Image Processing Approaches and Disaster Management

Author(s):  
Surendra Rahamatkar

This chapter presents the relevance of picture handling to distinguish different sorts of harm. For areal-type harm, 1) edge extraction, 2) unsupervised arrangement, 3) texture examination, and 4) edge improvement are suitable to distinguish harmed zone. For liner-type harm, it is hard to improve the permeability of harm partition by picture preparing. Likewise, the impact of overlaying office information to help staff to discover harm at an extraction is described.

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.


Author(s):  
H. Mohammadi ◽  
M. R. Delavar ◽  
M. A. Sharifi ◽  
M. D. Pirooz

Disaster risk is a function of hazard and vulnerability. Risk is defined as the expected losses, including lives, personal injuries, property damages, and economic disruptions, due to a particular hazard for a given area and time period. Risk assessment is one of the key elements of a natural disaster management strategy as it allows for better disaster mitigation and preparation. It provides input for informed decision making, and increases risk awareness among decision makers and other stakeholders. Virtual globes such as Google Earth can be used as a visualization tool. Proper spatiotemporal graphical representations of the concerned risk significantly reduces the amount of effort to visualize the impact of the risk and improves the efficiency of the decision-making process to mitigate the impact of the risk. The spatiotemporal visualization of tsunami waves for disaster management process is an attractive topic in geosciences to assist investigation of areas at tsunami risk. In this paper, a method for coupling virtual globes with tsunami wave arrival time models is presented. In this process we have shown 2D+Time of tsunami waves for propagation and inundation of tsunami waves, both coastal line deformation, and the flooded areas. In addition, the worst case scenario of tsunami on Chabahar port derived from tsunami modelling is also presented using KML on google earth.


2018 ◽  
Vol 3 (9) ◽  
pp. 113
Author(s):  
Rustam Khairi Zahari ◽  
Raja Noriza Raja Ariffin ◽  
Zainora Asmawi ◽  
Aisyah Nadhrah Ibrahim

The Indian Ocean tsunami of 26th December 2004 unleashed catastrophe in many nations including coastal communities located along the west-coast of Malaysian Peninsular.  The goal of this study is to explore the impact of the tsunami to the preparedness of the affected coastal communities.   Data was collected through questionnaire, interviews, documents analysis and field observations.  It was found that the 2004 tsunami disaster has left a significant mark on Malaysia's and the world's disaster management landscape but the tragedy has also heightened disaster awareness and steps must be taken to ensure vulnerable communities are well-equipped to face any eventualities. Keywords:  Tsunami; sustainable coastal communities; disaster management; vulnerability. eISSN 2514-7528 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.


2021 ◽  
pp. SP501-2021-17
Author(s):  
Yildirim Dilek ◽  
Yujiro Ogawa ◽  
Yasukini Okubo

AbstractEarthquakes and tsunamis are high–impact geohazard events that could be extremely destructive when they occur at large magnitudes and intensities, respectively, although their causes and potential locations are, for the most part, predictable within the framework of plate tectonics. Amongst the main reasons for their high impact include enormous numbers of casualties, extensive property damage in vast areas, and significant social and economic disruptions in urban settings where populous residential areas, global banking centres, industrial factories, and critical facilities (nuclear power plants, dams) may be located. In order to reduce the impact of these geohazards, the nations, societies, professional organizations and governments need to collaborate to prepare more effective seismic and tsunami risk assessments, disaster management plans, educational and training programmes for increased preparedness of the public, and strategic plans and objectives for capacity building, skill and knowledge transfer, and building of societal resilience. Improved building design and construction codes, and emergency preparedness and evacuation plans should be part of disaster management plans in countries where destructive earthquakes and tsunamis occurred earlier. Fast increasing population in coastal corridors in developing and developed countries is likely to escalate the social and economic impacts of these geohazards exponentially in the future. The chapters in this book present case studies of some of the most salient earthquake and tsunami events in historical and modern times, their origins and manifestations, and efforts and most effective practices of risk assessment and disaster management implemented by various governments, international organizations and inter–governmental agencies following these events. New methods of computing probabilistic seismic hazard risks, delineating respect distance and damage zones along–across seismically active faults and recognizing tsunamigenic and submarine landslides on the seafloor are introduced. The conclusions presented in the chapters show that: (1) scientific understanding of the characteristics of seismically active faults is paramount; (2) increased local (community), national and global resilience is necessary to empower societal preparedness for earthquake and tsunami events; and, (3) all stakeholders, including policy–makers, scientists, local, state and national governments, media, and world organizations (UNESCO, IUGS, GeoHazards International–GHI, Global Geodetic Observing System–GGOS; National Earthquake Hazards Reduction Program–NEHRP) must work together to disseminate accurate and timely information on geohazards, to develop effective legislation for risk reduction, and to prepare realistic and practical hazard mitigation and management measures.


2009 ◽  
Author(s):  
Kai Graf ◽  
Olaf Müller

This paper describes a method for the acquisition of the flying shape of spinnakers in a twisted flow wind tunnel. The method is based on photogrammetry. A set of digital cameras is used to obtain high resolution images of the spinnaker from different viewing angles. The images are post-processed using image-processing tools, pattern recognition methods and finally the photogrammetry algorithm. Results are shown comparing design versus flying shape of the spinnaker and the impact of wind velocity and wind twist on the flying shape. Finally some common rules for optimum spinnaker trimming are investigated and examined.


2021 ◽  
Author(s):  
Shidong Li ◽  
Jianwei Liu ◽  
Zhanjie Song

Abstract Since magnetic resonance imaging (MRI) has superior soft tissue contrast, contouring (brain) tumor accurately by MRI images is essential in medical image processing. Segmenting tumor accurately is immensely challenging, since tumor and normal tissues are often inextricably intertwined in the brain. It is also extremely time consuming manually. Late deep learning techniques start to show reasonable success in brain tumor segmentation automatically. The purpose of this study is to develop a new region-ofinterest-aided (ROI-aided) deep learning technique for automatic brain tumor MRI segmentation. The method consists of two major steps. Step one is to use a 2D network with U-Net architecture to localize the tumor ROI, which is to reduce the impact of normal tissue’s disturbance. Then a 3D U-Net is performed in step 2 for tumor segmentation within identified ROI. The proposed method is validated on MICCAI BraTS 2015 Challenge with 220 high Gliomas grade (HGG) and 54 low Gliomas grade (LGG) patients’ data. The Dice similarity coefficient and the Hausdorff distance between the manual tumor contour and that segmented by the proposed method are 0.876 ±0.068 and 3.594±1.347 mm, respectively. These numbers are indications that our proposed method is an effective ROI-aided deep learning strategy for brain MRI tumor segmentation, and a valid and useful tool in medical image processing.


Biometrics ◽  
2017 ◽  
pp. 382-402
Author(s):  
Petre Anghelescu

In this paper are presented solutions to develop algorithms for digital image processing focusing particularly on edge detection. Edge detection is one of the most important phases used in computer vision and image processing applications and also in human image understanding. In this chapter, implementation of classical edge detection algorithms it is presented and also implementation of algorithms based on the theory of Cellular Automata (CA). This work is totally related to the idea of understanding the impact of the inherently local information processing of CA on their ability to perform a managed computation at the global level. If a suitable encoding of a digital image is used, in some cases, it is possible to achieve better results in comparison with the solutions obtained by means of conventional approaches. The software application which is able to process images in order to detect edges using both conventional algorithms and CA based ones is written in C# programming language and experimental results are presented for images with different sizes and backgrounds.


2018 ◽  
Vol 15 ◽  
pp. 57-76 ◽  
Author(s):  
Krishna Raj Tiwari ◽  
Santosh Rayamajhi

Nepal is prone to a variety of recurring natural disasters such as floods, landslides, snow avalanches, thunderstorms, drought, earth quake and epidemics. In particular, floods, landslides, hailstorms and drought are almost regular phenomena. This paper has focused mainly on water induced disaster (Monsoon) prepared through review of documents, consultation with related line agencies and field level interaction with affected communities. The paper also seeks to explore and document the major disasters and their impacts in Nepal. It discusses policy and program, institutional arrangement and activities related to the disaster management as well as identification of gaps in the policy and program. Nepal has attempted to manage the prevalence of these hazards and their associated disasters through both informal civic involvement and formal government instruments. A legal and policy environment to deal with disasters has existed in one or the other form in Nepal since 1982, and these have been reviewed. Study showed that disaster management activities only found initial response rather post disaster program. However, findings of the previous and present programs and activities on disaster management have not addressed effectively to the vulnerable people and to reduce the impact from disasters at the local level. It is suggested that disaster management policy and program should be integrated and mainstreamed in development agenda.


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