Enhanced Fast Robustness Digital Image Watermarking Scheme with Secure Chaotic Encryption Scheme Via Selecting Optimal Feature Points

K. Sathyabama; V. Manikandan

doi:10.15866/irecos.v9i8.2207

Enhanced Fast Robustness Digital Image Watermarking Scheme with Secure Chaotic Encryption Scheme Via Selecting Optimal Feature Points

K. Sathyabama^(1*), V. Manikandan⁽²⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irecos.v9i8.2207

Abstract

In recent years, with the rapid development of internet, digital data has been widely used in various science and engineering applications. But, this development has also led to several threats and attacks from the intruders. Most of the organizations are very much concerned about the Illegal copyright activities which have become a series issue. A number of copyright protection schemes have been developed in the literature. Watermarking is one of the best known methods for copyright protection. Earlier Bit Error Rate (BER) is been observed to provide good results for choosing the optimal feature region from the watermarked image. However it fails to produce more accurate image quality measures. This research work mainly focuses on a novel technique implemented based on the simulated attacking approach and the GA-based Multi Dimensional Knapsack Problem (MDKP) solving technique to select the most sufficient feature regions for robust digital image watermarking without affecting the image quality. A major limitation in existing methods is the security problems which lead to decrease in the integrity of digital watermarking scheme. With that problem, the definite optimization problems (variant problems) cannot be resolved using genetic algorithms. To focus on the above mentioned problems, the proposed work uses two approaches. Chaotic Iterative Process encryption scheme is used to solve the security problems for watermarking image. Next, the optimal feature points can be chosen from the watermarked image by Modified version of Peak Signal Noise Ratio (MPSNR). MPSNR is based on the enhanced quality measurement of which point opposes the predefined and undefined attacks. With those two approaches the PSO algorithm is employed as a search strategy for identifying an optimal feature subset. The experimental results illustrates that comparing with various well-known feature-based techniques, the proposed method shows better performance in robust and more secure digital watermarking.
Copyright © 2014 Praise Worthy Prize - All rights reserved.

Keywords

Feature Detector; Copyright Protection; Digital Watermarking; Chaotic Iterative Process Encryption; Modified Version of Peak Signal Noise Ratio (MPSNR); Particle Swarm Optimization; SUSAN Detector; Optimal Feature Point Set; Predefined and Undefined Attac

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