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Image Processing Based Disease Detection for Sugarcane Leaves

Sugarcane is one of the most important crop in India. Indian sugar industry is the second largest agro based industry, next only to the textiles. But, being long durational crop, sugarcane is prone to the number of disease caused by pathogens viz. fungi, bacteria, viruses and phytoplasmas like organisms. Image processing techniques has been proved to be changing the scenario of agriculture in India with a number of research and applications like automatic disease detection, drone based pesticides and fertilizer dispensing, estimation of yield, vegetative growth, fruit sorting etc. This research is carried out to study effectiveness of Image Processing and computer vision techniques for detection of disease in sugarcane plants by observing the leaves. Few major diseases in sugarcane plant like red rot, mosaic and leaf scald have been studied and detection algorithm for the same has been implemented in this research work.

Published by: Arifa Khan, Manmohan Singh Yadav, Dr. Shafeeq Ahmad

Author: Arifa Khan

Paper ID: V3I4-1267

Paper Status: published

Published: July 31, 2017

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Review Paper

Crack Detection in Railway Track Using Image Processing

Computer vision can provide many potential advantages over manual methods of railway track inspection. Great levels of performance can be achieved through the automation of inspection using computer vision systems, as they allow scalable, quick, and cost-effective solutions to tasks otherwise unsuited to humans. At a minimum, railway track components can be objectively and quantitatively inspected, as the system does not suffer from fatigue or the subjectivity inherent with human inspectors. The digital nature of the data collection involved with a computer vision based method, archiving inspection results and trending of the data becomes feasible, leading to more advanced failure prediction models for maintenance scheduling and a more thorough understanding of railway track structure. In this research paper, a computer vision based method is presented. A system has been suggested which can periodically take images of the railway tracks and compared with the existing database of non-faulty track images on a continuous basis. If a fault arises in the track section, the system will automatically detect the fault and necessary actions can be taken, to avoid any mis-happening.

Published by: Aliza Raza Rizvi, Pervez Rauf Khan, Dr. Shafeeq Ahmad

Author: Aliza Raza Rizvi

Paper ID: V3I4-1266

Paper Status: published

Published: July 31, 2017

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Research Paper

Gateway Based Energy Efficient Routing: GEER

Wireless Sensor Networks comprise of an extensive number of little and minimal effort sensor nodes energised by little non rechargeable batteries and furnished with different detecting gadgets. WSN is sent, most likely in a rough and inhospitable landscape, it is relied upon that all of a sudden dynamic to accumulate the required information for a few times when something is identified, and after that outstanding to a great extent idle for drawn out stretches of time. In this way, scientists are constantly persuaded to configuration create effective energy efficient plans and relating calculations with a specific end goal to give sensible optimal utilization of battery power and to enhance the system lifetime for WSNs. The lifetime of wireless sensor network systems is enhanced by cluster location and balancing the network loading among the clusters. In this research work a gateway based technique has been contemplated. The nodes have been isolate into ordinary, middle of the road and progressed in light of their vitality arrangement and every class has its own particular paradigm for determination likelihood. The calculation performs well as far as number of alive nodes, network lifetime, average energy and so forth. A comprehensive investigation as far as different graphical parameters is additionally introduced in this work.

Published by: Naziya Anjum, Masood Ahmad, Dr. Shafeeq Ahmad

Author: Naziya Anjum

Paper ID: V3I4-1263

Paper Status: published

Published: July 31, 2017

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Universal Dependencies of Sanskrit

We present the first steps towards a treebank of Sanskrit within the Universal Dependencies framework. our dataset is tiny at the moment, consisting of less than 200 sentences—a result of a summer internship project. Nevertheless, this seems to be, to the best of our knowledge, the first publicly available piece of syntactically annotated Sanskrit text.We also present a parsing experiment, with results surpassing delexicalized parsing.

Published by: Puneet Dwivedi, Easha Guha

Author: Puneet Dwivedi

Paper ID: V3I4-1252

Paper Status: published

Published: July 31, 2017

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Parametric Study of Multi-Storey Buildings for Blast Load

An explosive is a mixture of compounds which, when initiated by heat, impact, friction, or shock, undergoes a rapid decomposition in the form of heat and gas where tremendous amounts of energy is released. Full or partial collapse of buildings, minor and major cracks are the most perceptible type of failure that may result from a blast load. The level of damage produced in a structure depends on charge weight, distance of building from point of explosion . This work deals with study of nature of blast loading and its effects on regular and irregular multi-storey building with and without shear wall opening.

Published by: Prajna, Deepthishree S. Aithal

Author: Prajna

Paper ID: V3I4-1248

Paper Status: published

Published: July 31, 2017

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Review of Classification of Copy Move Forgery

Copy move forgery is one of the important fields in forensic science for image pro-cessing. Image forgery is different like copy move attack, image splicing and image retouching. In this paper review the specific copy move forgery images and its detection methods.

Published by: Rekha Devi, Deepti Chauhan

Author: Rekha Devi

Paper ID: V3I4-1247

Paper Status: published

Published: July 31, 2017

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