Data hiding methods are used to carry information from one place to another. Digital watermarking is one of the data hiding methods. Imperceptibility and capacity are the conflicting parameters in digital watermarking. The more the embedded information, lower the imperceptibility and vice versa. Imperceptibility factor (IF) is measured as peak signal to noise ratio (PSNR) of the image after embedding information. No such schemes exist in the literature in which an image can be chosen that may carry a desired capacity, while keeping imperceptibility as high as possible. In this scheme a two stage fuzzy rule based system (FRBS) is designed to choose the image among the list that is capable of holding desired capacity while achieving high imperceptibility at the same time. Validity of the proposed scheme is checked through simulation results of different types of images like natural and medical. Moreover, the proposed scheme is also robust against JPEG compression attack.
Digital Watermarking (DW) based on computational intelligence (CI) is currently attracting considerable interest from the research community. This article provides an overview of the research progress in applying CI methods to the problem of DW. The scope of this review will encompass core methods of CI, including rough sets (RS), fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GA), swarm intelligence (SI), and hybrid intelligent systems. The research contributions in each field are systematically summarized and compared to highlight promising new research directions. The findings of this review should provide useful insights into the current DW literature and be a good source for anyone who is interested in the application of CI approaches to DW systems or related fields. In addition, hybrid intelligent systems are a growing research area in CI.