A Nature Based Computing Technique for Image Watermarking using Bacterial Foraging Optimization, Wavelet and Cosine Transform

Abstract

The Watermarking technique is used for the purpose of broadcast monitoring, copyright protection, integrity verification and authentication. Its application extends in fingerprinting and content description. In literature several methods like DWT, DCT are presented and embedded which occupies maximum energy. The watermarking techniques use lossy data compression due to strong energy compaction. The new methods and optimization techniques are required. The paper presents a new design and implemented by nature based computing. The proposed method combines the advantage of the wavelet transform and cosine transform. The proposed Bacterial Foraging Optimization technique hybrid with DWT and DCT increase the performance of watermarking of digital images. The high-frequency area of the image is used in this methodology. The method is comparable for Genetic Algorithms (GAs). Selected type of image of PSNR & NCC is processed in MATLAB. The effective results are compared with DWT-DCT algorithm, DWT and multiple images. NCC (normalized cross correlation), PSNR (Peak signal to noise ratio) value and IF (image fidelity) for different techniques are compared. The DWTDCT-BFO based watermarking performance is found best.