Gaussian Image Binarization

2021 ◽  
pp. 2150047
Author(s):  
Henry Kang ◽  
Ioannis Stamoulis
Keyword(s):  
Hybrid Method ◽  
Line Drawing ◽  
Research Community ◽  
The Other ◽  
Image Binarization ◽  
Unified Framework ◽  
Line Extraction ◽  
Difference Of Gaussians ◽  
Photorealistic Rendering ◽  
Binarization Method

Line drawing and screentoning are two distinct areas of study in non-photorealistic rendering, where the former emphasizes object contours, while the latter conveys tone and shading information on object surfaces. As these two problems are concerned with different yet equally important features, either method seldom delivers a complete description of the scene when used alone. Yet, research community has largely treated them as separate problems and thus resulted in two entirely different sets of solutions, complicating both implementation and usage. In this paper, we present a stylistic image binarization method called hybrid difference of Gaussians (HDoG) that performs both line drawing and screentoning in a unified framework. Our method is based upon two different extensions of DoG operator: one for line extraction, and the other for tone description. In particular, we propose an extension called adaptive DoG, that uses luminance as weight to automatically generate screentone that adapts to the local tone. Experimental results demonstrate that our hybrid method effectively generates aesthetically pleasing image binarizations that encompass both line drawing and screentoning, closely resembling professional pen-and-ink illustrations. Also, being based on Gaussian filtering, our method is very fast and also easy to implement.

scholarly journals Line-Drawn Scenes Provide Sufficient Information for Discrimination of Threat and Mere Negativity

i-Perception ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 204166951875580 ◽  
Author(s):  
Jasmine Boshyan ◽  
Lisa Feldman Barrett ◽  
Nicole Betz ◽  
Reginald B. Adams ◽  
Kestutis Kveraga
Keyword(s):  
Trend Analysis ◽  
Visual Information ◽  
Line Drawing ◽  
Research Community ◽  
Sufficient Information ◽  
Line Drawings ◽  
Different Types ◽  
Temporal Dimensions ◽  
Matching Color ◽  
Negative Stimuli

Previous work using color photographic scenes has shown that human observers are keenly sensitive to different types of threatening and negative stimuli and reliably classify them by the presence, and spatial and temporal directions of threat. To test whether such distinctions can be extracted from impoverished visual information, we used 500 line drawings made by hand-tracing the original set of photographic scenes. Sixty participants rated the scenes on spatial and temporal dimensions of threat. Based on these ratings, trend analysis revealed five scene categories that were comparable to those identified for the matching color photographic scenes. Another 61 participants were randomly assigned to rate the valence or arousal evoked by the line drawings. The line drawings perceived to be the most negative were also perceived to be the most arousing, replicating the finding for color photographic scenes. We demonstrate here that humans are very sensitive to the spatial and temporal directions of threat even when they must extract this information from simple line drawings, and rate the line drawings very similarly to matched color photographs. The set of 500 hand-traced line-drawing scenes has been made freely available to the research community: http://www.kveragalab.org/threat.html .

scholarly journals Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1621 ◽  
Author(s):  
Alfredo Nespoli ◽  
Emanuele Ogliari ◽  
Sonia Leva ◽  
Alessandro Massi Pavan ◽  
Adel Mellit ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Mean Absolute Error ◽  
Weather Forecast ◽  
Absolute Error ◽  
The Other ◽  
Pv System ◽  
Weather Forecasts ◽  
Forecasting Method ◽  
Forecasting Performance ◽  
Stable Performance

We compare the 24-hour ahead forecasting performance of two methods commonly used for the prediction of the power output of photovoltaic systems. Both methods are based on Artificial Neural Networks (ANN), which have been trained on the same dataset, thus enabling a much-needed homogeneous comparison currently lacking in the available literature. The dataset consists of an hourly series of simultaneous climatic and PV system parameters covering an entire year, and has been clustered to distinguish sunny from cloudy days and separately train the ANN. One forecasting method feeds only on the available dataset, while the other is a hybrid method as it relies upon the daily weather forecast. For sunny days, the first method shows a very good and stable prediction performance, with an almost constant Normalized Mean Absolute Error, NMAE%, in all cases (1% < NMAE% < 2%); the hybrid method shows an even better performance (NMAE% < 1%) for two of the days considered in this analysis, but overall a less stable performance (NMAE% > 2% and up to 5.3% for all the other cases). For cloudy days, the forecasting performance of both methods typically drops; the performance is rather stable for the method that does not use weather forecasts, while for the hybrid method it varies significantly for the days considered in the analysis.

