## 5 Experimental Results  
The proposed algorithm is compared with other Wavelet algorithms using Lena, Cameraman, Baboon, Boat, Barbara and Peppers images. Figure 4 demonstrates cover images where the embedding process is applied. Table 1 shows PSNR values for a watermarked image using Wavelet, block-based Wavelet and flexible scaling factor-based block Wavelet. Results show that the proposed algorithm gives better image quality values in Lena, Baboon, Boat, Barbara and Peppers images, excepting Cameraman [44; 45]. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **DWT (dB)** & **Block-DWT (dB)** &
\begin{tabular}{c} **FSF Based** \\ **Block-DWT (dB)** \\ \end{tabular} \\ \hline Lena & 41.16 & 43.25 & 44.41 \\ Cameraman & 43.68 & 43.61 & 42.19 \\ Baboon & 42.27 & 42.86 & 42.89 \\ Boat & 39.67 & 40.82 & 42.86 \\ Barbara & 39.82 & 39.84 & 43.19 \\ Peppers & 40.72 & 43.43 & 44.27 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Peak signal to noise ratio (PSNR) values after embedding binary image to the cover images. Figure 4: Cover images for watermarking embedding process. Embedding with FSF-based block DWT is compared with the other most common watermarking algorithms DCT and DFT. The cover image is transformed via discrete cosine transformation and the binary logo is embedded into the medium frequencies after zig-zag order. In the DFT algorithm, the binary watermark is embedded into the high magnitudes and is located in the corner of the image after Fourier Transformation. Table 2 demonstrates PSNR values of images after DCT, DFT and the proposed methodology. Results shows that the proposed algorithm higher PSNR values than the DCT and DFT algorithms. There are several measures of good watermarking algorithms such as robustness, security, data capacity and resistance. Image watermarking can be tested with geometric, temporal and statistical attacks. Temporal attacks are usually used for video sequences and 3D applications. Frame dropping, frame averaging and frame swapping are some of the frequently used attacks in the videos. In this work, we applied several statistical image geometric attacks to compare the proposed watermarking algorithm with the other two Wavelet algorithms [46]. Table 3 demonstrates PSNR values after the most commonly used attacks rotation, cropping, histogram equalization, contrast adjustment, JPEG 25, Gaussian noise, resizing and salt and pepper noise. PSNR values after attacks are always less than the PSNR value of the watermarked image. There are three algorithms tested with several images. Method A represents the Wavelet algorithm, B represents block-based Wavelet and C represents the proposed algorithm [47; 48]. Experimental results show that the proposed algorithm FSF-based block DWT has better results than the other two Wavelet algorithms in the literature. Time complexity in information hiding systems are based on the algorithm used to embed the watermark into the cover image. In addition to that, the pre-processing stage for the cover image is also another important criterion for finding out time complexity. The most common watermarking algorithm DWT has O(N), DCT has O(NlogN) and DFT has O(N2) time complexity. Block-based DWT and proposed FSF-based Block-DWT algorithms have O(NlogN) time complexities. Table 4 shows CPU times in embedding and extraction for binary image watermarking into the grey scale Lena cover image. The block-DWT algorithms require more CPU time for both embedding and extraction than non-block-DWT watermarking. Table 5 shows similarity ratios after attacks for Lena, Cameraman, Baboon, Boat, Barbara and Peppers images. SR represents the quality of the extracted watermark. If the ratio is equal to 1, it means the extracted watermark is exactly the same as an embedded watermark. Experimental results show that SR values are greater than 0.8 after attacks. The FSF-based watermarking algorithm is more successful than the other two Wavelet algorithms in the extraction [49].