Multi-objective Particle Swarm Optimization Based Image Watermarking Scheme

Abstract

Abstract.A novel image watermarking scheme based on the statistics of the blocked DCT coefficients. The watermark is embedded into the middle frequency of those DCT coefficients by modulating the number of those positive and negative coefficients. In order to achieve better robustness and imperceptibility, multi-objective particle swarm optimization (MPSO) has been used in the watermark embedding and extracting procedure. The particle swarm optimization is applied to obtain optimum multiple scaling factors and the embedding strength. The experimental results show that the proposed scheme has significant improvement in term of imperceptibility and robustness under various general attacks.

Biometric Watermarking Schemes Based on QR Decomposition and Schur Decompositon in RIDWT Domain

“…Optimization algorithms in a watermarking scheme are usually used to determine optimal embedding parameters or embedding positions. Some of algorithms used to find suitable parameters are Ant Colony Optimization (ACO) [28,29], Artificial Bee Colony (ABC) [30][31][32], Cuckoo Search (CS) [33], Differential Evolution (DE) [34][35][36], Firefly Algorithm (FA) [25,[37][38][39][40][41], Genetic Algorithm (GAL) [42][43][44], Particle Swarm Optimization (PSO) [45][46][47] etc. FA, inspired by the behaviors of fireflies, have been found to be more advantageous compared with other nature-inspired algorithms and to present good optimal solutions for many problems.…”