1,058 research outputs found

    Detection of curved lines with B-COSFIRE filters: A case study on crack delineation

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    The detection of curvilinear structures is an important step for various computer vision applications, ranging from medical image analysis for segmentation of blood vessels, to remote sensing for the identification of roads and rivers, and to biometrics and robotics, among others. %The visual system of the brain has remarkable abilities to detect curvilinear structures in noisy images. This is a nontrivial task especially for the detection of thin or incomplete curvilinear structures surrounded with noise. We propose a general purpose curvilinear structure detector that uses the brain-inspired trainable B-COSFIRE filters. It consists of four main steps, namely nonlinear filtering with B-COSFIRE, thinning with non-maximum suppression, hysteresis thresholding and morphological closing. We demonstrate its effectiveness on a data set of noisy images with cracked pavements, where we achieve state-of-the-art results (F-measure=0.865). The proposed method can be employed in any computer vision methodology that requires the delineation of curvilinear and elongated structures.Comment: Accepted at Computer Analysis of Images and Patterns (CAIP) 201

    A Search for Wolf-Rayet Stars in the Small Magellanic Cloud

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    We conducted an extensive search for Wolf-Rayet stars (W-Rs) in the SMC, using the same interference filter imaging techniques that have proved successful in finding W-Rs in more distant members of the Local Group. Photometry of some 1.6 million stellar images resulted in some 20 good candidates, which we then examined spectroscopically. Two of these indeed proved to be newly found W-Rs, bringing the total known in the SMC from 9 to 11. Other finds included previously unknown Of-type stars (one as early as O5f?p)),the recovery of the Luminous Blue Variable S18, and the discovery of a previously unknown SMC symbiotic star. More important, however, is the fact that there does not exist a significant number of W-Rs waiting to be discovered in the SMC. The number of W-Rs in the SMC is a factor of 3 lower than in the LMC (per unit luminosity), and we argue this is the result of the SMC's low metallicity on the evolution of the most massive stars.Comment: Accepted by Astrophysical Journal. Postscript version available via ftp.lowell.edu/pub/massey/smcwr.ps.gz Revised version contains slightly revised spectral types for the Of stars but is otherwise unchange

    Filter-based approach for ornamentation detection and recognition in singing folk music

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    This is a Conference paper presented by the authors at the CAiP 2015; 16th International Conference on Computer Analysis of Images and Patterns, held in Malta from the 2 to 4 September, 2015.Ornamentations in music play a significant role for the emotion which a performer or a composer aims to create. The automated identification of ornamentations enhances the understanding of music, which can be used as a feature for tasks such as performer identification or mood classification. Existing methods rely on a pre-processing step that performs note segmentation. We propose an alternative method by adapting the existing two-dimensional COSFIRE filter approach to onedimension (1D) for the automatic identification of ornamentations in monophonic folk songs. We construct a set of 1D COSFIRE filters that are selective for the 12 notes of the Western music theory. The response of a 1D COSFIRE filter is computed as the geometric mean of the differences between the fundamental frequency values in a local neighbourhood and the preferred values at the corresponding positions. We apply the proposed 1D COSFIRE filters to the pitch tracks of a song at every position along the entire signal, which in turn give response values in the range [0,1]. The 1D COSFIRE filters that we propose are effective to recognize meaningful musical information which can be transformed into symbolic representations and used for further analysis. We demonstrate the effectiveness of the proposed methodology in a new data set that we introduce, which comprises five monophonic Cypriot folk tunes consisting of 428 ornamentations. The proposed method is effective for the detection and recognition of ornamentations in singing folk music.This research was funded from the Republic of Cyprus through the Cyprus research promotion foundation and also supported by the University of Cyprus by the research grant ANΘPΩΠIΣTIKEΣ / ANΘPΩ / 0311(BE) / 19.peer-reviewe

    Study of the impacts of droplets deposited from the gas core onto a gas-sheared liquid film

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    The results of an experimental study on droplet impactions in the flow of a gas-sheared liquid film are presented. In contrast to most similar studies, the impacting droplets were entrained from film surface by the gas stream. The measurements provide film thickness data, resolved in both longitudinal and transverse coordinates and in time together with the images of droplets above the interface and images of gas bubbles entrapped by liquid film. The parameters of impacting droplets were measured together with the local liquid film thickness. Two main scenarios of droplet-film interaction, based on type of film perturbation, are identified; the parameter identifying which scenario occurs is identified as the angle of impingement. At large angles an asymmetric crater appears on film surface; at shallow angles a long, narrow furrow appears. The most significant difference between the two scenarios is related to possible impact outcome: craters may lead to creation secondary droplets, whereas furrows are accompanied by entrapment of gas bubbles into the liquid film. In addition, occurrence of partial survival of impacting droplet is reported

    Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews

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    Background: Digital data sources have become ubiquitous in modern culture in the era of digital technology but often tend to be under-researched because of restricted access to data sources due to fragmentation, privacy issues, or industry ownership, and the methodological complexity of demonstrating their measurable impact on human health. Even though new big data sources have shown unprecedented potential for disease diagnosis and outbreak detection, we need to investigate results in the existing literature to gain a comprehensive understanding of their impact on and benefits to human health. / Objective: A systematic review of systematic reviews on identifying digital data sources and their impact area on people's health, including challenges, opportunities, and good practices. Methods: A multidatabase search was performed. Peer-reviewed papers published between January 2010 and November 2020 relevant to digital data sources on health were extracted, assessed, and reviewed. / Results: The 64 reviews are covered by three domains, that is, universal health coverage (UHC), public health emergencies, and healthier populations, defined in WHO's General Programme of Work, 2019-2023, and the European Programme of Work, 2020-2025. In all three categories, social media platforms are the most popular digital data source, accounting for 47% (N = 8), 84% (N = 11), and 76% (N = 26) of studies, respectively. The second most utilized data source are electronic health records (EHRs) (N = 13), followed by websites (N = 7) and mass media (N = 5). In all three categories, the most studied impact of digital data sources is on prevention, management, and intervention of diseases (N = 40), and as a tool, there are also many studies (N = 10) on early warning systems for infectious diseases. However, they could also pose health hazards (N = 13), for instance, by exacerbating mental health issues and promoting smoking and drinking behavior among young people. / Conclusions: The digital data sources presented are essential for collecting and mining information about human health. The key impact of social media, electronic health records, and websites is in the area of infectious diseases and early warning systems, and in the area of personal health, that is, on mental health and smoking and drinking prevention. However, further research is required to address privacy, trust, transparency, and interoperability to leverage the potential of data held in multiple datastores and systems. This study also identified the apparent gap in systematic reviews investigating the novel big data streams, Internet of Things (IoT) data streams, and sensor, mobile, and GPS data researched using artificial intelligence, complex network, and other computer science methods, as in this domain systematic reviews are not common

    Automatic differentiation of u- and n-serrated patterns in direct immunofluorescence images

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    Epidermolysis bullosa acquisita (EBA) is a subepidermal autoimmune blistering disease of the skin. Manual u- and n-serrated patterns analysis in direct immunofluorescence (DIF) images is used in medical practice to differentiate EBA from other forms of pemphigoid. The manual analysis of serration patterns in DIF images is very challenging, mainly due to noise and lack of training of the immunofluorescence (IF) microscopists. There are no automatic techniques to distinguish these two types of serration patterns. We propose an algorithm for the automatic recognition of such a disease. We first locate a region where u- and n-serrated patterns are typically found. Then, we apply a bank of B-COSFIRE filters to the identified region of interest in the DIF image in order to detect ridge contours. This is followed by the construction of a normalized histogram of orientations. Finally, we classify an image by using the nearest neighbors algorithm that compares its normalized histogram of orientations with all the images in the dataset. The best results that we achieve on the UMCG publicly available data set is 84.6% correct classification, which is comparable to the results of medical experts

    Gas rising through a large diameter column of very viscous liquid: Flow patterns and their dynamic characteristics

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    Gas-liquid flows are affected strongly by both the liquid and gas properties and the pipe diameter, which control features and the stability of flow patterns and their transitions. For this reason, empirical models describing the flow dynamics can be applied only to limited range of conditions. Experiments were carried out to study the behaviour of air passing through silicone oil (360 Pa.s) in 240 mm diameter bubble column using Electrical Capacitance Tomography and pressure transducers mounted on the wall. These experiments are aimed at reproducing expected conditions for flows including (but not limited to) crude oils, bitumen, and magmatic flows in volcanic conduits. The paper presents observation and quantification of the flow patterns present. It particularly provides the characteristics of gas-liquid slug flows such as: void fraction; Taylor bubble velocity; frequency of periodic structures; lengths of liquid slugs and Taylor bubbles. An additional flow pattern, churn flow, has been identified. The transition between slug and churn has been quantified and the mechanism causing it are elucidated with the assistance of a model for the draining of the liquid film surrounding the Taylor bubble once this has burst through the top surface of the aerated column of gas-liquid mixture. It is noted that the transition from slug to churn is gradual
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