Informatics Publishing Limited

R. Punidha ¹, S. Anisha Vincy ², Mary Judith ², D. Ramya ²

Affiliations
1 Department of Computer Science and Engineering, Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600062, Tamil Nadu, IN
2 Department of Information Technology, Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College, Avadi, Chennai - 600062, Tamil Nadu, IN

Abstract

Background/Objectives: The main objective of the proposed work is to get the permission for accessing element through remote authentication by hiding encrypted biometric signal within image of the user. Methods/Statistical Analysis: The biometric signal is encrypted using Arnold transform algorithm and hided into the cover image with Qualified Significant Wavelet Tree (QSWT). The image of the person is denoted as cover image. The Compressed cover image gets transmitted over wireless channel for remote authentication. The Inverse Wavelet Transform is used to separate encrypted signal and the cover image. The biometric signal gets decrypted by inverse Arnold transformation algorithm. Findings: The Arnold transform algorithm increases the Normalized Cross Corelation (NCC) value for normalizing the image in order to improve the quality of reconstructed image. Hence, the Mean Square Error (MSE) is decreased and Peak Signal to Noise Ratio (PSNR) value is increased in the proposed work. And so the error is minimized in the proposed system compared to the existing techniques. The problems identified in the existing systems such as data loss, complexity and accuracy in biometric signal has been overcome by the proposed system. Application/Improvements: The proposed system can be used in military purposes for sharing confidential data. The data can be accessed over remote areas in secured maner.

Keywords

Arnold Transform Algorithm, Authentication, Biometric Signal, Remote Systems, QSWT

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V. Saranya ¹, N. Matheswari ², R. Punidha ³, M. Soundarya ¹

Affiliations
1 Department of Information Technology, Vel Tech Multitech Engineering College, Chennai - 600062, Tamil Nadu, IN
2 Department of Information Technology, Eloka Enterprise Private Limited, Chennai - 600020, Tamil Nadu, IN
3 Department of Computer Science and Engineering, Vel Tech Multitech Engineering College, Chennai - 600062, Tamil Nadu, IN

Abstract

Background/Objectives: Wireless sensor network deployed over a geological area for monitoring environment and it communicates with connected nodes in the network for processing and gathering information. Methods/Statistical Analysis: This system proposes a framework for tracking, called Energy Efficient Tracking (EET), which defines the nodes of the spatial region around a target, called face. Instead of finding the target location in a face, we estimate movement of a target. Energy efficiency obtained due to tracking being performed by different clusters instead of using a faces. Findings: This system helps to reduce the energy consumption. Brink detection algorithm that enables the sensor network to be aware of target entering the face bit earlier, and to work in a timely fashion. An optimal selection algorithm is to select an appropriate sensor, which can result in having the best detection and low energy cost of transmitting data across the faces. This framework presented an efficient movement tracking system using clustering to overcome the communication latency among nodes. Application/Improvements: Energy efficiency is an important challenge in wireless sensor networks for target tracking applications. This framework proposed efficient tracking using clustering.

Keywords

Brink Detection, Clustering, Energy, Optimal Selection, Spatial, Tracking

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R. Krishnamoorthy ¹, K. Rajavijayalakshmi ¹, R. Punidha ¹

Affiliations
1 Department of Computer Science and Engineering, Anna University of Technology, Tiruchirappalli, IN

Abstract

In this paper, a new lossy to lossless image coding scheme combined with Orthogonal Polynomials Transform and Integer Wavelet Transform is proposed. The Lifting Scheme based Integer Wavelet Transform (LS-IWT) is first applied on the image in order to reduce the blocking artifact and memory demand. The Embedded Zero tree Wavelet (EZW) subband coding algorithm is used in this proposed work for progressive image coding which achieves efficient bit rate reduction. The computational complexity of lower subband coding of EZW algorithm is reduced in this proposed work with a new integer based Orthogonal Polynomials transform coding. The normalization and mapping are done on the subband of the image for exploiting the subjective redundancy and the zero tree structure is obtained for EZW coding and so the computation complexity is greatly reduced in this proposed work. The experimental results of the proposed technique also show that the efficient bit rate reduction is achieved for both lossy and lossless compression when compared with existing techniques.

Keywords

Orthogonal Polynomials Transform Coding, Integer Wavelet Transform, Embedded Zerotree Coding.

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