Automatic Contextual Thresholding of Color Images: Application in Road Seed Extraction

In this paper is a totally automatic strategy proposed to reduce the complexity of patterns (vegetation, building, soils etc.) that interact with the object ´road´ in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computationknown as NandA (Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Severalexperiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort.Neste artigo é proposta uma estratégia totalmente automática para reduzir a complexidade de padrões (vegetação, edificações, solos etc.) que interagem com o objeto ´rodovia´ em imagens coloridas, reduzindo conseqüentemente a dificuldade na extração automática desse objeto. A metodologia proposta consiste em três etapas seqüências. Na primeira etapa é aplicado o operador pontual para o cálculo de índice de artificialidade denominado NandA (Natural and Artificial). O resultado é uma imagem cujo atributo de intensidade é a resposta do NandA. A segunda etapa consiste na limiarização automática da imagem obtida no passo anterior, resultando numa imagem binária. Esta imagem geralmente permite separar os objetos artificiais e naturais. A terceira etapa consiste em aplicar uma metodologia preexistentepara a extração de sementes de rodovia a partir da imagem binária gerada na segunda etapa. Vários experimentos realizados com imagens reais possibilitaram uma verificação experimental do potencial da metodologia proposta. A comparação dos resultados obtidos, com os correspondentes gerados por uma metodologia para extração de sementes de rodovia em imagens pancromáticas, possibilitou verificar que o principal benefício foi adrástica diminuição do esforço computacional

AUTOMATIC EXTRACTION OF RIVERS IN SATELLITE IMAGES USING GEOMETRIC ACTIVE CONTOURS

This work aims to define and test a method for the extraction of rivers in orbital images for regions that are seasonally flooded, ie, large areas containing more water bodies besides the river, such as Pantanal. In the proposed methodology, several tools from the area of Image Analysis and Computer Vision have been employed, performing a preprocessing, followed by a topological modeling that is built upon a skeletonization process followed by an analysis of this skeleton. Lastly, the methodology selects structure that represents the river, by performing a topological filtering. This process is responsible for the selection of points that initiate the process of delineation of rivers using a geometric active contour method, called .Level Set Method.. The methodology was evaluated qualitatively (visual) and quantitatively (numerical) using the criteria of completeness and correctness in a series of real images of the Pantanal region. The edges extracted from rivers, were projected onto the original images, thus allowing a qualitative assessment. With respect to the numerical results for the criteria of completeness and correctness, these were always above 80%, which shows that the methodology is very effective and robust for the community that needs to perform feature extraction in remote sensing image

Anais do V Encontro Brasileiro de Educomunicação: Educação midiática e políticas públicas

A presente coletânea, que chega ao público através de um suporte digital, tem como objetivo disponibilizar os papers, bem como os relatos de experiências educomunicativas apresentados durante o V ENCONTRO BRASILEIRO DE EDUCOMUNICAÇÃO, que teve como tema central: “Educação Midiática e Políticas Públicas”. O evento foi realizado em São Paulo, entre 19 e 21 de setembro de 2013, a partir de uma parceria entre o NCE/USP - Núcleo de Comunicação e Educação da USP, a Licenciatura em Educomunicação da ECA/USP, a ABPEducom – Associação Brasileira de Pesquisadores e Profissionais da Educomunicação e a FAPCOM – Faculdade Paulus de Tecnologia e Comunicação, que ofereceu seu campus, na Vila Mariana, para os atos do evento. Os presentes anais disponibilizam o texto de abertura, de autoria do coordenador geral do evento, denominado “Educação midiática e políticas públicas: vertentes históricas da emergência da Educomunicação na América Latina”. Na sequência, apresentam 61 papers sobre aspectos específicos da temática geral, resultantes de pesquisas na área, seguidos de 27 relatos de práticas educomunicativas, em nível nacional

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Metodologia automática para extração de cruzamentos de rodovias em imagens de alta resolução

