Affiliations: [a] Akshaya College of Engineering and Technology, Anna University, Coimbatore, Tamilnadu, India
| [b] Department of Computer Science and Engineering, Akshaya College of Engineering and Technology
| [c] Department of Artificial Intelligence, G.H. Raisoni College of Engineering, Nagpur, India
| [d] Mechanical Engineering Department, College of Engineering, King Khalid University, Abha, Asir, Kingdom of Saudi Arabia
| [e]
E.G.S Pillay Engineering College, India
Correspondence:
[*]
Corresponding author. A. Umaamaheshvari, Akshaya College of Engineering and Technology, Anna University, Coimbatore, Tamilnadu, India Pin Code: 642 109. E-mail: [email protected].
Abstract: The optimization algorithms mimic the process of natural evolution. In watermarking, appropriate positions to insert the watermark is identified by the image that covers. These positions represent the populations of genetic algorithms. The major drawback in genetic algorithm are that it may get stuck-up at a local optimum while moving towards the best global solution and hence the result is poor when compared to other local optimization techniques. The proposed work based on Bandelet based biogeography firefly hybrid algorithms. The Number of pixels, Intensity of the pixel and contrast are considered for watermarking. The redundancy is reduced by Bandelet and used to determine the best location to embed the information into an image both locally and globally. Results of these techniques are compared based on coefficient correlation, index structural similarity, and noise ratio from peak signal.
Keywords: Biogeography firefly algorithm, genetic algorithm, optimization, peak signal to noise ratio