An Object-Oriented Awareness-Based Methodology for ERP

2011 ◽  
pp. 149-159
Author(s):  
Farhad Daneshgar
Keyword(s):  
Knowledge Sharing ◽  
Conceptual Model ◽  
Business Processes ◽  
Research Community ◽  
Computer Supported Cooperative Work ◽  
The Other ◽  
Successful Implementation ◽  
Conceptual Modelling ◽  
Erp Systems ◽  
Is Development

It is now believed that success of ERP systems is largely dependent on not only the successful evaluation, selection, implementation and post-implementation of ERP systems, but also on integrating it with the organizational business processes. On the other hand, nearly all business processes are collaborative in the sense that multiple human agents or actors interact with one another for achieving one or more process goals. As a result, one can claim that one major factor in successful implementation of the ERP systems is development of appropriate conceptual models of the ERP process from various perspectives. In this chapter the writer, being a member of the CSCW (computer supported cooperative work) research community, introduces a conceptual model for ERP which has an emphasis on the collaborative nature of ERP process that explicitly addresses the “awareness” and “knowledge-sharing” issues within the ERP process. This conceptual model demonstrates collaboration requirements of the actors behind individual business processes as well as the relationships among these business processes. This chapter is intended to introduce to the ERP community a relevant piece of work in conceptual modelling from the perspective of CSCW with the aim of attracting research collaborators for further investigation in these fields.

scholarly journals Ethical and Scientific Pitfalls Concerning Laboratory Research with Non-Human Primates, and Possible Solutions

Animals ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Constança Carvalho ◽  
Augusta Gaspar ◽  
Andrew Knight ◽  
Luís Vicente
Keyword(s):  
Laboratory Animal ◽  
Ethics Committees ◽  
Research Community ◽  
The Other ◽  
Laboratory Research ◽  
Human Beings ◽  
Ethical Challenges ◽  
Ethical Frameworks ◽  
Moral Duties ◽  
The One

Basic and applied laboratory research, whenever intrusive or invasive, presents substantial ethical challenges for ethical committees, be it with human beings or with non-human animals. In this paper we discuss the use of non-human primates (NHPs), mostly as animal models, in laboratory based research. We examine the two ethical frameworks that support current legislation and guidelines: deontology and utilitarianism. While human based research is regulated under deontological principles, guidelines for laboratory animal research rely on utilitarianism. We argue that the utilitarian framework is inadequate for this purpose: on the one hand, it is almost impossible to accurately predict the benefits of a study for all potential stakeholders; and on the other hand, harm inflicted on NHPs (and other animals) used in laboratory research is extensive despite the increasing efforts of ethics committees and the research community to address this. Although deontology and utilitarianism are both valid ethical frameworks, we advocate that a deontological approach is more suitable, since we arguably have moral duties to NHPs. We provide suggestions on how to ensure that research currently conducted in laboratory settings shifts towards approaches that abide by deontological principles. We assert that this would not impede reasonable scientific research.

An enhanced image binarization method incorporating with Monte-Carlo simulation

2019 ◽  
Vol 26 (6) ◽  
pp. 1661-1671
Author(s):  
Zheng Han ◽  
Bin Su ◽  
Yan-ge Li ◽  
Yang-fan Ma ◽  
Wei-dong Wang ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Image Binarization ◽  
Binarization Method

Disciplinary Translations

2020 ◽  
Vol 26 (2) ◽  
pp. 230-250
Author(s):  
Casper Bruun Jensen
Keyword(s):  
Science And Technology Studies ◽  
Science And Technology ◽  
Research Community ◽  
The Other ◽  
Literary Studies ◽  
Knowledge Change ◽  
Technical Mediation ◽  
The One ◽  
Nonhuman Agency ◽  
Instructive Case

