Morphological routine proposal to extraction of highways in digital images of high resolution

This research proposes to apply techniques of Mathematics Morphology to extract highways in digital images of high resolution, targeting the upgrade of cartographic products. Remote Sensing data and Mathematical Morphological techniques were integrated in the process of extraction. Mathematical Morphology's objective is to improve and extract the relevant information of the visual image. In order to test the proposed approach some morphological operators related to preprocess, were applied to the original images. Routines were implemented in the MATLAB environment. Results indicated good performances by the implemented operators. The integration of the technologies aimed to implement the semiautomatic extraction of highways with the purpose to use them in processes of cartographic updating.

Detecção e restauração de áreas sombreadas em imagens digitais de alta resolução espacial

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Use of comet assay to assess DNA damage in patients infected by Helicobacter pylori - Comparisons between visual and image analyses

Studies of DNA damage in gastric epithelial cells of Helicobacter pylori (H. pylori)-infected patients are conflicting, possibly due to different methods used for scoring DNA damage by Comet assay. Therefore, we compared the sensitivity of visual microscopic analysis (arbitrary units-scores and comets%) and image analysis system (tail moment), in the gastric epithelial cells from the antrum and corpus of 122 H. pylori-infected and 32 non-infected patients. The feasibility of cryopreserved peripheral blood lymphocytes and whole-blood cells for DNA damage biomonitoring was also investigated. In the antrum, the levels of DNA damage were significantly higher in H. pylori-infected patients with gastritis than in non-infected patients with normal mucosa, when evaluated by image analysis system, arbitrary units and comets%. In the corpus, the comets% was not sufficiently sensitive to detect the difference between H. pylori-infected patients with gastritis and non-infected patients with normal mucosa. The image analysis system was sensitive enough to detect differences between non-infected patients and H. pylori-infected patients with mild gastritis and between infected patients with moderate and severe gastritis, in both antrum, and corpus, while arbitrary units and comets% were unable to detect these differences. In cryopreserved peripheral blood lymphocytes, the levels of DNA damage (tail moment) were significantly higher in H. pylori-infected patients with moderate and severe gastritis than in non-infected patients. Overall, our results indicate that the image analysis system is more sensitive and adequate to measure the levels of DNA damage in gastric epithelial cells than the other methods assayed. (c) 2005 Elsevier B.V. All rights reserved.

Image categorization through optimum path forest and visual words

Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.

Quantitative characterization of multi-phase materials by digital image processing

An automatic image processing and analysis technique has been developed for quantitative characterization of multi-phase materials. For the development of this technique is used the Khoros system that offers the basic morphological tools and a flexible, visual programming language. These techniques are implemented in a highly user oriented image processing environment that allows the user to adapt each step of the processing to his special requirements.To illustrate the implementation and performance of this technique, images of two different materials are processed for microstructure characterization. The result is presented through the determination of volume fraction of the different phases or precipitates.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

Implementation of filters for image pre-processing for leaf analyses in plantations

In this work an image pre-processing module has been developed to extract quantitative information from plantation images with various degrees of infestation. Four filters comprise this module: the first one acts on smoothness of the image, the second one removes image background enhancing plants leaves, the third filter removes isolated dots not removed by the previous filter, and the fourth one is used to highlight leaves' edges. At first the filters were tested with MATLAB, for a quick visual feedback of the filters' behavior. Then the filters were implemented in the C programming language. At last, the module as been coded in VHDL for the implementation on a Stratix II family FPGA. Tests were run and the results are shown in this paper. © 2008 Springer-Verlag Berlin Heidelberg.

