Icics2017079

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International Conference on Intelligent Computing and Systems

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International Conference on Intelligent Computing and Systems 2017 [ICICS 2017]

ISBN Website Received Article ID

978-81-933235-5-7 icics.asia 10 – January – 2017 ICICS079

VOL eMail Accepted eAID

01 icics@asdf.res.in 28 - January – 2017 ICICS.2017.079

A Real Time Analytical Architecture for Weather Fore Casting 1,2

U Karthick1, R Sathishkannan2, P Gomathi3 Department of CSE, 3Department of EEE, NSN College of Engineering, India

Abstract: In each technology there is one same challenge added to Big Data collected from remote sensing application than it collecting the information, and extracting the most required information in a proficient way leads a system on the way to major computational challenges, such the challenges are examine, load, and aggregate, everyplace data are remotely collected. In the view of observance above stated factors, there is a necessity for designing system architecture those receptions both real-time data processing, as well as offline data processing. In this paper, we propose an analytical architecture on big data for remotely detected data from satellite application. The proposed architecture comprises three main units:1) Remote sensing Big Data acquisition unit (RSDU); 2) Data processing unit (DPU); and 3) Data analysis decision unit (DADU). In starting stage, RSDU gets data from the satellite and then transmit this data to the Base Station, where the initial processing of data takes place. Next, DPU acting an important role in architecture for effective processing of real-time Data collected from remote application by given that filtration, load balancing, and parallel processing. In final stage, DADU is the top most layer unit of the offered architecture, which one is responsible for compilation, loading of the results, and Generation of decision based on the results acknowledged from DPU.

ISBN Website Received Article ID

978-81-933235-5-7 icics.asia 10 – January – 2017 ICICS080

VOL eMail Accepted eAID

01 icics@asdf.res.in 28 - January – 2017 ICICS.2017.080

Quick Response Barcode Denoising and Deblurring Using Wiener Filter 1

J Stephy Graph1, P Gomathi2 Assistant Professor, Department of CSE, Professor & Dean, Department of EEE NSN College of Engineering & Technology, India 2

Abstract: The quick response (QR) code is two dimensional which is similar to a barcode. The difference between QR code and barcode is that, a barcode holds information only in the horizontal direction, while a QR code can hold information both horizontally and vertically. This is the reason why QR codes are referred to as two-dimensional. The two methods are proposed to deblur and denoise the QR barcode. The contents like text, links, etc can be hidden in the QR code and those hidden contents can be read using smart phone scanners. The size of the QR code image varies depending upon the length of the texts or links. The visual quality of QR code image is improved by using the wiener filter.

This paper is prepared exclusively for International Conference on Intelligent Computing and Systems 2017 [ICICS 2017] which is published by ASDF International, Registered in London, United Kingdom under the directions of the Editor-in-Chief Dr M Sivaraja and Editors Dr. Daniel James, Dr. Kokula Krishna Hari Kunasekaran and Dr. Saikishore Elangovan. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage, and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honoured. For all other uses, contact the owner/author(s). Copyright Holder can be reached at copy@asdf.international for distribution.

2017 © Reserved by Association of Scientists, Developers and Faculties [www.ASDF.international]


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