Early in his career, Bruno Latour’s limited readership consisted mainly of the research community in science and technology studies (STS) that he helped to inaugurate. Today the situation could hardly be more different. Latour is now subject to the “translations”—the processes by which ideas travel—that he has provided such powerful tools for analyzing. He has become a “mutable mobile”—eminently transportable but always changing as he goes—that in different contexts exists as a variety of conceptual characters or figurations. As the Latour network continues to see significant extensions and transformations, it offers an instructive case for understanding the potentials and dynamics of traveling texts and ideas—and of their relation to existing disciplinary formations—as ecologies of knowledge change. This article examines the reception and adaptation of Latour’s ideas in two quite different intellectual contexts: anthropology and literary studies. The proliferation of Latour figurations is shown to be a consequence of interactions between, on the one hand, existing disciplinary constellations of ideas, concerns, and practices, and, on the other hand, his own often ambiguous arguments on topics including theory and method, nonhuman agency and politics, and technical mediation.

Plateaus and Asymptotes

2017 ◽  
Vol 26 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Wayne D. Gray
Keyword(s):  
Experimental Psychology ◽  
Deliberate Practice ◽  
Research Community ◽  
The Other ◽  
Performance Limits ◽  
Training Problem ◽  
Performance Levels ◽  
Active User ◽  
And Performance ◽  
Learning And Performance

One hundred twenty years ago, the emergent field of experimental psychology debated whether plateaus of performance during training were real or not. Sixty years ago, the battle was over whether learning asymptoted or not. Thirty years ago, the research community was seized with concerns over stable plateaus at suboptimal performance levels among experts. Applied researchers viewed this as a systems problem and referred to it as the paradox of the active user. Basic researchers diagnosed this as a training problem and embraced deliberate practice. The concepts of plateaus and asymptotes and the distinction between the two are important as the questions asked and the means of overcoming one or the other differ. These questions have meaning as we inquire about the nature of performance limits in skilled behavior and the distinction between brain capacity and brain efficiency. This article brings phenomena that are hiding in the open to the attention of the research community in the hope that delineating the distinction between plateaus and asymptotes will help clarify the distinction between real versus “spurious limits” and advance theoretical debates regarding learning and performance.

Chained Beam-Constraint-Model (CBCM): A Powerful Tool for Modeling Large and Complicated Deflections of Flexible Beams in Compliant Mechanisms

2014 ◽  
Author(s):  
Fulei Ma ◽  
Guimin Chen
Keyword(s):  
Large Deflection ◽  
Compliant Mechanisms ◽  
Research Community ◽  
The Other ◽  
New Method ◽  
Flexible Beam ◽  
Large Deflections ◽  
Flexible Beams ◽  
Constraint Model

Modeling large deflections has been one of the most fundamental problems in the research community of compliant mechanisms. Although many methods are available, there still exists a need for a method that is simple, accurate, and can be applied to a vast variety of large deflection problems. Based on the beam constraint model (BCM), we propose a new method for modeling large deflections called chained BCM (CBCM), which divides a flexible beam into a few elements and models each element by BCM. It is demonstrated that CBCM is capable of modeling various large and complicated deflections of flexible beams in compliant mechanisms. In general, CBCM obtains accurate results with no more than 6 BCM elements, thus is more efficient than most of the other discretization-based methods.

CONNECTIONIST MODEL BINARIZATION

1991 ◽  
Vol 05 (04) ◽  
pp. 629-644 ◽  
Author(s):  
NOBORU BABAGUCHI ◽  
KOJI YAMADA ◽  
KOICHI KISE ◽  
YOSHIKAZU TEZUKA
Keyword(s):  
Back Propagation ◽  
Connectionist Model ◽  
Gray Level ◽  
Threshold Selection ◽  
Back Propagation Algorithm ◽  
Image Binarization ◽  
Multilayer Network ◽  
Binarization Method ◽  
Gray Level Histogram ◽  
Binarized Image

Image binarization is a task to convert gray-level images into bi-level ones. Its underlying notion can be simply thought of as threshold selection. However, the result of binarization will cause significant influence on the process of image recognition or understanding. In this paper we discuss a new binarization method, named CMB (connectionist model binarization), which uses the connectionist model. In the method a gray-level histogram is input to a multilayer network trained with the back-propagation algorithm to obtain a threshold which gives a visually suitable binarized image. From the experimental results, it was verified that CMB is an effective binarization method in comparison with other methods.

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