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Measurements of simulated periodontal bone defects in inverted digital image and film-based radiograph: An in vitro study

Purpose: This study was performed to compare the inverted digital images and film-based images of dry pig mandibles to measure the periodontal bone defect depth. Materials and Methods: Forty 2-wall bone defects were made in the proximal region of the premolar in the dry pig mandibles. The digital and conventional radiographs were taken using a Schick sensor and Kodak F-speed intraoral film. Image manipulation (inversion) was performed using Adobe Photoshop 7.0 software. Four trained examiners made all of the radiographic measurements in millimeters a total of three times from the cementoenamel junction to the most apical extension of the bone loss with both types of images: inverted digital and film. The measurements were also made in dry mandibles using a periodontal probe and digital caliper. The Student's t-test was used to compare the depth measurements obtained from the two types of images and direct visual measurement in the dry mandibles. A significance level of 0.05 for a 95% confidence interval was used for each comparison. Results: There was a significant difference between depth measurements in the inverted digital images and direct visual measurements (p>|t|=0.0039), with means of 6.29 mm (IC95%:6.04-6.54) and 6.79 mm (IC95%:6.45-7.11), respectively. There was a non-significant difference between the film-based radiographs and direct visual measurements (p>|t|=0.4950), with means of 6.64mm (IC95%:6.40-6.89) and 6.79mm(IC95%:6.45-7.11), respectively. Conclusion: The periodontal bone defect measurements in the inverted digital images were inferior to film-based radiographs, underestimating the amount of bone loss. copy; 2012 by Korean Academy of Oral and Maxillofacial Radiology.

Evaluation epidermal p53 immunostaining by digital image analysis

Digital techniques have been developed and validated to assess semiquantitatively immunohistochemical nuclear staining. Currently visual classification is the standard for qualitative nuclear evaluation. Analysis of pixels that represents the immunohistochemical labeling can be more sensitive, reproducible and objective than visual grading. This study compared two semiquantitative techniques of digital image analysis with three techniques of visual analysis imaging to estimate the p53 nuclear immunostaining. Methods: Sixty-three sun-exposed forearm-skin biopsies were photographed and submitted to three visual analyses of images: the qualitative visual evaluation method (0 to 4 +), the percentage of labeled nuclei and HSCORE. Digital image analysis was performed using ImageJ 1.45p; the density of nuclei was scored per ephitelial area (DensNU) and the pixel density was established in marked suprabasal epithelium (DensPSB). Results: Statistical significance was found in: the agreement and correlation among the visual estimates of evaluators, correlation among the median visual score of the evaluators, the HSCORE and the percentage of marked nuclei with the DensNU and DensPSB estimates. DensNU was strongly correlated to the percentage of p53-marked nuclei in the epidermis, and DensPSB with the HSCORE. Conclusion: The parameters presented herein can be applied in routine analysis of immunohistochemical nuclear staining of epidermis. © 2012 John Wiley & Sons A/S.

Image quality evaluation of chest for computed radiography

The daily-to-day of medical practice is marked by a constant search for an accurate diagnosis and therapeutic assessment. For this purpose the doctor serves up a wide variety of imaging techniques, however, the methods using ionizing radiation still the most widely used because it is considered cheaper and above all very efficient when used with control and quality. The optimization of the risk-benefit ratio is considered a major breakthrough in relation to conventional radiology, though this is not the reality of computing and digital radiology, where Brazil has not established standards and protocols for this purpose. This work aims to optimize computational chest radiographs (anterior-posterior projection-AP). To achieve this objective were used a homogeneous phantoms that simulate the characteristics of absorption and scattering of radiation close to the chest of a patient standard. Another factor studied was the subjective evaluation of image quality, carried out by visual grading assessment (VGA) by specialists in radiology, using an anthropomorphic phantom to identify the best image for a particular pathology (fracture or pneumonia). Quantifying the corresponding images indicated by the radiologist was performed from the quantification of physical parameters (Detective Quantum Efficiency - DQE, Modulation Transfer Function - MTF and Noise Power Spectrum - NPS) using the software MatLab®. © 2013 Springer-Verlag.

Ilustração: passeio pela poesia visual

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Imagens imersivas: estudo sobre a dicotomia proximidade e afastamento no jornalismo visual

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Espaço e identidade visual: uma investigação sobre soluções de design para empresas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)