta por duas partes, sendo a primeira dedicada às operações de processamento e interpretação de imagens de satélite Landsat e, a segunda dedicada à produção de novas métricas de fragmentação da paisagem com recurso à ferramenta SIG utilizando operações de álgebra de mapas. O comportamento da fragmentação é analisado, à luz do efeito dos fatores ambientais e socioeconómicas ao nível da região. Os resultados obtidos, através da aplicação de técnicas de deteção remota e usando imagens Landsat TM e ETM+, permitiram a elaboração de mapas de coberto do solo, onde se distinguiram 8 classes temáticas e espectralmente diferentes. Verificou-se em termos globais que aproximadamente 38% da área sofreu algum tipo de alteração no período estudado, sendo as classes de miombo e áreas cultivadas as que mais alterações sofreram. A fragmentação da paisagem foi avaliada através da implementação de novas métricas, mostrando os resultados, que no período 1990-2000, a fragmentação foi superior à que se verificou entre 2000-2010. A nível espacial, a dinâmica de fragmentação foi mais acentuada, entre 1990-2000, na Humpata e, entre 2000-2010, no Lubango; ANALYSIS OF LANDSCAPE AND LAND USE LAND COVER CHANGE IN LUBANGO AND SURROUNDINGS ABSTRACT: Thematic cartography shows up as an essential ally in the study and knowledge of the state of landscapes and terrestrial ecosystems. Angola is a country with an enormous lack of cartographic information to support the several activities carried out in a variety of areas. This is the reason information on the earth’s surface is necessary, registering alterations which occur over time in ecosystems and identifying the associated factors in its origin, so as to implement metrics that allow a more sustainable management of its enormous territory. This study was carried out in the Southeast of Angola in the Lubango, Humpata and Chibia Municipalities, with an area of approximately 9600 km2. Our objectives were the following: a) land cover mapping and land cover changes monitoring over the period 1990 to 2010 using Landsat images, b) to analyze and interpret landscape structures changes using land cover maps, and landscapes metrics, and c) to quantify and to examine the relationship between landscape fragmentation and its drivers. The methodology developed in the study has two parts, the first includes Landsat satellite images processing and interpretation and, the second the production of new landscape fragmentation metrics with support to a GIS tool and algebraic mapping operations. The fragmentation behavior is analyzed, taking into account the effect of environmental and socioeconomic factors at a regional level. The results allowed obtaining land cover maps, in which 8 spectrally different thematic classes were distinguished. It was observed that 38% of the area suffered some type of alteration in the studied period, with higher changes observed in the classes of miombo and agriculture. Landscapes fragmentation results, evaluated through the implementation of new metrics, show that, values are greater in the period 1990-2000 than in 2000-2010. At municipality level, fragmentation dynamics were more accentuated in Humpata between 1990 -2000 and in Lubango between 2000 -2010.

Retrieving Cloud Characteristics from Ground-Based Daytime Color All-Sky Images

A discussion is presented of daytime sky imaging and techniques that may be applied to the analysis of full-color sky images to infer cloud macrophysical properties. Descriptions of two different types of skyimaging systems developed by the authors are presented, one of which has been developed into a commercially available instrument. Retrievals of fractional sky cover from automated processing methods are compared to human retrievals, both from direct observations and visual analyses of sky images. Although some uncertainty exists in fractional sky cover retrievals from sky images, this uncertainty is no greater than that attached to human observations for the commercially available sky-imager retrievals. Thus, the application of automatic digital image processing techniques on sky images is a useful method to complement, or even replace, traditional human observations of sky cover and, potentially, cloud type. Additionally, the possibilities for inferring other cloud parameters such as cloud brokenness and solar obstruction further enhance the usefulness of sky imagers

Diagnostic agreement between panoramic radiographs and color doppler images of carotid atheroma

The aim of this study was to investigate the agreement between diagnoses of calcified atheroma seen on panoramic radiographs and color Doppler images. Our interest stems from the fact that panoramic images can show the presence of atheroma regardless of the level of obstruction detected by color Doppler images. Panoramic and color Doppler images of 16 patients obtained from the archives of the Health Department of the city of Valença, RJ, Brazil, were analyzed in this study. Both sides of each patient were observed on the images, with a total of 32 analyzed cervical regions. The level of agreement between diagnoses was analyzed using the Kappa statistics. There was a high level of agreement, with a Kappa value of 0.78. In conclusion, panoramic radiographs can help detecting calcifications in the cervical region of patients susceptible to vascular diseases predisposing to myocardial infarction and cerebrovascular accidents. If properly trained and informed, dentists can refer their patients to a physician for a cardiovascular evaluation in order to receive proper and timely medical treatment.

Determination of Three-Dimensional Left Ventricle Motion to Analyze Ventricular Dyssyncrony in SPECT Images

A method to compute three-dimension (3D) left ventricle (LV) motion and its color coded visualization scheme for the qualitative analysis in SPECT images is proposed. It is used to investigate some aspects of Cardiac Resynchronization Therapy (CRT). The method was applied to 3D gated-SPECT images sets from normal subjects and patients with severe Idiopathic Heart Failure, before and after CRT. Color coded visualization maps representing the LV regional motion showed significant difference between patients and normal subjects. Moreover, they indicated a difference between the two groups. Numerical results of regional mean values representing the intensity and direction of movement in radial direction are presented. A difference of one order of magnitude in the intensity of the movement on patients in relation to the normal subjects was observed. Quantitative and qualitative parameters gave good indications of potential application of the technique to diagnosis and follow up of patients submitted to CRT.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Statistical segmentation methods and color variance analysis of retinal images

In this research, the effectiveness of Naive Bayes and Gaussian Mixture Models classifiers on segmenting exudates in retinal images is studied and the results are evaluated with metrics commonly used in medical imaging. Also, a color variation analysis of retinal images is carried out to find how effectively can retinal images be segmented using only the color information of the pixels.