Informatics Publishing Limited

Bibi Isac ¹, V. Santhi ¹, Arunkumar Thangavelu ¹

Affiliations
1 School of Computing Science and Engineering, VIT University, Vellore, IN

Abstract

Copyrights protection of digital data become inevitable in current world. Digital watermarks have been recently proposed as secured scheme for copyright protection, authentication, source tracking, and broadcast monitoring of video, audio, text data and digital images. In this paper a method to embed a watermark in region of non-interest (RONI) and a method for adaptive calculation of strength factor using neural network are proposed. The embedding and extraction processes are carried out in the transform domain by using Discrete Wavelet Transform (DWT). Finally, the algorithm robustness is tested against noise addition attacks and geometric distortion attacks. The results authenticate that the proposed watermarking algorithm does not degrade the quality of cover image as the watermark is inserted only in region of non-interest and is resistive to attacks.

Keywords

Digital Watermarking, Invisible Watermarking, Neural Networks Based Watermarking Technique, Transform Domain Watermarking, Region of Non-Interest Based Watermarking.

Full Text

     

V. Santhi ¹, Arunkumar Thangavelu ¹

Affiliations
1 School of Computing Sciences and Engineering, VIT University, Tamil Nadu, IN

Abstract

Digital watermarking technique emerged as a tool for protecting the multimedia data from copyright infringement. In digital watermarking an imperceptible signal is embedded into the host image, which uniquely identifies the ownership. In the proposed algorithms, DNA sequence is used as a digital watermark, as the DNA sequences are unique and difficult to copy. This paper proposes two algorithms namely content based watermark algorithm using DNA sequence (CBDNA) and user specified watermark algorithm using DNA sequence (USDNA). In CBDNA the DNA sequence is generated from the cover data itself whereas in USDNA input data is chosen by the user and DNA sequence is generated based on the input data. These DNA sequences serve as a watermark for the cover data. The quality of the cover image and extracted watermark is measured using peak signal to noise ratio (PSNR) and normalized correlation (NC) respectively. The calculated values are tabulated and it shows that the proposed algorithm is withstanding many attacks, since watermark is available in all the frequency range of cover data.

Keywords

Deoxyribonucleic Acid (DNA), Discrete Wavelet Transform (DWT), Content Based Watermarking Algorithm Using DNA Sequence (CBDNA), User Specified Watermarking DNA sequence (USDNA).

Full Text

     

Arunkumar Thangavelu ¹, N. Manoharan ²

Affiliations
1 School of Computer Science and Engineering, VIT University, Vellore – 632014, Tamil Nadu, IN
2 Computer Science, P. A. College, Manomaniam Sundaranar University, Tirunelveli – 627012, Tamil Nadu, IN

Abstract

Objectives The farmers are getting far less cost for their farming products since they didn’t know where to offer for the best cost. This issue could be settled by this paper. Methods/Statistical Analysis: We worked with Historical Data of various agricultural commodities production, demands and pricing at different locations using MongoDB, a NoSQL database tool. A Module where the Buyers of Agricultural Commodities would enter their need and the costs they offer, for commodities. Demand qualities and Current Price datasets are created. The calculations for each of the Farmer Module and Buyer Module were composed and executed to satisfy the point of guaranteeing that the farmers can offer his wares at the ideal cost. Findings: Making a Module, where the Buyers of Agricultural Commodities would enter their need and the costs they will offer, store these points of interest and in light of these subtle elements, Demand qualities, and Current Price datasets are created. Farmer modules were created with the available agricultural commodities and their cost, a location of availability. The calculations for each of the Farmer Module and Buyer Module were composed and executed effectively. The calculations were tried for different situations and the normal results were figured it out. Examine the information and the farmer’s need (i.e) estimation called as horticulture yield investigation, and in this way discover the different valuable examples and making sense of the best methodologies at the agriculturists to cost and offer their yields in various locales at various times of the year. To satisfy the point of guaranteeing that the rancher can offer his wares at the most ideal cost. Applications/Improvements: This application could be moved to the cloud with MongoDB server and the farmers and purchasers will be given a separate login id. Total system may be available in web.

Keywords

Agriculture Business, Agricultural Commodities, Big Data, NoSQL, MongoDB.

Full Text