A Novel Water Marking Scheme Using Feature Selection technique using Particle of Swarm Optimization

Abstract

Digital watermarking techniques play an important role in privacy protection and copyright protection for multimedia data. In current research trend various watermarking technique are available such as spatial watermarking technique and frequency based watermarking technique. In frequency based watermarking technique used wavelet transform function and Fourier transforms function. The transform based watermarking techniques are very good in quality assessment of watermark image, but lacked from a problem of geometrical attack such as rotation attack translation attack and noise attack. The transformation of attack in watermark multimedia data compromised with the problem of privacy protection and copyright act. For the minimization of geometrical attack used various techniques such as feature selection based watermarking and support vector based multi-class coefficient selection technique. In feature selection based watermarking technique used wavelet transform function for feature extraction. The extracted feature selected by searching technique such as direct search and heuristic based searching technique. The searched coefficient of wavelet transform used for embedding process. In this dissertation proposed a support vector machine based watermarking technique. Support vector based watermarking technique used a classification of feature attribute of digital image. After the classification of feature attribute estimate the correlation coefficient of attribute and apply embedding process, the process of embedding done by person’s coefficient. Person’s coefficient selects a position of embedded water mark in host image. Our experimental result shows better result in compression of support vector based water marking technique. For the estimation of results used three standard parameter PSNR embedding time and number of correlation of feature of watermark image.

Authors and Affiliations

Vasimraj Siraj Tamboli, Abhijeet Dinkar Cholke, Ravindra Sundarlal Kakade

Keywords

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  • EP ID EP20078
  • DOI -
  • Views 301
  • Downloads 5

How To Cite

Vasimraj Siraj Tamboli, Abhijeet Dinkar Cholke, Ravindra Sundarlal Kakade (2015). A Novel Water Marking Scheme Using Feature Selection technique using Particle of Swarm Optimization. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(4), -. https://europub.co.uk/articles/-A-20078