Pesquisas em extração de rodovias em imagens digitais não são recentes, sendo as primeiras da década de 70. Os métodos desenvolvidos normalmente são classificados em duas classes: semi-automático e automático. Esta última classe não prevê a intervenção de um operador. Neste contexto, a extração automática de cruzamentos de rodovias é fundamental, embora muito poucos trabalhos são encontrados na literatura sobre extração de rodovias. A razão principal é a grande diversidade de cruzamentos de rodovias, gerando algumas dificuldades para construir um conhecimento a priori sobre cruzamentos. Esta pesquisa propõe uma metodologia automática para resolver este problema, combinando segmentos de rodovias extraídos de uma imagem de alta resolução (pixel 2m), reamostrada da imagem original de alta resolução. A metodologia proposta foi testada em um conjunto de imagens de alta resolução, mostrando-se confiável e eficiente. Desde que as bordas das rodovias sejam satisfatoriamente definidas, o método se mostrou capaz de extrair totalmente os cruzamentos de rodovias. Além disso, gerou uma significante melhora na malha viária (aproximadamente 16%) extraída pela metodologia automática de extração de segmentos de rodovias.Researches on road extraction from digital images are not recent, being the first one from 70's. The methods developed are usually classified into two classes, i.e., semiautomatic and automatic. Concerning this last class, no intervention with the operator is expected. In this context, the road crossing extraction is fundamental, although very few works are found in the relevant literature. The main reason is the great diversity of road crossings, bringing some difficulties to build up a priori knowledge of them. This research proposes a methodology for solving this problem combining road segments extracted from a high – resolution image (pixel 2m) resampled from the original, high – resolution image. The proposed methodology was tested with a set of high – resolution image, showing that it is reliable and efficient. Whenever the road edges were well - defined the method was able to totally extract the road crossings. In addition it provided road networks with completion significantly better (about 16%) than the corresponding ones previously extracted by the automatic road segment extraction method.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Extração semiautomática de rodovias no espaço-objeto: uso integrado de um estereopar de imagens aéreas e um MDT

Neste artigo é proposto um método semiautomático para extração de rodovias combinando um estereopar de imagens aéreas de baixa resolução com um poliedro gerado a partir de um modelo digital do terreno (MDT). O problema é formulado no espaço-objeto através de uma função objetivo que modela o objeto 'rodovia' como uma curva suave e pertencente a uma superfície poliédrica. A função objetivo proposta depende também de informações radiométricas, que são acessadas no espaço-imagem via relação de colinearidade entre pontos da rodovia no espaço-objeto e os correspondentes nos espaços imagem do estereopar. A linha poligonal que melhor modela a rodovia selecionada é obtida por otimização no espaço-objeto da função objetivo, tendo por base o algoritmo de programação dinâmica. O processo de otimização é iterativo e dependente do fornecimento por um operador de uma aproximação inicial para a rodovia selecionada. Os resultados obtidos mostraram que o método é robusto frente a anomalias existentes ao longo das rodovias, tais como obstruções causadas por sombras e árvores.In this paper a semiautomatic method is proposed for road extraction by combining a stereoscopic pair of low-resolution aerial images and a polyhedron generated by using a digital terrain model (DTM). The problem is formulated in the object space by means of an objective function which models the object 'road' as a smooth curve that belongs to a polyhedral surface. The proposed objective function also depends on the radiometric information, which is accessed in the image space via collinearity relation between road points, in the object space and corresponding points in the image spaces of stereoscopic images. The polyline providing the best representation for a selected road is obtained in the object space via optimization of the objective function by using the dynamic programming algorithm. The optimization process is iterative and an operator needs to supply an initial polyline approximating the selected road. The obtained results showed that the method is robust against anomalies existing along roads, such as obstruction caused by shadows and trees

Limiarização contextual automática de imagens coloridas: aplicação na extração de sementes de rodovia

In this paper is a totally automatic strategy proposed to reduce the complexity of patterns ( vegetation, building, soils etc.) that interact with the object 'road' in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computation known as NandA ( Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Several experiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort