scholarly journals Railway Safety and Security using Image Processing and IOT

2021 ◽  
Vol 9 (VI) ◽  
pp. 2494-2501
Author(s):  
Mrs. S. S. Telsang
Keyword(s):  
Image Processing ◽  
Comparative Studies ◽  
Railway Tracks ◽  
The Poor ◽  
Railway Safety ◽  
Primary Form ◽  
Small Improvement

The railways have become the primary form of transportation because of their capability and speed. Even a small improvement in this sector will aid the overall development of a nation. There are various reasons for abnormalities that occur on railway tracks which result in breakdowns and accidents. The poor maintenance of the railway tracks will also result in accidents. The important aspect we are considering in this paper is to avoid the crowd of passengers in each compartment considering the Covid-19 situation. Other aspects are avoiding accidents in foggy conditions, obstacles in front of railways, due to track faults. Comparative studies of different methods used in these aspects of railways are made and the best which gives better accuracy is considered for Implementation.

ON A COMPARATIVE LANDSCAPE STUDIES OF DELTAS UNDER DESERTIFICATION PROCESS WITH LANDSCAPE PATTERTNS STRUCTURAL METRICS

2020 ◽  
Author(s):  
P. Reymov ◽  
◽  
Viktor Statov ◽  
G. Khudaybergenov ◽  
N. Mamutov ◽  
...  
Keyword(s):  
Image Processing ◽  
Landscape Metrics ◽  
Comparative Studies ◽  
Landscape Patterns ◽  
Aral Sea ◽  
Aral Sea Basin ◽  
Landscape Studies ◽  
Desertification Process ◽  
Input Layer ◽  
Structural Metrics

The report disputes some possibilities of landscape patterns structural metrics fot comparative studies of structural and functional affinity for intra-continental arid deltas, such us Aral Sea basin and Caspian plains. We suggest using optical indexes (NDVI, SAVI et al.) as a input layer for the statistical image processing and landscape metrics extracting.

The Contour Size Detection of Driver Airbag Based on Image Processing Technology

2013 ◽  
Vol 658 ◽  
pp. 546-550
Author(s):  
Xiao Dong Wang ◽  
Xiao Wei Chen ◽  
Wei Zhang ◽  
Bo Liu ◽  
Liang Dong An
Keyword(s):  
Image Processing ◽  
Template Matching ◽  
Detection Method ◽  
Detection Efficiency ◽  
Ccd Camera ◽  
Processing Technology ◽  
Edge Extraction ◽  
Image Preprocessing ◽  
The Poor ◽  
Image Processing Technology

In this paper we have developed a new methodology for detecting the contour size of driver airbag based on image processing technology and Machine vision. Through the CCD camera we can obtain the image, and then do the following operations by a computer, such as binarization, edge extraction and so on the other image preprocessing. This methodology uses intelligent template matching technology to detect the airbags and by comparing with the predefined parameter to determine whether the contour size is qualified .The experimental results show that: this new detection method solves the disadvantage of traditional detection method, such as the low detection efficiency, the detection precision is not high, the poor detection repeatability, the higher rate of detection miscarriage of justice.

scholarly journals Anomaly Detection System Using Digital Image Processing For The Indian Railways

2021 ◽  
pp. 186-190
Author(s):  
Sharmista Shastry ◽  
Amartya Anshuman ◽  
Vedant Tibrewal ◽  
Yogesh Kumar Choukiker
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Detection System ◽  
Cost Effective ◽  
Daily Basis ◽  
Economic Life ◽  
Railway Network ◽  
Loss Of Life ◽  
Railway Tracks

The Indian Railways are the lifeline of India's transport system. Being the fourth largest railway network in the world, it covers the length and breadth of the country. In 2018-19, 23.12 million people and 3.36 million metric tons of freight depended on the railways on a daily basis. They bind the economic life of the country and foster the development of industry and agriculture. However, poor maintenance of the railway tracks has caused several accidents over the years. Derailments due to the presence of faults in railway tracks cause heavy loss of life and railway property. Therefore, timely detection and analysis of these cracks is of utmost importance. This proposal aims at providing a cost effective solution to the problem of fault detection in railway tracks using digital image processing.

scholarly journals Elephant Intrusion Detection and Repulsion System using Matlab

2020 ◽  
Vol 9 (5) ◽  
pp. 37-39
Keyword(s):  
Image Processing ◽  
Railway Track ◽  
Prototype Model ◽  
Indian States ◽  
Railway Line ◽  
Railway Tracks ◽  
Time Interaction ◽  
Engine Driver ◽  
Pass Through ◽  
Wild Life

Elephant intrusion across the railway track leads to Human-Elephant conflict, collisionof trains, elephant death and injuries. Railway tracks pass through wild life habitats in several Indian states. In India, due to railway cross lines,the accidents that resulted in the death of249 elephants during 1987-2018.The surveillance and monitoring the elephants in the railway line in the forest is very difficult. The speed of the train in India among forest areas is around 50-55km/h during day and 35km/h at night, the engine driver can’t stop the train once the elephant is seen. So, we develop a system to detect the elephant intrusion at a certain distance by using sensors and image processing using MATLAB, creates an alert to engine driver and forest officer of the region and repel the elephant from the railway line. Hence we are creating a prototype model for real time interaction of elephant intrusion across railway tracks

scholarly journals Analysis of models for image processing when implementing an object detection system on a railway track

2021 ◽  
Vol 1 (1) ◽  
pp. 43-51
Author(s):  
A. T. Tisetsky
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Control System ◽  
Detection System ◽  
Railway Track ◽  
Rolling Stock ◽  
Global System ◽  
Railway Tracks ◽  
Railway Industry ◽  
And Training

With the development of the railway industry, informatization of society and the automation of many technological processes, it becomes possible to create an automatic control system, diagnostics and safety of locomotive movement. One of the most important systems of this complex is the system for detecting objects on railway tracks, ruptures of the railway bed and its turns. Such a system can be developed in the form of a camera installed on a locomotive and information processing systems on board each rolling stock, or a global system for remote processing of information from several locomotives. Regardless of the implementation of the system, there is a need to create a block for detecting objects on images coming from cameras. The implementation of this block is possible using interacting full-convolutional and convolutional neural networks and training on a dataset covering various situations occurring on the railway tracks.

Deep Learning Based Object and Railway Track Recognition Using Train Mounted Thermal Imaging System

2020 ◽  
Vol 17 (11) ◽  
pp. 5062-5071
Author(s):  
Rajiv Kapoor ◽  
Rohini Goel ◽  
Avinash Sharma
Keyword(s):  
Deep Learning ◽  
Thermal Imaging ◽  
Imaging System ◽  
Night Vision ◽  
Railway Track ◽  
Validation Data ◽  
Ir Camera ◽  
Railway Tracks ◽  
Railway Safety ◽  
Thermal Imaging System

An intelligent railways safety system is very essential to avoid the accidents. The motivation behind the problem is the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. Continuous research is being carried out by distinct researchers to ensure railway safety and to reduce accident rates. In this paper, a novel method is proposed for identifying objects (obstacles) on the railway tracks in front of a moving train using a thermal camera. This approach presents a novel way of detecting the railway tracks as well as a deep network based method to recognize obstacles on the track. A pre-trained network is used that provides the model understanding of real world objects and enables deep learning classifiers for obstacle identification. The validation data is acquired by thermal imaging using night vision IR camera. In this work, the Faster R-CNN is used that efficiently recognize obstacles on the railway tracks. This process can be a great help for railways to reduce accidents and financial burdens. The result shows that the proposed method has good accuracy of approximately 83% which helps to enhance the railway safety.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

Analysis of the 9th November 1990 flare

2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin
Keyword(s):  
Image Processing ◽  
Two Dimensional ◽  
Temporal Behaviour ◽  
Contour Maps ◽  
Dimensional Measurements ◽  
Processing Software ◽  
Image Processing Software

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.

The 'well-known' theory of electron image formation

1983 ◽  
Vol 41 ◽  
pp. 288-289
Author(s):  
M.A. O'Keefe ◽  
W.O. Saxton
Keyword(s):  
Image Processing ◽  
Image Formation ◽  
Source Profiles ◽  
Electron Image

A recent paper by Kirkland on nonlinear electron image processing, referring to a relatively new textbook, highlights the persistence in the literature of calculations based on incomplete and/or incorrect models of electron imageing, notwithstanding the various papers which have recently pointed out the correct forms of the appropriate equations. Since at least part of the problem can be traced to underlying assumptions about the illumination coherence conditions, we attempt to clarify both the assumptions and the corresponding equations in this paper, illustrating the effects of an incorrect theory by means of images calculated in different ways.The first point to be made clear concerning the illumination coherence conditions is that (except for very thin specimens) it is insufficient simply to know the source profiles present, i.e. the ranges of different directions and energies (focus levels) present in the source; we must also know in general whether the various illumination components are coherent or incoherent with respect to one another.

Recent Applications of High Resolution Electron Microscopy to Crystalline Arrays of Virus Particles

1978 ◽  
Vol 36 (3) ◽  
pp. 470-482 ◽  
Author(s):  
R.W. Horne
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Analytical Techniques ◽  
Staining Technique ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
Full Potential ◽  
Virus Particles ◽  
Resolution Electron ◽  
Wide Range

The technique of surrounding virus particles with a neutralised electron dense stain was described at the Fourth International Congress on Electron Microscopy, Berlin 1958 (see Home & Brenner, 1960, p. 625). For many years the negative staining technique in one form or another, has been applied to a wide range of biological materials. However, the full potential of the method has only recently been explored following the development and applications of optical diffraction and computer image analytical techniques to electron micrographs (cf. De Hosier & Klug, 1968; Markham 1968; Crowther et al., 1970; Home & Markham, 1973; Klug & Berger, 1974; Crowther & Klug, 1975). These image processing procedures have allowed a more precise and quantitative approach to be made concerning the interpretation, measurement and reconstruction of repeating features in certain biological systems.

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