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Automated LED Text Recognition with Neural Network and PCA –A Review

Light-emitting diodes text dot-matrix text (LED text) is being widely used for displaying information and announcements. LED display for modernization of society and catch on for its versatile application with many benefits. Existing paper used k-nearest neighbor(k-NN) approach, low computation complexity method for pattern recognition, is used to recognition character component as any class of character and canny edge was used to detect character pixels when appear in led display area from scene images. The drawback of existing system is that it cannot handle text line with non-uniform color and containing less than 3 characters. It also cannot detect continuous LED text. Our proposed system will utilize the probabilistic neural network (PNN) classification to add the robust classification for the higher level of the adaptiveness. Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. Our proposed system will achieve better detection and recognition rate than existing system.

Published by: Sonu Rani, Navpreet Kaur

Author: Sonu Rani

Paper ID: V2I3-1185

Paper Status: published

Published: June 20, 2016

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Research Paper

A Novel Approach for the Reduction of Noise

Most of the current speckle reduction system uses various filters .There are various filters for reducing the speckle noise reduction. But due to some drawbacks these traditional filters cannot remove speckle noise efficiently. So a hybrid technique speckle noise reduction using anisotropic filter based on wavelets is used. In this paper the necessary idea of an uncorrupted image from the noisy image is identified as “denoising”. Choosing the most excellent way plays a very important role for getting the desired image. So in this thesis report a study is made on “Speckle Noise reduction using anisotropic filter based on wavelets”. There are various existing techniques to remove the speckle noise reduction but due to some drawbacks these techniques cannot remove speckle noise efficiently. The adaptive filters that are Kuan filter, Lee filter, and Frost filter are not able to remove a full removal of speckle without losing any edges because they relies on local statistical data and this statistical data depends upon window size and shape. As these existing filters are very much sensitive to the window shape and window size. If the window shape is very much larger than over smoothing will occurs. As the size of window is smaller than the smoothing ability of the window will reduce. So to overcome these limitations, a new hybrid technique that combines wavelet based denoising and anisotropic diffusion filter is proposed. Wavelet is dependent on both frequency and time domain. It is frame based approach. It provides better resolution and it does not depend upon the window size. In addition the anisotropic filter is based on partial differential equation approach.

Published by: Bodh Raj, Arun Sharma, Kapil Kapoor, Divya Jyoti

Author: Bodh Raj

Paper ID: V2I3-1184

Paper Status: published

Published: June 17, 2016

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Review Paper

Noise Reduction: A Review

Most of the current speckle reduction system uses various filters .There are various filters for reducing the speckle noise reduction. But due to some drawbacks these traditional filters cannot remove speckle noise efficiently. So a hybrid technique speckle noise reduction using anisotropic filter based on wavelets is used. In this paper the necessary idea of an uncorrupted image from the noisy image is identified as “denoising”. Choosing the most excellent way plays a very important role for getting the desired image. So in this thesis report a study is made on “Speckle Noise reduction using anisotropic filter based on wavelets”. There are various existing techniques to remove the speckle noise reduction but due to some drawbacks these techniques cannot remove speckle noise efficiently.

Published by: Bodh Raj, Arun Sharma, Kapil Kapoor, Divya Jyoti

Author: Bodh Raj

Paper ID: V2I3-1183

Paper Status: published

Published: June 17, 2016

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A Review on IEEE-754 Standard Floating Point Arithmetic Unit

Floating point operations in digital systems form an integral part in the design of many digital processors. Digital Signal Processor is the most important application of floating point operations. In the recent years many approaches for floating point operations have been proposed and their merits and demerits are compared. For floating point operations the operands are first converted into IEEE 754 format in either single precision or double precision format. The arithmetic operations are performed on the significant part of the IEEE format. In this paper various floating point operation unit architectures are reviewed. Few designers work on high speed architectures for reducing the delay of the overall circuit while others work on the area utilization parameters. Then the conclusion is drawn based on various architectural analyses.

Published by: Monika Maan, Abhay Bindal

Author: Monika Maan

Paper ID: V2I3-1182

Paper Status: published

Published: June 16, 2016

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Hybrid Exemplar-Based Image in Painting Algorithm using Non Local Total Variation Model

Exemplar-based algorithms are a popular technique for image in painting. They mainly have two important phases: deciding the filling-in order and selecting good exemplars. Traditional exemplar-based algorithms are to search suitable patches from source regions to fill in the missing parts, but they have to face a problem: improper selection of exemplars. To improve the problem we introduction modified exemplar based using non local total variation model which include two main step patch priority and patch completion. Experimental results show the superiority of the proposed method compared to the competitive methods. The proposed method may be used for restoration of digital images of defective or damaged artifacts.

Published by: Preeti Gupta, Kuldip Pahwa

Author: Preeti Gupta

Paper ID: V2I3-1181

Paper Status: published

Published: June 16, 2016

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Multi-level Authentication for Internet of Things to Establish Secure Healthcare Network

The Cloud based healthcare monitoring sensor networks (C-HMSN) consist of a number of wireless nodes connected to each other using wireless connections. As these wireless nodes are connected to base stations so they are highly prone areas for hacking attacks. During data analysis there is need to secure cryptographic keys when the HMSN nodes are in working condition, for secure propagation of the sensitive information. An Efficient corporate key management and distribution scheme is required to maintain the data security in HMSNs. Existing cryptographic key management and distribution technique usually consume higher amount of energy and put larger computational overheads on Wireless Sensor Nodes. The cryptographic keys are used on different levels of HMSN communication i.e. neighbor nodes, cluster heads and base stations. In this paper we will present corporate improved key management architecture, called SECURE KEY EXCHANGE adaptable for the HMSNs, to enable comprehensive, trustworthy, user-verifiable, and cost-effective key management. It allows only authorized applications to use the keys and administrator can remotely issue authenticated commands and verify system output. In addition, it also has to be improved to work with HMSN nodes, which means it must use less computational power of the HMSN. The wireless sensor node should be energy efficient, increasing the life of wireless sensor network.

Published by: Shilpa Kansal, Navpreet Kaur

Author: Shilpa Kansal

Paper ID: V2I3-1179

Paper Status: published

Published: June 16, 2016

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