# Improving DFT-Based Image Watermarking Using Particle Swarm Optimization Algorithm
## 5 Experimental Results and Discussion
### Analysis and Discussion
Estimation of the secret key can be very dangerous, especially for image content: if the database of images is stolen, the adversary would be able to infringe the copyright and intellectual property, so watermarking needs to be handled with care. In this way, when setting the fixed values for the secret key (pair of radiuses \(r_{1}\), \(r_{2}\)), the security of the conventional DFT-based watermarking is very compromised. To solve this security issue, the PSO algorithm has a fundamental role, finding the unique secret key to each image in a given dataset, moreover providing benefits in imperceptibility and robustness. Finally, Table 10 shows a comparison performance by considering the previously reported methods in [19; 20; 21; 22; 23; 24; 25; 26] and our proposal. A grid cell appears with a dash '-', when the authors did not report a criterion or simulation. Comparatively, we consider only relevant criteria, as they are the most essential in the design of a robust digital watermarking optimized by the PSO algorithm. For the sake of brevity, we perform a punctual comparison in Table 10. Is clear that our proposed method is outperformed by all the works in Table 10 in terms of watermark payload, because in all of them the purpose is prioritize the capacity of watermarking techniques. However, although the capacity is relatively high, there exist several drawbacks by the current state-of-the-art. One of them is related to the weakness against geometric distortions, focusing its attention only on the rotation, cropping and resizing. There exist more geometric distortions that need to be considered in the design of a robust watermarking. A trend in the current state-of-the-art is the use of PSNR as the imperceptibility metric in the fitness function of PSO. The benefits of the use of VIF instead of PSNR are clear, as shown along the experimental results in this paper. Future research in the scientific literature may consider another imperceptibility metrics different to PSNR in the fitness function of PSO, to obtain improvements in terms of the image quality of the watermarked images. Another important aspect is the number of images used in the experimental results as well as its bit depth resolution. In this sense, in Table 10 we show that almost all works in the current state-of-the-art [19; 21; 22; 24; 25; 26] performed experiments on a few digital images (less than 10 images) with 8-bit grayscale resolution, to exception of the work in [20] which consider 64 color images with 24 bit/pixel of resolution. However, considering a few images in a watermarking test may be a drawback for implementing the watermarking algorithm in large scale image datasets. In this way, massive testing in terms of imperceptibility and robustness considering large image datasets should be compulsory, as the case of our proposal that considers a dataset of 1000 color images with 24 bit/pixel of resolution. Finally, all proposals in Table 10 are competitive in terms of robustness against JPEG compression and noise image corruption.