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Sathappan, S.
- Efficient Lossless Image Compression using Modified Hierarchical Forecast and Context Adaptive System
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Authors
Affiliations
1 Department of Computer Science and Engineering, Erode Arts and Science College, Erode - 638009, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Erode Arts and Science College, Erode - 638009, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 34 (2015), Pagination:Abstract
Objective: The main intention of this investigation is to protect the sharpness of image through decreasing the bit rates in compression image. Also this scenario intends to accomplish the high compression ratio by using the lossless compression approaches. Methods: In this research, Hierarchical Forecast and Context Adaptive systems are introduced to provide the lossless compression color image. Modified Hierarchical Prediction Scheme is enhanced which overcomes the issue of enormous prediction error rate near edges and preserves the sharpness of images. This scenario considers the vertical, horizontal and diagonal (left up, left down and right up, right down) predictors to predict pixels. Diagonal predictor enhances the perdition accuracy of pixels in Hierarchical Prediction. Findings: In this work the methods used namely Context Adaptive Coding and Modified Hierarchical Prediction Scheme are used to preserve the sharpness of an image. The experimental tests conducted were proves that the proposed methodology can preserve the sharpness of the image efficiently rather than existing method. The experimental results of this work prove that the proposed methodology is improved in terms of all performance metrics called Bits Per Pixel (BPP), Compression Ratio, Mean Square Error rate (MSE) and Peak Signal to Noise Ratio (PSNR). Application/Improvement: The findings demonstrate that by using proposed MHPCA scheme the bit rates in compressed images are reduced significantly which preserves the sharpness of the image. MHPCA coding scheme also reduces the error rate considerably and produces higher compression ratio than the existing HPCA scheme.Keywords
Context Adaptive Coding, Lossless Color Image Compression, Modified Hierarchical Prediction- Multi Aspect Sparse Time Integrated Cut-off Authentication (STI-CA) for Cloud Data Storage
Abstract Views :242 |
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Authors
Affiliations
1 Department of Computer Science, Erode Arts and Science College, Erode–638009, Tamil Nadu, IN
1 Department of Computer Science, Erode Arts and Science College, Erode–638009, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 10, No 4 (2017), Pagination:Abstract
Objectives/Background: Cloud infrastructure is a pool of commuting resources such as information storage servers, application progress platforms, load balancers and virtual machines that are shared between the users for transactional processes with on demand process. However, transactional process lacks a secure authentication system, while it does not attest the trustworthiness of dynamic contents threats which outlaw the cloud system. Methods/Statistical Analysis: To establish the authenticity and avoiding improper data modification on cloud based data transactions, a framework called, multi aspect Sparse Time Integrated Cut-off Authentication (STI-CA) for Cloud Data Storage is designed. STI-CA framework commences with the password registry for each cloud user on the basis of two dimensional service matrices reducing the overhead incurred during user authentication by applying Sparse Vector Cloud User Registry. Next, by utilizing Time Integrated One Time Password, which is unique for each cloud user and each login reduces the execution time and space complexity as the cloud server does not maintain the password. Finally, the Cut-off Potential Cryptography prevents the unauthorized user modification on transactional data, therefore improving the security. Here the Amazon Simple Storage Service (Amazon S3) dataset is used for experiment using the JAVA coding with Cloudsim3. A series of simulation results are performed to test the data confidentiality, execution time, communication overhead and space complexity for obtaining transactional data and measure the effectiveness of STI-CA framework. Findings: STI-CA framework offers better performance with an improvement of the data confidentiality by 31%, reduces execution time by 20%, reduce communication overhead by 30% and also minimize space complexity by 22% compared to existing models of DRAFT and iCloud native Mac OS X respectively. Applications/Improvements: It can be further extended with implementation of new model with different parameters which improves more confidentiality and integrity.Keywords
Authentication, Cloud Data Storage, Cut-off, Multi Aspect, Password registry, Potential Cryptography, Sparse, Time Integrated.- Self Organized Quantum Key Authentication Technique for Secure Data Communication in Mobile Ad Hoc Network
Abstract Views :157 |
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Authors
S. Sangeetha
1,
S. Sathappan
1
Affiliations
1 Department of Computer Science, Erode Arts and Science College, Erode - 638112, Tamil Nadu, IN
1 Department of Computer Science, Erode Arts and Science College, Erode - 638112, Tamil Nadu, IN